Having published an earlier January 2024 US National Science Foundation (NSF) funding announcement for the TRAILS (Trustworthy AI in Law & Society) Institute yesterday (February 21, 2024), I’m following up with an announcement about the initiative’s first round of seed funding.
The Institute for Trustworthy AI in Law & Society (TRAILS) has unveiled an inaugural round of seed grants designed to integrate a greater diversity of stakeholders into the artificial intelligence (AI) development and governance lifecycle, ultimately creating positive feedback loops to improve trustworthiness, accessibility and efficacy in AI-infused systems.
The eight grants announced on January 24, 2024—ranging from $100K to $150K apiece and totaling just over $1.5 million—were awarded to interdisciplinary teams of faculty associated with the institute. Funded projects include developing AI chatbots to assist with smoking cessation, designing animal-like robots that can improve autism-specific support at home, and exploring how people use and rely upon AI-generated language translation systems.
All eight projects fall under the broader mission of TRAILS, which is to transform the practice of AI from one driven primarily by technological innovation to one that is driven by ethics, human rights, and input and feedback from communities whose voices have previously been marginalized.
“At the speed with which AI is developing, our seed grant program will enable us to keep pace—or even stay one step ahead—by incentivizing cutting-edge research and scholarship that spans AI design, development and governance,” said Hal Daumé III, a professor of computer science at the University of Maryland who is the director of TRAILS.
After TRAILS was launched in May 2023 with a $20 million award from the National Science Foundation (NSF) and the National Institute of Standards and Technology (NIST), lead faculty met to brainstorm how the institute could best move forward with research, innovation and outreach that would have a meaningful impact.
They determined a seed grant program could quickly leverage the wide range of academic talent at TRAILS’ four primary institutions. This includes the University of Maryland’s expertise in computing and human-computer interaction; George Washington University’s strengths in systems engineering and AI as it relates to law and governance; Morgan State University’s work in addressing bias and inequity in AI; and Cornell University’s research in human behavior and decision-making.
“NIST and NSF’s support of TRAILS enables us to create a structured mechanism to reach across academic and institutional boundaries in search of innovative solutions,” said David Broniatowski, an associate professor of engineering management and systems engineering at George Washington University who leads TRAILS activities on the GW campus. “Seed funding from TRAILS will enable multidisciplinary teams to identify opportunities for their research to have impact, and to build the case for even larger, multi-institutional efforts.”
Further discussions were held at a TRAILS faculty retreat to identify seed grant guidelines and collaborative themes that mirror TRAILS’ primary research thrusts—participatory design, methods and metrics, evaluating trust, and participatory governance.
“Some of the funded projects are taking a fresh look at ideas we may have already been working on individually, and others are taking an entirely new approach to timely, pressing issues involving AI and machine learning,” said Virginia Byrne, an assistant professor of higher education & student affairs at Morgan State who is leading TRAILS activities on that campus and who served on the seed grant review committee.
A second round of seed funding will be announced later this year, said Darren Cambridge, who was recently hired as managing director of TRAILS to lead its day-to-day operations.
Projects selected in the first round are eligible for a renewal, while other TRAILS faculty—or any faculty member at the four primary TRAILS institutions—can submit new proposals for consideration, Cambridge said.
Ultimately, the seed funding program is expected to strengthen and incentivize other TRAILS activities that are now taking shape, including K–12 education and outreach programs, AI policy seminars and workshops on Capitol Hill, and multiple postdoc opportunities for early-career researchers.
“We want TRAILS to be the ‘go-to’ resource for educators, policymakers and others who are seeking answers and solutions on how to build, manage and use AI systems that will benefit all of society,” Cambridge said.
The eight projects selected for the first round of TRAILS seed-funding are:
Chung Hyuk Park and Zoe Szajnfarber from GW and Hernisa Kacorri from UMD aim to improve the support infrastructure and access to quality care for families of autistic children. Early interventions are strongly correlated with positive outcomes, while provider shortages and financial burdens have raised challenges—particularly for families without sufficient resources and experience. The researchers will develop novel parent-robot teaming for the home, advance the assistive technology, and assess the impact of teaming to promote more trust in human-robot collaborative settings.
Soheil Feizi from UMD and Robert Brauneis from GW will investigate various issues surrounding text-to-image [emphasis mine] generative AI models like Stable Diffusion, DALL-E 2, and Midjourney, focusing on myriad legal, aesthetic and computational aspects that are currently unresolved. A key question is how copyright law might adapt if these tools create works in an artist’s style. The team will explore how generative AI models represent individual artists’ styles, and whether those representations are complex and distinctive enough to form stable objects of protection. The researchers will also explore legal and technical questions to determine if specific artworks, especially rare and unique ones, have already been used to train AI models.
Huaishu Peng and Ge Gao from UMD will work with Malte Jung from Cornell to increase trust-building in embodied AI systems, which bridge the gap between computers and human physical senses. Specifically, the researchers will explore embodied AI systems in the form of miniaturized on-body or desktop robotic systems that can enable the exchange of nonverbal cues between blind and sighted individuals, an essential component of efficient collaboration. The researchers will also examine multiple factors—both physical and mental—in order to gain a deeper understanding of both groups’ values related to teamwork facilitated by embodied AI.
Marine Carpuat and Ge Gao from UMD will explore “mental models”—how humans perceive things—for language translation systems used by millions of people daily. They will focus on how individuals, depending on their language fluency and familiarity with the technology, make sense of their “error boundary”—that is, deciding whether an AI-generated translation is correct or incorrect. The team will also develop innovative techniques to teach users how to improve their mental models as they interact with machine translation systems.
Hal Daumé III, Furong Huang and Zubin Jelveh from UMD and Donald Braman from GW will propose new philosophies grounded in law to conceptualize, evaluate and achieve “effort-aware fairness,” which involves algorithms for determining whether an individual or a group of individuals is discriminated against in terms of equality of effort. The researchers will develop new metrics, evaluate fairness of datasets, and design novel algorithms that enable AI auditors to uncover and potentially correct unfair decisions.
Lorien Abroms and David Broniatowski from GW will recruit smokers to study the reliability of using generative chatbots, such as ChatGPT, as the basis for a digital smoking cessation program. Additional work will examine the acceptability by smokers and their perceptions of trust in using this rapidly evolving technology for help to quit smoking. The researchers hope their study will directly inform future digital interventions for smoking cessation and/or modifying other health behaviors.
Adam Aviv from GW and Michelle Mazurek from UMD will examine bias, unfairness and untruths such as sexism, racism and other forms of misrepresentation that come out of certain AI and machine learning systems. Though some systems have public warnings of potential biases, the researchers want to explore how users understand these warnings, if they recognize how biases may manifest themselves in the AI-generated responses, and how users attempt to expose, mitigate and manage potentially biased responses.
Susan Ariel Aaronson and David Broniatowski from GW plan to create a prototype of a searchable, easy-to-use website to enable policymakers to better utilize academic research related to trustworthy and participatory AI. The team will analyze research publications by TRAILS-affiliated researchers to ascertain which ones may have policy implications. Then, each relevant publication will be summarized and categorized by research questions, issues, keywords, and relevant policymaking uses. The resulting database prototype will enable the researchers to test the utility of this resource for policymakers over time.
Yes, things are moving quickly where AI is concerned. There’s text-to-image being investigated by Soheil Feizi and Robert Brauneis and, since the funding announcement in early January 2024, text-to-video has been announced (Open AI’s Sora was previewed February 15, 2024). I wonder if that will be added to the project.
One more comment, Huaishu Peng’s, Ge Gao’s, and Malte Jung’s project for “… trust-building in embodied AI systems …” brings to mind Elon Musk’s stated goal of using brain implants for“human/AI symbiosis.” (I have more about that in an upcoming post.) Hopefully, Susan Ariel Aaronson’s and David Broniatowski’s proposed website for policymakers will be able to keep up with what’s happening in the field of AI, including research on the impact of private investments primarily designed for generating profits.
I haven’t seen this much interest in the ethics and social impacts of emerging technologies in years. It seems that the latest AI (artificial intelligence) panic has stimulated interest not only in regulation but ethics too.
NSF and philanthropic partners announce $16 million in funding to prioritize ethical and social considerations in emerging technologies
ReDDDoT is a collaboration with five philanthropic partners and crosses all disciplines of science and engineering_
The U.S. National Science Foundation today launched a new $16 million program in collaboration with five philanthropic partners that seeks to ensure ethical, legal, community and societal considerations are embedded in the lifecycle of technology’s creation and use. The Responsible Design, Development and Deployment of Technologies (ReDDDoT) program aims to help create technologies that promote the public’s wellbeing and mitigate potential harms.
“The design, development and deployment of technologies have broad impacts on society,” said NSF Director Sethuraman Panchanathan. “As discoveries and innovations are translated to practice, it is essential that we engage and enable diverse communities to participate in this work. NSF and its philanthropic partners share a strong commitment to creating a comprehensive approach for co-design through soliciting community input, incorporating community values and engaging a broad array of academic and professional voices across the lifecycle of technology creation and use.”
The ReDDDoT program invites proposals from multidisciplinary, multi-sector teams that examine and demonstrate the principles, methodologies and impacts associated with responsible design, development and deployment of technologies, especially those specified in the “CHIPS and Science Act of 2022.” In addition to NSF, the program is funded and supported by the Ford Foundation, the Patrick J. McGovern Foundation, Pivotal Ventures, Siegel Family Endowment and the Eric and Wendy Schmidt Fund for Strategic Innovation.
“In recognition of the role responsible technologists can play to advance human progress, and the danger unaccountable technology poses to social justice, the ReDDDoT program serves as both a collaboration and a covenant between philanthropy and government to center public interest technology into the future of progress,” said Darren Walker, president of the Ford Foundation. “This $16 million initiative will cultivate expertise from public interest technologists across sectors who are rooted in community and grounded by the belief that innovation, equity and ethics must equally be the catalysts for technological progress.”
The broad goals of ReDDDoT include:
*Stimulating activity and filling gaps in research, innovation and capacity building in the responsible design, development, and deployment of technologies. * Creating broad and inclusive communities of interest that bring together key stakeholders to better inform practices for the design, development, and deployment of technologies. * Educating and training the science, technology, engineering, and mathematics workforce on approaches to responsible design, development, and deployment of technologies. * Accelerating pathways to societal and economic benefits while developing strategies to avoid or mitigate societal and economic harms. * Empowering communities, including economically disadvantaged and marginalized populations, to participate in all stages of technology development, including the earliest stages of ideation and design.
Phase 1 of the program solicits proposals for Workshops, Planning Grants, or the creation of Translational Research Coordination Networks, while Phase 2 solicits full project proposals. The initial areas of focus for 2024 include artificial intelligence, biotechnology or natural and anthropogenic disaster prevention or mitigation. Future iterations of the program may consider other key technology focus areas enumerated in the CHIPS and Science Act.
“The core belief at the heart of ReDDDoT – that technology should be shaped by ethical, legal, and societal considerations as well as community values – also drives the work of the Patrick J. McGovern Foundation to build a human-centered digital future for all. We’re pleased to support this partnership, committed to advancing the development of AI, biotechnology, and climate technologies that advance equity, sustainability, and justice.” – Vilas Dhar, President, Patrick J. McGovern Foundation
“From generative AI to quantum computing, the pace of technology development is only accelerating. Too often, technological advances are not accompanied by discussion and design that considers negative impacts or unrealized potential. We’re excited to support ReDDDoT as an opportunity to uplift new and often forgotten perspectives that critically examine technology’s impact on civic life, and advance Siegel Family Endowment’s vision of technological change that includes and improves the lives of all people.” – Katy Knight, President and Executive Director of Siegel Family Endowment
The University of Maryland has been chosen to lead a multi-institutional effort supported by the National Science Foundation (NSF) that will develop new artificial intelligence (AI) technologies designed to promote trust and mitigate risks, while simultaneously empowering and educating the public.
The NSF Institute for Trustworthy AI in Law & Society (TRAILS) announced on May 4, 2023, unites specialists in AI and machine learning with social scientists, legal scholars, educators and public policy experts. The multidisciplinary team will work with impacted communities, private industry and the federal government to determine what trust in AI looks like, how to develop technical solutions for AI that can be trusted, and which policy models best create and sustain trust.
Funded by a $20 million award from NSF, the new institute is expected to transform the practice of AI from one driven primarily by technological innovation to one that is driven by ethics, human rights, and input and feedback from communities whose voices have previously been marginalized.
“As artificial intelligence continues to grow exponentially, we must embrace its potential for helping to solve the grand challenges of our time, as well as ensure that it is used both ethically and responsibly,” said UMD President Darryll J. Pines. “With strong federal support, this new institute will lead in defining the science and innovation needed to harness the power of AI for the benefit of the public good and all humankind.”
In addition to UMD, TRAILS will include faculty members from George Washington University (GW) and Morgan State University, with more support coming from Cornell University, the National Institute of Standards and Technology (NIST), and private sector organizations like the DataedX Group, Arthur AI, Checkstep, FinRegLab and Techstars.
At the heart of establishing the new institute is the consensus that AI is currently at a crossroads. AI-infused systems have great potential to enhance human capacity, increase productivity, catalyze innovation, and mitigate complex problems, but today’s systems are developed and deployed in a process that is opaque and insular to the public, and therefore, often untrustworthy to those affected by the technology.
“We’ve structured our research goals to educate, learn from, recruit, retain and support communities whose voices are often not recognized in mainstream AI development,” said Hal Daumé III, a UMD professor of computer science who is lead principal investigator of the NSF award and will serve as the director of TRAILS.
Inappropriate trust in AI can result in many negative outcomes, Daumé said. People often “overtrust” AI systems to do things they’re fundamentally incapable of. This can lead to people or organizations giving up their own power to systems that are not acting in their best interest. At the same time, people can also “undertrust” AI systems, leading them to avoid using systems that could ultimately help them.
Given these conditions—and the fact that AI is increasingly being deployed to mediate society’s online communications, determine health care options, and offer guidelines in the criminal justice system—it has become urgent to ensure that people’s trust in AI systems matches those same systems’ level of trustworthiness.
TRAILS has identified four key research thrusts to promote the development of AI systems that can earn the public’s trust through broader participation in the AI ecosystem.
The first, known as participatory AI, advocates involving human stakeholders in the development, deployment and use of these systems. It aims to create technology in a way that aligns with the values and interests of diverse groups of people, rather than being controlled by a few experts or solely driven by profit.
Leading the efforts in participatory AI is Katie Shilton, an associate professor in UMD’s College of Information Studies who specializes in ethics and sociotechnical systems. Tom Goldstein, a UMD associate professor of computer science, will lead the institute’s second research thrust, developing advanced machine learning algorithms that reflect the values and interests of the relevant stakeholders.
Daumé, Shilton and Goldstein all have appointments in the University of Maryland Institute for Advanced Computer Studies, which is providing administrative and technical support for TRAILS.
David Broniatowski, an associate professor of engineering management and systems engineering at GW, will lead the institute’s third research thrust of evaluating how people make sense of the AI systems that are developed, and the degree to which their levels of reliability, fairness, transparency and accountability will lead to appropriate levels of trust. Susan Ariel Aaronson, a research professor of international affairs at GW, will use her expertise in data-driven change and international data governance to lead the institute’s fourth thrust of participatory governance and trust.
Virginia Byrne, an assistant professor of higher education and student affairs at Morgan State, will lead community-driven projects related to the interplay between AI and education. According to Daumé, the TRAILS team will rely heavily on Morgan State’s leadership—as Maryland’s preeminent public urban research university—in conducting rigorous, participatory community-based research with broad societal impacts.
Additional academic support will come from Valerie Reyna, a professor of human development at Cornell, who will use her expertise in human judgment and cognition to advance efforts focused on how people interpret their use of AI.
Federal officials at NIST will collaborate with TRAILS in the development of meaningful measures, benchmarks, test beds and certification methods—particularly as they apply to important topics essential to trust and trustworthiness such as safety, fairness, privacy, transparency, explainability, accountability, accuracy and reliability.
“The ability to measure AI system trustworthiness and its impacts on individuals, communities and society is limited. TRAILS can help advance our understanding of the foundations of trustworthy AI, ethical and societal considerations of AI, and how to build systems that are trusted by the people who use and are affected by them,” said Under Secretary of Commerce for Standards and Technology and NIST Director Laurie E. Locascio.
Today’s announcement [May 4, 2023] is the latest in a series of federal grants establishing a cohort of National Artificial Intelligence Research Institutes. This recent investment in seven new AI institutes, totaling $140 million, follows two previous rounds of awards.
“Maryland is at the forefront of our nation’s scientific innovation thanks to our talented workforce, top-tier universities, and federal partners,” said U.S. Sen. Chris Van Hollen (D-Md.). “This National Science Foundation award for the University of Maryland—in coordination with other Maryland-based research institutions including Morgan State University and NIST—will promote ethical and responsible AI development, with the goal of helping us harness the benefits of this powerful emerging technology while limiting the potential risks it poses. This investment entrusts Maryland with a critical priority for our shared future, recognizing the unparalleled ingenuity and world-class reputation of our institutions.”
The NSF, in collaboration with government agencies and private sector leaders, has now invested close to half a billion dollars in the AI institutes ecosystem—an investment that expands a collaborative AI research network into almost every U.S. state.
“The National AI Research Institutes are a critical component of our nation’s AI innovation, infrastructure, technology, education and partnerships ecosystem,” said NSF Director Sethuraman Panchanathan. “[They] are driving discoveries that will ensure our country is at the forefront of the global AI revolution.”
As noted in the UMD news release, this funding is part of a ‘bundle’, here’s more from the May 4, 2023 US NSF news release announcing the full $ 140 million funding program, Note: Links have been removed,
The U.S. National Science Foundation, in collaboration with other federal agencies, higher education institutions and other stakeholders, today announced a $140 million investment to establish seven new National Artificial Intelligence Research Institutes. The announcement is part of a broader effort across the federal government to advance a cohesive approach to AI-related opportunities and risks.
The new AI Institutes will advance foundational AI research that promotes ethical and trustworthy AI systems and technologies, develop novel approaches to cybersecurity, contribute to innovative solutions to climate change, expand the understanding of the brain, and leverage AI capabilities to enhance education and public health. The institutes will support the development of a diverse AI workforce in the U.S. and help address the risks and potential harms posed by AI. This investment means NSF and its funding partners have now invested close to half a billion dollars in the AI Institutes research network, which reaches almost every U.S. state.
“The National AI Research Institutes are a critical component of our nation’s AI innovation, infrastructure, technology, education and partnerships ecosystem,” said NSF Director Sethuraman Panchanathan. “These institutes are driving discoveries that will ensure our country is at the forefront of the global AI revolution.”
“These strategic federal investments will advance American AI infrastructure and innovation, so that AI can help tackle some of the biggest challenges we face, from climate change to health. Importantly, the growing network of National AI Research Institutes will promote responsible innovation that safeguards people’s safety and rights,” said White House Office of Science and Technology Policy Director Arati Prabhakar.
The new AI Institutes are interdisciplinary collaborations among top AI researchers and are supported by co-funding from the U.S. Department of Commerce’s National Institutes of Standards and Technology (NIST); U.S. Department of Homeland Security’s Science and Technology Directorate (DHS S&T); U.S. Department of Agriculture’s National Institute of Food and Agriculture (USDA-NIFA); U.S. Department of Education’s Institute of Education Sciences (ED-IES); U.S. Department of Defense’s Office of the Undersecretary of Defense for Research and Engineering (DoD OUSD R&E); and IBM Corporation (IBM).
“Foundational research in AI and machine learning has never been more critical to the understanding, creation and deployment of AI-powered systems that deliver transformative and trustworthy solutions across our society,” said NSF Assistant Director for Computer and Information Science and Engineering Margaret Martonosi. “These recent awards, as well as our AI Institutes ecosystem as a whole, represent our active efforts in addressing national economic and societal priorities that hinge on our nation’s AI capability and leadership.”
The new AI Institutes focus on six research themes:
Trustworthy AI
NSF Institute for Trustworthy AI in Law & Society (TRAILS)
Led by the University of Maryland, TRAILS aims to transform the practice of AI from one driven primarily by technological innovation to one driven with attention to ethics, human rights and support for communities whose voices have been marginalized into mainstream AI. TRAILS will be the first institute of its kind to integrate participatory design, technology, and governance of AI systems and technologies and will focus on investigating what trust in AI looks like, whether current technical solutions for AI can be trusted, and which policy models can effectively sustain AI trustworthiness. TRAILS is funded by a partnership between NSF and NIST.
Intelligent Agents for Next-Generation Cybersecurity
AI Institute for Agent-based Cyber Threat Intelligence and Operation (ACTION)
Led by the University of California, Santa Barbara, this institute will develop novel approaches that leverage AI to anticipate and take corrective actions against cyberthreats that target the security and privacy of computer networks and their users. The team of researchers will work with experts in security operations to develop a revolutionary approach to cybersecurity, in which AI-enabled intelligent security agents cooperate with humans across the cyberdefense life cycle to jointly improve the resilience of security of computer systems over time. ACTION is funded by a partnership between NSF, DHS S&T, and IBM.
Climate Smart Agriculture and Forestry
AI Institute for Climate-Land Interactions, Mitigation, Adaptation, Tradeoffs and Economy (AI-CLIMATE)
Led by the University of Minnesota Twin Cities, this institute aims to advance foundational AI by incorporating knowledge from agriculture and forestry sciences and leveraging these unique, new AI methods to curb climate effects while lifting rural economies. By creating a new scientific discipline and innovation ecosystem intersecting AI and climate-smart agriculture and forestry, our researchers and practitioners will discover and invent compelling AI-powered knowledge and solutions. Examples include AI-enhanced estimation methods of greenhouse gases and specialized field-to-market decision support tools. A key goal is to lower the cost of and improve accounting for carbon in farms and forests to empower carbon markets and inform decision making. The institute will also expand and diversify rural and urban AI workforces. AI-CLIMATE is funded by USDA-NIFA.
Neural and Cognitive Foundations of Artificial Intelligence
AI Institute for Artificial and Natural Intelligence (ARNI)
Led by Columbia University, this institute will draw together top researchers across the country to focus on a national priority: connecting the major progress made in AI systems to the revolution in our understanding of the brain. ARNI will meet the urgent need for new paradigms of interdisciplinary research between neuroscience, cognitive science and AI. This will accelerate progress in all three fields and broaden the transformative impact on society in the next decade. ARNI is funded by a partnership between NSF and DoD OUSD R&E.
AI for Decision Making
AI Institute for Societal Decision Making (AI-SDM)
Led by Carnegie Mellon University, this institute seeks to create human-centric AI for decision making to bolster effective response in uncertain, dynamic and resource-constrained scenarios like disaster management and public health. By bringing together an interdisciplinary team of AI and social science researchers, AI-SDM will enable emergency managers, public health officials, first responders, community workers and the public to make decisions that are data driven, robust, agile, resource efficient and trustworthy. The vision of the institute will be realized via development of AI theory and methods, translational research, training and outreach, enabled by partnerships with diverse universities, government organizations, corporate partners, community colleges, public libraries and high schools.
AI-Augmented Learning to Expand Education Opportunities and Improve Outcomes
AI Institute for Inclusive Intelligent Technologies for Education (INVITE)
Led by the University of Illinois Urbana-Champaign, this institute seeks to fundamentally reframe how educational technologies interact with learners by developing AI tools and approaches to support three crucial noncognitive skills known to underlie effective learning: persistence, academic resilience and collaboration. The institute’s use-inspired research will focus on how children communicate STEM content, how they learn to persist through challenging work, and how teachers support and promote noncognitive skill development. The resultant AI-based tools will be integrated into classrooms to empower teachers to support learners in more developmentally appropriate ways.
AI Institute for Exceptional Education (AI4ExceptionalEd)
Led by the University at Buffalo, this institute will work toward universal speech and language screening for children. The framework, the AI screener, will analyze video and audio streams of children during classroom interactions and assess the need for evidence-based interventions tailored to individual needs of students. The institute will serve children in need of ability-based speech and language services, advance foundational AI technologies and enhance understanding of childhood speech and language development. The AI Institute for Exceptional Education was previously announced in January 2023. The INVITE and AI4ExceptionalEd institutes are funded by a partnership between NSF and ED-IES.
Statements from NSF’s Federal Government Funding Partners
“Increasing AI system trustworthiness while reducing its risks will be key to unleashing AI’s potential benefits and ensuring our shared societal values,” said Under Secretary of Commerce for Standards and Technology and NIST Director Laurie E. Locascio. “Today, the ability to measure AI system trustworthiness and its impacts on individuals, communities and society is limited. TRAILS can help advance our understanding of the foundations of trustworthy AI, ethical and societal considerations of AI, and how to build systems that are trusted by the people who use and are affected by them.”
“The ACTION Institute will help us better assess the opportunities and risks of rapidly evolving AI technology and its impact on DHS missions,” said Dimitri Kusnezov, DHS under secretary for science and technology. “This group of researchers and their ambition to push the limits of fundamental AI and apply new insights represents a significant investment in cybersecurity defense. These partnerships allow us to collectively remain on the forefront of leading-edge research for AI technologies.”
“In the tradition of USDA National Institute of Food and Agriculture investments, this new institute leverages the scientific power of U.S. land-grant universities informed by close partnership with farmers, producers, educators and innovators to address the grand challenge of rising greenhouse gas concentrations and associated climate change,” said Acting NIFA Director Dionne Toombs. “This innovative center will address the urgent need to counter climate-related threats, lower greenhouse gas emissions, grow the American workforce and increase new rural opportunities.”
“The leading-edge in AI research inevitably draws from our, so far, limited understanding of human cognition. This AI Institute seeks to unify the fields of AI and neuroscience to bring advanced designs and approaches to more capable and trustworthy AI, while also providing better understanding of the human brain,” said Bindu Nair, director, Basic Research Office, Office of the Undersecretary of Defense for Research and Engineering. “We are proud to partner with NSF in this critical field of research, as continued advancement in these areas holds the potential for further and significant benefits to national security, the economy and improvements in quality of life.”
“We are excited to partner with NSF on these two AI institutes,” said IES Director Mark Schneider. “We hope that they will provide valuable insights into how to tap modern technologies to improve the education sciences — but more importantly we hope that they will lead to better student outcomes and identify ways to free up the time of teachers to deliver more informed individualized instruction for the students they care so much about.”
Two things I noticed, (1) No mention of including ethics training or concepts in science and technology education and (2) No mention of integrating ethics and social issues into any of the AI Institutes. So, it seems that ‘Responsible Design, Development and Deployment of Technologies (ReDDDoT)’ occupies its own fiefdom.
Some sobering thoughts
Things can go terribly wrong with new technology as seen in the British television hit series, Mr. Bates vs. The Post Office (based on a true story) , from a January 9, 2024 posting by Ani Blundel for tellyvisions.org,
…
… what is this show that’s caused the entire country to rise up as one to defend the rights of the lowly sub-postal worker? Known as the “British Post Office scandal,” the incidents first began in 1999 when the U.K. postal system began to switch to digital systems, using the Horizon Accounting system to track the monies brought in. However, the IT system was faulty from the start, and rather than blame the technology, the British government accused, arrested, persecuted, and convicted over 700 postal workers of fraud and theft. This continued through 2015 when the glitch was finally recognized, and in 2019, the convictions were ruled to be a miscarriage of justice.
…
Here’s the series synopsis:
The drama tells the story of one of the greatest miscarriages of justice in British legal history. Hundreds of innocent sub-postmasters and postmistresses were wrongly accused of theft, fraud, and false accounting due to a defective IT system. Many of the wronged workers were prosecuted, some of whom were imprisoned for crimes they never committed, and their lives were irreparably ruined by the scandal. Following the landmark Court of Appeal decision to overturn their criminal convictions, dozens of former sub-postmasters and postmistresses have been exonerated on all counts as they battled to finally clear their names. They fought for over ten years, finally proving their innocence and sealing a resounding victory, but all involved believe the fight is not over yet, not by a long way.
Here’s a video trailer for ‘Mr. Bates vs. The Post Office,
The outcry from the general public against the government’s bureaucratic mismanagement and abuse of employees has been loud and sustained enough that Prime Minister Rishi Sunak had to come out with a statement condemning what happened back during the 2009 incident. Further, the current Justice Secretary, Alex Chalk, is now trying to figure out the fastest way to exonerate the hundreds of sub-post managers and sub-postmistresses who were wrongfully convicted back then and if there are steps to be taken to punish the post office a decade later.
…
It’s a horrifying story and the worst I’ve seen so far but, sadly, it’s not the only one of its kind.
Too often people’s concerns and worries about new technology are dismissed or trivialized. Somehow, all the work done to establish ethical standards and develop trust seems to be used as a kind of sop to the concerns rather than being integrated into the implementation of life-altering technologies.
This is a different approach to neuromorphic (brainlike) computing being described in an August 28, 2023 news item on phys.org, Note: A link has been removed,
The word “fractals” might inspire images of psychedelic colors spiraling into infinity in a computer animation. An invisible, but powerful and useful, version of this phenomenon exists in the realm of dynamic magnetic fractal networks.
Dustin Gilbert, assistant professor in the Department of Materials Science and Engineering [University of Tennessee, US], and colleagues have published new findings in the behavior of these networks—observations that could advance neuromorphic computing capabilities.
Their research is detailed in their article “Skyrmion-Excited Spin-Wave Fractal Networks,” cover story for the August 17, 2023, issue of Advanced Materials.
“Most magnetic materials—like in refrigerator magnets—are just comprised of domains where the magnetic spins all orient parallel,” said Gilbert. “Almost 15 years ago, a German research group discovered these special magnets where the spins make loops—like a nanoscale magnetic lasso. These are called skyrmions.”
Named for legendary particle physicist Tony Skyrme, a skyrmion’s magnetic swirl gives it a non-trivial topology. As a result of this topology, the skyrmion has particle-like properties—they are hard to create or destroy, they can move and even bounce off of each other. The skyrmion also has dynamic modes—they can wiggle, shake, stretch, whirl, and breath[e].
As the skyrmions “jump and jive,” they are creating magnetic spin waves with a very narrow wavelength. The interactions of these waves form an unexpected fractal structure.
“Just like a person dancing in a pool of water, they generate waves which ripple outward,” said Gilbert. “Many people dancing make many waves, which normally would seem like a turbulent, chaotic sea. We measured these waves and showed that they have a well-defined structure and collectively form a fractal which changes trillions of times per second.”
Fractals are important and interesting because they are inherently tied to a “chaos effect”—small changes in initial conditions lead to big changes in the fractal network.
“Where we want to go with this is that if you have a skyrmion lattice and you illuminate it with spin waves, the way the waves make its way through this fractal-generating structure is going to depend very intimately on its construction,” said Gilbert. “So, if you could write individual skyrmions, it can effectively process incoming spin waves into something on the backside—and it’s programmable. It’s a neuromorphic architecture.”
The Advanced Materials cover illustration [image at top of this posting] depicts a visual representation of this process, with the skyrmions floating on top of a turbulent blue sea illustrative of the chaotic structure generated by the spin wave fractal.
“Those waves interfere just like if you throw a handful of pebbles into a pond,” said Gilbert. “You get a choppy, turbulent mess. But it’s not just any simple mess, it’s actually a fractal. We have an experiment now showing that the spin waves generated by skyrmions aren’t just a mess of waves, they have inherent structure of their very own. By, essentially, controlling those stones that we ‘throw in,’ you get very different patterns, and that’s what we’re driving towards.”
The discovery was made in part by neutron scattering experiments at the Oak Ridge National Laboratory (ORNL) High Flux Isotope Reactor and at the National Institute of Standards and Technology (NIST) Center for Neutron Research. Neutrons are magnetic and pass through materials easily, making them ideal probes for studying materials with complex magnetic behavior such as skyrmions and other quantum phenomena.
Gilbert’s co-authors for the new article are Nan Tang, Namila Liyanage, and Liz Quigley, students in his research group; Alex Grutter and Julie Borchers from National Institute of Standards and Technology (NIST), Lisa DeBeer-Schmidt and Mike Fitzsimmons from Oak Ridge National Laboratory; and Eric Fullerton, Sheena Patel, and Sergio Montoya from the University of California, San Diego.
The team’s next step is to build a working model using the skyrmion behavior.
“If we can develop thinking computers, that, of course, is extraordinarily important,” said Gilbert. “So, we will propose to make a miniaturized, spin wave neuromorphic architecture.” He also hopes that the ripples from this UT Knoxville discovery inspire researchers to explore uses for a spiraling range of future applications.
Here’s a link to and a citation for the paper,
Skyrmion-Excited Spin-Wave Fractal Networks by Nan Tang, W. L. N. C. Liyanage, Sergio A. Montoya, Sheena Patel, Lizabeth J. Quigley, Alexander J. Grutter, Michael R. Fitzsimmons, Sunil Sinha, Julie A. Borchers, Eric E. Fullerton, Lisa DeBeer-Schmitt, Dustin A. Gilbert. Advanced Materials Volume 35, Issue 33 August 17, 2023 2300416 DOI: https://doi.org/10.1002/adma.202300416 First published: 04 May 2023
A September 1, 2021 news item on ScienceDaily announces a new type of memristor from Texas A&M University (Texas A&M or TAMU) and the National University of Singapore (NUS)
In a discovery published in the journal Nature, an international team of researchers has described a novel molecular device with exceptional computing prowess.
Reminiscent of the plasticity of connections in the human brain, the device can be reconfigured on the fly for different computational tasks by simply changing applied voltages. Furthermore, like nerve cells can store memories, the same device can also retain information for future retrieval and processing.
“The brain has the remarkable ability to change its wiring around by making and breaking connections between nerve cells. Achieving something comparable in a physical system has been extremely challenging,” said Dr. R. Stanley Williams [emphasis mine], professor in the Department of Electrical and Computer Engineering at Texas A&M University. “We have now created a molecular device with dramatic reconfigurability, which is achieved not by changing physical connections like in the brain, but by reprogramming its logic.”
Dr. T. Venkatesan, director of the Center for Quantum Research and Technology (CQRT) at the University of Oklahoma, Scientific Affiliate at National Institute of Standards and Technology, Gaithersburg, and adjunct professor of electrical and computer engineering at the National University of Singapore, added that their molecular device might in the future help design next-generation processing chips with enhanced computational power and speed, but consuming significantly reduced energy.
Whether it is the familiar laptop or a sophisticated supercomputer, digital technologies face a common nemesis, the von Neumann bottleneck. This delay in computational processing is a consequence of current computer architectures, wherein the memory, containing data and programs, is physically separated from the processor. As a result, computers spend a significant amount of time shuttling information between the two systems, causing the bottleneck. Also, despite extremely fast processor speeds, these units can be idling for extended amounts of time during periods of information exchange.
As an alternative to conventional electronic parts used for designing memory units and processors, devices called memristors offer a way to circumvent the von Neumann bottleneck. Memristors, such as those made of niobium dioxide and vanadium dioxide, transition from being an insulator to a conductor at a set temperature. This property gives these types of memristors the ability to perform computations and store data.
However, despite their many advantages, these metal oxide memristors are made of rare-earth elements and can operate only in restrictive temperature regimes. Hence, there has been an ongoing search for promising organic molecules that can perform a comparable memristive function, said Williams.
Dr. Sreebrata Goswami, a professor at the Indian Association for the Cultivation of Science, designed the material used in this work. The compound has a central metal atom (iron) bound to three phenyl azo pyridine organic molecules called ligands.
“This behaves like an electron sponge that can absorb as many as six electrons reversibly, resulting in seven different redox states,” said Sreebrata. “The interconnectivity between these states is the key behind the reconfigurability shown in this work.”
Dr. Sreetosh Goswami, a researcher at the National University of Singapore, devised this project by creating a tiny electrical circuit consisting of a 40-nanometer layer of molecular film sandwiched between a layer of gold on top and gold-infused nanodisc and indium tin oxide at the bottom.
On applying a negative voltage on the device, Sreetosh witnessed a current-voltage profile that was nothing like anyone had seen before. Unlike metal-oxide memristors that can switch from metal to insulator at only one fixed voltage, the organic molecular devices could switch back and forth from insulator to conductor at several discrete sequential voltages.
“So, if you think of the device as an on-off switch, as we were sweeping the voltage more negative, the device first switched from on to off, then off to on, then on to off and then back to on. I’ll say that we were just blown out of our seat,” said Venkatesan. “We had to convince ourselves that what we were seeing was real.”
Sreetosh and Sreebrata investigated the molecular mechanisms underlying the curious switching behavior using an imaging technique called Raman spectroscopy. In particular, they looked for spectral signatures in the vibrational motion of the organic molecule that could explain the multiple transitions. Their investigation revealed that sweeping the voltage negative triggered the ligands on the molecule to undergo a series of reduction, or electron-gaining, events that caused the molecule to transition between off state and on states.
Next, to describe the extremely complex current-voltage profile of the molecular device mathematically, Williams deviated from the conventional approach of basic physics-based equations. Instead, he described the behavior of the molecules using a decision tree algorithm with “if-then-else” statements, a commonplace line of code in several computer programs, particularly digital games.
“Video games have a structure where you have a character that does something, and then something occurs as a result. And so, if you write that out in a computer algorithm, they are if-then-else statements,” said Williams. “Here, the molecule is switching from on to off as a consequence of applied voltage, and that’s when I had the eureka moment to use decision trees to describe these devices, and it worked very well.”
But the researchers went a step further to exploit these molecular devices to run programs for different real-world computational tasks. Sreetosh showed experimentally that their devices could perform fairly complex computations in a single time step and then be reprogrammed to perform another task in the next instant.
“It was quite extraordinary; our device was doing something like what the brain does, but in a very different way,” said Sreetosh. “When you’re learning something new or when you’re deciding, the brain can actually reconfigure and change physical wiring around. Similarly, we can logically reprogram or reconfigure our devices by giving them a different voltage pulse then they’ve seen before.”
Venkatesan noted that it would take thousands of transistors to perform the same computational functions as one of their molecular devices with its different decision trees. Hence, he said their technology might first be used in handheld devices, like cell phones and sensors, and other applications where power is limited.
Other contributors to the research include Dr. Abhijeet Patra and Dr. Ariando from the National University of Singapore; Dr. Rajib Pramanick and Dr. Santi Prasad Rath from the Indian Association for the Cultivation of Science; Dr. Martin Foltin from Hewlett Packard Enterprise, Colorado; and Dr. Damien Thompson from the University of Limerick, Ireland.
Venkatesan said that this research is indicative of the future discoveries from this collaborative team, which will include the center of nanoscience and engineering at the Indian Institute of Science and the Microsystems and Nanotechnology Division at the NIST.
I’ve highlighted R. Stanley Williams because he and his team at HP [Hewlett Packard] Labs helped to kick off current memristor research in 2008 with the publication of two papers as per my April 5, 2010 posting,
In 2008, two memristor papers were published in Nature and Nature Nanotechnology, respectively. In the first (Nature, May 2008 [article still behind a paywall], a team at HP Labs claimed they had proved the existence of memristors (a fourth member of electrical engineering’s ‘Holy Trinity of the capacitor, resistor, and inductor’). In the second paper (Nature Nanotechnology, July 2008 [article still behind a paywall]) the team reported that they had achieved engineering control.
…
The novel memory device is based on a molecular system that can transition between on and off states at several discrete sequential voltages Courtesy: National University of Singapore
Many electronic devices today are dependent on semiconductor logic circuits based on switches hard-wired to perform predefined logic functions. Physicists from the National University of Singapore (NUS), together with an international team of researchers, have developed a novel molecular memristor, or an electronic memory device, that has exceptional memory reconfigurability.
Unlike hard-wired standard circuits, the molecular device can be reconfigured using voltage to embed different computational tasks. The energy-efficient new technology, which is capable of enhanced computational power and speed, can potentially be used in edge computing, as well as handheld devices and applications with limited power resource.
“This work is a significant breakthrough in our quest to design low-energy computing. The idea of using multiple switching in a single element draws inspiration from how the brain works and fundamentally reimagines the design strategy of a logic circuit,” said Associate Professor Ariando from the NUS Department of Physics who led the research.
The research was first published in the journal Nature on 1 September 2021, and carried out in collaboration with the Indian Association for the Cultivation of Science, Hewlett Packard Enterprise, the University of Limerick, the University of Oklahoma, and Texas A&M University.
Brain-inspired technology
“This new discovery can contribute to developments in edge computing as a sophisticated in-memory computing approach to overcome the von Neumann bottleneck, a delay in computational processing seen in many digital technologies due to the physical separation of memory storage from a device’s processor,” said Assoc Prof Ariando. The new molecular device also has the potential to contribute to designing next generation processing chips with enhanced computational power and speed.
“Similar to the flexibility and adaptability of connections in the human brain, our memory device can be reconfigured on the fly for different computational tasks by simply changing applied voltages. Furthermore, like how nerve cells can store memories, the same device can also retain information for future retrieval and processing,” said first author Dr Sreetosh Goswami, Research Fellow from the Department of Physics at NUS.
Research team member Dr Sreebrata Goswami, who was a Senior Research Scientist at NUS and previously Professor at the Indian Association for the Cultivation of Science, conceptualised and designed a molecular system belonging to the chemical family of phenyl azo pyridines that have a central metal atom bound to organic molecules called ligands. “These molecules are like electron sponges that can offer as many as six electron transfers resulting in five different molecular states. The interconnectivity between these states is the key behind the device’s reconfigurability,” explained Dr Sreebrata Goswami.
Dr Sreetosh Goswami created a tiny electrical circuit consisting a 40-nanometer layer of molecular film sandwiched between a top layer of gold, and a bottom layer of gold-infused nanodisc and indium tin oxide. He observed an unprecedented current-voltage profile upon applying a negative voltage to the device. Unlike conventional metal-oxide memristors that are switched on and off at only one fixed voltage, these organic molecular devices could switch between on-off states at several discrete sequential voltages.
Using an imaging technique called Raman spectroscopy, spectral signatures in the vibrational motion of the organic molecule were observed to explain the multiple transitions. Dr Sreebrata Goswami explained, “Sweeping the negative voltage triggered the ligands on the molecule to undergo a series of reduction, or electron-gaining which caused the molecule to transition between off and on states.”
The researchers described the behavior of the molecules using a decision tree algorithm with “if-then-else” statements, which is used in the coding of several computer programs, particularly digital games, as compared to the conventional approach of using basic physics-based equations.
New possibilities for energy-efficient devices
Building on their research, the team used the molecular memory devices to run programs for different real-world computational tasks. As a proof of concept, the team demonstrated that their technology could perform complex computations in a single step, and could be reprogrammed to perform another task in the next instant. An individual molecular memory device could perform the same computational functions as thousands of transistors, making the technology a more powerful and energy-efficient memory option.
“The technology might first be used in handheld devices, like cell phones and sensors, and other applications where power is limited,” added Assoc Prof Ariando.
The team in the midst of building new electronic devices incorporating their innovation, and working with collaborators to conduct simulation and benchmarking relating to existing technologies.
Other contributors to the research paper include Abhijeet Patra and Santi Prasad Rath from NUS, Rajib Pramanick from the Indian Association for the Cultivation of Science, Martin Foltin from Hewlett Packard Enterprise, Damien Thompson from the University of Limerick, T. Venkatesan from the University of Oklahoma, and R. Stanley Williams from Texas A&M University.
Here’s a link to and a citation for the paper,
Decision trees within a molecular memristor by Sreetosh Goswami, Rajib Pramanick, Abhijeet Patra, Santi Prasad Rath, Martin Foltin, A. Ariando, Damien Thompson, T. Venkatesan, Sreebrata Goswami & R. Stanley Williams. Nature volume 597, pages 51–56 (2021) DOI: https://doi.org/10.1038/s41586-021-03748-0 Published 01 September 2021 Issue Date 02 September 2021
A September 20, 2021 news item on phys.org announces research investigating the heating of electronics at the nanoscale,
A team of physicists at CU Boulder [University of Colorado at Boulder] has solved the mystery behind a perplexing phenomenon in the nano realm: why some ultra-small heat sources cool down faster if you pack them closer together. The findings, published today in the journal Proceedings of the National Academy of Sciences (PNAS), could one day help the tech industry design faster electronic devices that overheat less.
“Often, heat is a challenging consideration in designing electronics. You build a device then discover that it’s heating up faster than desired,” said study co-author Joshua Knobloch, postdoctoral research associate at JILA, a joint research institute between CU Boulder and the National Institute of Standards and Technology (NIST). “Our goal is to understand the fundamental physics involved so we can engineer future devices to efficiently manage the flow of heat.”
The research began with an unexplained observation: In 2015, researchers led by physicists Margaret Murnane and Henry Kapteyn at JILA were experimenting with bars of metal that were many times thinner than the width of a human hair on a silicon base. When they heated those bars up with a laser, something strange occurred.
“They behaved very counterintuitively,” Knobloch said. “These nano-scale heat sources do not usually dissipate heat efficiently. But if you pack them close together, they cool down much more quickly.”
Now, the researchers know why it happens.
In the new study, they used computer-based simulations to track the passage of heat from their nano-sized bars. They discovered that when they placed the heat sources close together, the vibrations of energy they produced began to bounce off each other, scattering heat away and cooling the bars down.
The group’s results highlight a major challenge in designing the next generation of tiny devices, such as microprocessors or quantum computer chips: When you shrink down to very small scales, heat does not always behave the way you think it should.
Atom by atom
The transmission of heat in devices matters, the researchers added. Even minute defects in the design of electronics like computer chips can allow temperature to build up, adding wear and tear to a device. As tech companies strive to produce smaller and smaller electronics, they’ll need to pay more attention than ever before to phonons—vibrations of atoms that carry heat in solids.
“Heat flow involves very complex processes, making it hard to control,” Knobloch said. “But if we can understand how phonons behave on the small scale, then we can tailor their transport, allowing us to build more efficient devices.”
To do just that, Murnane and Kapteyn and their team of experimental physicists joined forces with a group of theorists led by Mahmoud Hussein, professor in the Ann and H.J. Smead Department of Aerospace Engineering Sciences. His group specializes in simulating, or modeling, the motion of phonons.
“At the atomic scale, the very nature of heat transfer emerges in a new light,” said Hussein who also has a courtesy appointment in the Department of Physics.
The researchers, essentially, recreated their experiment from several years before, but this time, entirely on a computer. They modeled a series of silicon bars, laid side by side like the slats in a train track and heated them up.
The simulations were so detailed, Knobloch said, that the team could follow the behavior of each and every atom in the model—millions of them in all—from start to finish.
“We were really pushing the limits of memory of the Summit Supercomputer at CU Boulder,” he said.
Directing heat
The technique paid off. The researchers found, for example, that when they spaced their silicon bars far enough apart, heat tended to escape away from those materials in a predictable way. The energy leaked from the bars and into the material below them, dissipating in every direction.
When the bars got closer together, however, something else happened. As the heat from those sources scattered, it effectively forced that energy to flow more intensely away from the sources—like a crowd of people in a stadium jostling against each other and eventually leaping out of the exit. The team denoted this phenomenon “directional thermal channeling.”
“This phenomenon increases the transport of heat down into the substrate and away from the heat sources,” Knobloch said.
The researchers suspect that engineers could one day tap into this unusual behavior to gain a better handle on how heat flows in small electronics—directing that energy along a desired path, instead of letting it run wild and free.
For now, the researchers see the latest study as what scientists from different disciplines can do when they work together.
“This project was such an exciting collaboration between science and engineering—where advanced computational analysis methods developed by Mahmoud’s group were critical for understanding new materials behavior uncovered earlier by our group using new extreme ultraviolet quantum light sources,” said Murnane, also a professor of physics.
…
Here’s a link to and a citation for the paper,
Directional thermal channeling: A phenomenon triggered by tight packing of heat sources by Hossein Honarvar, Joshua L. Knobloch, Travis D. Frazer, Begoña Abad, Brendan McBennett, Mahmoud I. Hussein, Henry C. Kapteyn, Margaret M. Murnane, and Jorge N. Hernandez-Charpak. PNAS October 5, 2021 118 (40) e2109056118; DOI: https://doi.org/10.1073/pnas.2109056118
It’s the ‘est’ of it all. The coolest, the whitest, the blackest … Scientists and artists are both pursuing the ‘est’. (More about the pursuit later in this posting.)
In this case, scientists have developed the coolest, whitest paint yet. From an April 16, 2021 news item on Nanowerk,
In an effort to curb global warming, Purdue University engineers have created the whitest paint yet. Coating buildings with this paint may one day cool them off enough to reduce the need for air conditioning, the researchers say.
In October [2020], the team created an ultra-white paint that pushed limits on how white paint can be. Now they’ve outdone that. The newer paint not only is whiter but also can keep surfaces cooler than the formulation that the researchers had previously demonstrated.
“If you were to use this paint to cover a roof area of about 1,000 square feet, we estimate that you could get a cooling power of 10 kilowatts. That’s more powerful than the central air conditioners used by most houses,” said Xiulin Ruan, a Purdue professor of mechanical engineering.
…
Caption: Xiulin Ruan, a Purdue University professor of mechanical engineering, holds up his lab’s sample of the whitest paint on record. Credit: Purdue University/Jared Pike
This is nicely done. Researcher Xiulin Ruan is standing close to a structure that could be said to resemble the sun while in shirtsleeves and sunglasses and holding up a sample of his whitest paint in April (not usually a warm month in Indiana).
The researchers believe that this white may be the closest equivalent of the blackest black, “Vantablack,” [emphasis mine; see comments later in this post] which absorbs up to 99.9% of visible light. The new whitest paint formulation reflects up to 98.1% of sunlight – compared with the 95.5% of sunlight reflected by the researchers’ previous ultra-white paint – and sends infrared heat away from a surface at the same time.
Typical commercial white paint gets warmer rather than cooler. Paints on the market that are designed to reject heat reflect only 80%-90% of sunlight and can’t make surfaces cooler than their surroundings.
The team’s research paper showing how the paint works publishes Thursday (April 15 [2021]) as the cover of the journal ACS Applied Materials & Interfaces.
What makes the whitest paint so white
Two features give the paint its extreme whiteness. One is the paint’s very high concentration of a chemical compound called barium sulfate [emphasis mine] which is also used to make photo paper and cosmetics white.
“We looked at various commercial products, basically anything that’s white,” said Xiangyu Li, a postdoctoral researcher at the Massachusetts Institute of Technology who worked on this project as a Purdue Ph.D. student in Ruan’s lab. “We found that using barium sulfate, you can theoretically make things really, really reflective, which means that they’re really, really white.”
The second feature is that the barium sulfate particles are all different sizes in the paint. How much each particle scatters light depends on its size, so a wider range of particle sizes allows the paint to scatter more of the light spectrum from the sun.
“A high concentration of particles that are also different sizes gives the paint the broadest spectral scattering, which contributes to the highest reflectance,” said Joseph Peoples, a Purdue Ph.D. student in mechanical engineering.
There is a little bit of room to make the paint whiter, but not much without compromising the paint.”Although a higher particle concentration is better for making something white, you can’t increase the concentration too much. The higher the concentration, the easier it is for the paint to break or peel off,” Li said.
How the whitest paint is also the coolest
The paint’s whiteness also means that the paint is the coolest on record. Using high-accuracy temperature reading equipment called thermocouples, the researchers demonstrated outdoors that the paint can keep surfaces 19 degrees Fahrenheit cooler than their ambient surroundings at night. It can also cool surfaces 8 degrees Fahrenheit below their surroundings under strong sunlight during noon hours.
The paint’s solar reflectance is so effective, it even worked in the middle of winter. During an outdoor test with an ambient temperature of 43 degrees Fahrenheit, the paint still managed to lower the sample temperature by 18 degrees Fahrenheit.
This white paint is the result of six years of research building on attempts going back to the 1970s to develop radiative cooling paint as a feasible alternative to traditional air conditioners.
Ruan’s lab had considered over 100 different materials, narrowed them down to 10 and tested about 50 different formulations for each material. Their previous whitest paint was a formulation made of calcium carbonate, an earth-abundant compound commonly found in rocks and seashells.
The researchers showed in their study that like commercial paint, their barium sulfate-based paint can potentially handle outdoor conditions. The technique that the researchers used to create the paint also is compatible with the commercial paint fabrication process.
Patent applications for this paint formulation have been filed through the Purdue Research Foundation Office of Technology Commercialization. This research was supported by the Cooling Technologies Research Center at Purdue University and the Air Force Office of Scientific Research [emphasis mine] through the Defense University Research Instrumentation Program (Grant No.427 FA9550-17-1-0368). The research was performed at Purdue’s FLEX Lab and Ray W. Herrick Laboratories and the Birck Nanotechnology Center of Purdue’s Discovery Park.
Vantablack’s 99.9% light absorption no longer qualifies it for the ‘blackest black’. A newer standard for the ‘blackest black’ was set by the US National Institute of Standards and Technology at 99.99% light absorption with its N.I.S.T. ultra-black in 2019, although that too seems to have been bested.
I have three postings covering the Vantablack and blackest black story,
The third posting (December 2019) provides a brief summary of the story along with what was the latest from the US National Institute of Standards and Technology. There’s also a little bit about the ‘The Redemption of Vanity’ an art piece demonstrating the blackest black material from the Massachusetts Institute of Technology, which they state has 99.995% (at least) absorption of light.
From a science perspective, the blackest black would be useful for space exploration.
I am surprised there doesn’t seem to have been an artistic rush to work with the whitest white. That impression may be due to the fact that the feuds get more attention than quiet work.
Dark side to the whitest white?
Andrew Parnell, research fellow in physics and astronomy at the University of Sheffield (UK), mentions a downside to obtaining the material needed to produce this cooling white paint in a June 10, 2021 essay on The Conversation (h/t Fast Company), Note: Links have been removed,
… this whiter-than-white paint has a darker side. The energy required to dig up raw barite ore to produce and process the barium sulphite that makes up nearly 60% of the paint means it has a huge carbon footprint. And using the paint widely would mean a dramatic increase in the mining of barium.
Parnell ends his essay with this (Note: Links have been removed),
Barium sulphite-based paint is just one way to improve the reflectivity of buildings. I’ve spent the last few years researching the colour white in the natural world, from white surfaces to white animals. Animal hairs, feathers and butterfly wings provide different examples of how nature regulates temperature within a structure. Mimicking these natural techniques could help to keep our cities cooler with less cost to the environment.
The wings of one intensely white beetle species called Lepidiota stigma appear a strikingly bright white thanks to nanostructures in their scales, which are very good at scattering incoming light. This natural light-scattering property can be used to design even better paints: for example, by using recycled plastic to create white paint containing similar nanostructures with a far lower carbon footprint. When it comes to taking inspiration from nature, the sky’s the limit.
Before getting to the moon dust, it seems the US National Institute of Standards and Technology (NIST) has undergone a communications strategy transformation. For example, there’s this whimsical video about the NIST’s latest on moon dust,
An April 28, 2021 news item on phys.org offers a little more whimsy and moon dust from the NIST,
Like a chameleon of the night sky, the moon often changes its appearance. It might look larger, brighter or redder, for example, due to its phases, its position in the solar system or smoke in Earth’s atmosphere. (It is not made of green cheese, however.)
Another factor in its appearance is the size and shape of moon dust particles, the small rock grains that cover the moon’s surface. Researchers at the National Institute of Standards and Technology (NIST) are now measuring tinier moon dust particles than ever before, a step toward more precisely explaining the moon’s apparent color and brightness. This in turn might help improve tracking of weather patterns and other phenomena by satellite cameras that use the moon as a calibration source.
NIST researchers and collaborators have developed a complex method of measuring the exact three-dimensional shape of 25 particles of moon dust collected during the Apollo 11 mission in 1969. The team includes researchers from the Air Force Research Laboratory, the Space Science Institute and the University of Missouri-Kansas City.
These researchers have been studying moon dust for several years. But as described in a new journal paper, they now have X-ray nano computed tomography (XCT), which allowed them to examine the shape of particles as small as 400 nanometers (billionths of a meter) in length.
The research team developed a method for both measuring and computationally analyzing how the dust particle shapes scatter light. Follow-up studies will include many more particles, and more clearly link their shape to light scattering. Researchers are especially interested in a feature called “albedo,” moonspeak for how much light or radiation it reflects.
The recipe for measuring the Moon’s nano dust is complicated. First you need to mix it with something, as if making an omelet, and then turn it on a stick for hours like a rotisserie chicken. Straws and dressmakers’ pins are involved too.
“The procedure is elaborate because it is hard to get a small particle by itself, but one needs to measure many particles for good statistics, since they are randomly distributed in size and shape,” NIST Fellow Ed Garboczi said.
“Since they are so tiny and because they only come in powders, a single particle needs to be separated from all the others,” Garboczi continued. “They are too small to do that by hand, at least not in any quantity, so they must be carefully dispersed in a medium. The medium must also freeze their mechanical motion, in order to be able to get good XCT images. If there is any movement of the particles during the several hours of the XCT scan, then the images will be badly blurred and generally not usable. The final form of the sample must also be compatible with getting the X-ray source and camera close to the sample while it rotates, so a narrow, straight cylinder is best.”
The procedure involved stirring the Apollo 11 material into epoxy, which was then dripped over the outside of a tiny straw to get a thin layer. Small pieces of this layer were then removed from the straw and mounted on dressmakers’ pins, which were inserted into the XCT instrument.
The XCT machine generated X-ray images of the samples that were reconstructed by software into slices. NIST software stacked the slices into a 3D image and then converted it into a format that classified units of volume, or voxels, as either inside or outside the particles. The 3D particle shapes were identified computationally from these segmented images. The voxels making up each particle were saved in separate files that were forwarded to software for solving electromagnetic scattering problems in the visible to the infrared frequency range.
The results indicated that the color of light absorbed by a moon dust particle is highly sensitive to its shape and can be significantly different from that of spherical or ellipsoidal particles of the same size. That doesn’t mean too much to the researchers — yet.
“This is our first look at the influence of actual shapes of lunar particles on light scattering and focuses on some fundamental particle properties,” co-author Jay Goguen of the Space Science Institute said. “The models developed here form the basis of future calculations that could model observations of the spectrum, brightness and polarization of the moon’s surface and how those observed quantities change during the moon’s phases.”
The authors are now studying a wider range of moon dust shapes and sizes, including particles collected during the Apollo 14 mission in 1971. The moon dust samples were loaned to NIST by NASA’s Curation and Analysis Planning Team for Extraterrestrial Materials program.
Here’s a (2nd) link to and a citation for the paper,
Since then, the technique has become even more popular with the result that the US National Institute of Standards and Technology (NIST) has produced a beginner’s guide, according to a Jan. 8, 2021 news item on Nanowerk,
In a technique known as DNA origami, researchers fold long strands of DNA over and over again to construct a variety of tiny 3D structures, including miniature biosensors and drug-delivery containers. Pioneered at the California Institute of Technology in 2006, DNA origami has attracted hundreds of new researchers over the past decade, eager to build receptacles and sensors that could detect and treat disease in the human body, assess the environmental impact of pollutants, and assist in a host of other biological applications.
Although the principles of DNA origami are straightforward, the technique’s tools and methods for designing new structures are not always easy to grasp and have not been well documented. In addition, scientists new to the method have had no single reference they could turn to for the most efficient way of building DNA structures and how to avoid pitfalls that could waste months or even years of research.
That’s why Jacob Majikes and Alex Liddle, researchers at the National Institute of Standards and Technology (NIST) who have studied DNA origami for years, have compiled the first detailed tutorial on the technique. Their comprehensive report provides a step-by-step guide to designing DNA origami nanostructures, using state-of-the-art tools.
…
Here’s an image illustrating some of the techniques for DNA origami,
Caption: Collage shows some of the techniques and designs employed in DNA origami. Credit: K. Dill/NIST
A Jan. 8, 2021 US NIST news release (also on EurekAlert), which originated the news item, provide more detail as to the authors’ motivations, objectives, and future plans for their beginner’s guide,
“We wanted to take all the tools that people have developed and put them all in one place, and to explain things that you can’t say in a traditional journal article,” said Majikes. “Review papers might tell you everything that everyone’s done, but they don’t tell you how the people did it. “
DNA origami relies on the ability of complementary base pairs of the DNA molecule to bind to each other. Among DNA’s four bases — adenine (A), cytosine (C), guanine (G) and thymine (T) — A binds with T and G with C. This means that a specific sequence of As, Ts, Cs and Gs will find and bind to its complement.
The binding enables short strands of DNA to act as “staples,” keeping sections of long strands folded or joining separate strands. A typical origami design may require 250 staples. In this way, the DNA can self-assemble into a variety of shapes, forming a nanoscale framework to which an assortment of nanoparticles — many useful in medical treatment, biological research and environmental monitoring — can attach.
The challenges in using DNA origami are twofold, said Majikes. First, researchers are fabricating 3D structures using a foreign language — the base pairs A, G, T and C. In addition, they’re using those base-pair staples to twist and untwist the familiar double helix of DNA molecules so that the strands bend into specific shapes. That can be difficult to design and visualize. Majikes and Liddle urge researchers to strengthen their design intuition by building 3D mock-ups, such as sculptures made with bar magnets, before they start fabrication. These models, which can reveal which aspects of the folding process are critical and which ones are less important, should then be “flattened” into 2D to be compatible with computer-aided design tools for DNA origami, which typically use two-dimensional representations.
DNA folding can be accomplished in a variety of ways, some less efficient than others, noted Majikes. Some strategies, in fact, may be doomed to failure.
“Pointing out things like ‘You could do this, but it’s not a good idea’ — that type of perspective isn’t in a traditional journal article, but because NIST is focused on driving the state of technology in the nation, we’re able to publish this work in the NIST journal,” Majikes said. “I don’t think there’s anywhere else that would have given us the leeway and the time and the person hours to put all this together.”
Liddle and Majikes plan to follow up their work with several additional manuscripts detailing how to successfully fabricate nanoscale devices with DNA.
Here’s a link to and a citation for the beginner’s guide,
DNA Origami Design: A How-To Tutorial by Majikes, Jacob M. and Liddle, J. Alexander. Journal of Research of the National Institute of Standards and Technology Volume 126, Article No. 126001 (2021) Published online Jan. 8, 2021. DOI: 10.6028/jres.126.001
This is open access and it include such gems as this,
1.2 Education or Skill Level
Readers of this tutorial should be familiar with the physical properties of B-DNA, single-stranded DNA (ssDNA), and crossover junctions. In addition, once ready to create a structure for a specific application, the designer should determine the full list of functional requirements. This list includes answers to the following questions: What should the structure do? What specific properties are critical to the system’s performance?
1.3 Prerequisites
The designer should have either sufficient paper for manual design (not recommended) or a design program such as cadnano [1] (all versions sufficient), nanoengineer®, ParaboninSēquio®, or equivalent.1 A registered account with three-dimensional (3D) structure prediction servers such as CanDo [2, 3] is also recommended.
1.4Tools or Equipment
Equipment includes desktop or laptop computer equipment, craft supplies for macroscale models, and DNA nanotechnology computer-aided design (CAD) software.
