Tag Archives: Oara Neumann

New approach to detecting soil contaminants

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This new approach doesn’t require test samples!?! A May 9, 2925 news item on ScienceDaily explains how that is possible,

A team of researchers at Rice University and Baylor College of Medicine has developed a new strategy for identifying hazardous pollutants in soil, even ones that have never been isolated or studied in a lab.

The new approach, described in a study published in Proceedings of the National Academy of Sciences [PNAS], uses light-based imaging, theoretical predictions of compounds’ light signatures and machine learning (ML) algorithms to detect toxic compounds like polycyclic aromatic hydrocarbons (PAHs) and their derivative compounds (PACs) in soil. A common by-product of combustion, PAHs and PACs have been linked to cancer, developmental issues and other serious health problems.

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A May 9, 2025 Rice University news release (also on EurekAlert), which originated the news item, goes on to give details, Note: Links have been removed,

Identifying pollutants in soil usually requires advanced laboratories and standard physical reference samples of the suspected contaminants. However, for many environmental pollutants that pose a public health risk, there is no experimental data available that can be used to detect them.

“This method makes it possible to identify chemicals that have not yet been isolated experimentally,” said Naomi Halas, University Professor and the Stanley C. Moore Professor of Electrical and Computer Engineering at Rice.

The new method uses a light-based imaging technique known as surface-enhanced Raman spectroscopy, which analyzes how light interacts with molecules, tracking the unique patterns, or spectra, they emit. Spectra serve as “chemical fingerprints” for each compound. The technique is refined through the use of signature nanoshells designed to enhance relevant traits in the spectra.

Using density functional theory ⎯ a computational modeling technique that can predict how atoms and electrons behave in a molecule ⎯ the researchers calculated what the spectra of a whole range of PAHs and PACs look like based on the compounds’ molecular structure. This allowed them to generate a virtual library of “fingerprints” for PAHs and PACs.

Two complementary ML algorithms ⎯ characteristic peak extraction and characteristic peak similarity ⎯ were used to parse relevant spectral traits in real-world soil samples and match them to compounds mapped out in the virtual library of spectra.

“We are using PAHs in soil to illustrate this very important new strategy,” Halas said. “There are tens of thousands of PAH-derived chemicals and this approach ⎯ calculating their spectra and using machine learning to connect the theoretically calculated spectra to those observed in a sample ⎯ allows us to identify chemicals that we may not, or do not, have any experimental data for.”

The method addresses a critical gap in environmental monitoring, opening the door to identifying a much broader range of hazardous compounds ⎯ including those that have changed over time. This is especially important given that soil is a dynamic environment where chemicals are subject to transformations that can render them harder to detect.

Thomas Senftle, Rice’s William Marsh Rice Trustee Associate Professor of Chemical and Biomolecular Engineering, compared the process to using facial recognition in order to find an individual in a crowd.

“You can imagine we have a picture of a person when they’re a teenager, but now they’re in their 30s,” Senftle said. “In my group what we do is, on the theory side, we can predict what the picture will look like.”

The researchers tested the method on soil from a restored watershed and natural area using both artificially contaminated samples and a control sample. Results showed the new approach reliably picked out even minute traces of PAHs using a simpler and faster process than conventional techniques.

“This method can identify lesser-known and largely unstudied PAH and PAC pollutant molecules,” said Oara Neumann, a Rice research scientist who is a co-author on the study.

In the future, the method could enable on-site field testing by integrating the ML algorithms and theoretical spectral library with portable Raman devices into a mobile system, making it easier for farmers, communities and environmental agencies to test soil for hazardous compounds without needing to send samples to specialized labs and wait days for results.

Ankit Patel, assistant professor of electrical and computer engineering at Rice and assistant professor of neuroscience at BCM, is a corresponding author on the study alongside Halas.

Other Rice co-authors include computer science doctoral alum Yilong Ju; doctoral students Sarah Denison, Peixuan Jin and Andres Sanchez-Alvarado; Peter Nordlander, the Wiess Chair in Physics and Astronomy and professor of electrical and computer engineering and materials science and nanoengineering; and Pedro Alvarez, the George R. Brown Professor of Civil and Environmental Engineering.

The research was supported by the National Institutes of Health (P42ES027725-01), the Welch Foundation (C-1220, C-1222) and the Carl and Lillian Illig Fellowship (Smalley-Curl Institute, H20398-239440). The content herein is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations and institutions.

Here’s a link to and a citation for the paper,

In silico machine learning–enabled detection of polycyclic aromatic hydrocarbons from contaminated soil by Yilong Ju, Oara Neumann, Sara B. Denison, Peixuan Jin, Andres B. Sanchez-Alvarado, Peter Nordlander, Thomas P. Senftle, Pedro J. J. Alvarez, Ankit Patel, and Naomi J. Halas. PNAS [Proceedings of the National Academy of Sciences] 122 (19) e2427069122 May 13, 2025 DOI: https://doi.org/10.1073/pnas.2427069122 PUblished online: May 8, 2025

This paper is behind a paywall.

Using only sunlight to desalinate water

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The researchers seem to believe that this new desalination technique could be a game changer. From a June 20, 2017 news item on Azonano,

An off-grid technology using only the energy from sunlight to transform salt water into fresh drinking water has been developed as an outcome of the effort from a federally funded research.

The desalination system uses a combination of light-harvesting nanophotonics and membrane distillation technology and is considered to be the first major innovation from the Center for Nanotechnology Enabled Water Treatment (NEWT), which is a multi-institutional engineering research center located at Rice University.

NEWT’s “nanophotonics-enabled solar membrane distillation” technology (NESMD) integrates tried-and-true water treatment methods with cutting-edge nanotechnology capable of transforming sunlight to heat. …

A June 19, 2017 Rice University news release, which originated the news item, expands on the theme,

More than 18,000 desalination plants operate in 150 countries, but NEWT’s desalination technology is unlike any other used today.

“Direct solar desalination could be a game changer for some of the estimated 1 billion people who lack access to clean drinking water,” said Rice scientist and water treatment expert Qilin Li, a corresponding author on the study. “This off-grid technology is capable of providing sufficient clean water for family use in a compact footprint, and it can be scaled up to provide water for larger communities.”

The oldest method for making freshwater from salt water is distillation. Salt water is boiled, and the steam is captured and run through a condensing coil. Distillation has been used for centuries, but it requires complex infrastructure and is energy inefficient due to the amount of heat required to boil water and produce steam. More than half the cost of operating a water distillation plant is for energy.

An emerging technology for desalination is membrane distillation, where hot salt water is flowed across one side of a porous membrane and cold freshwater is flowed across the other. Water vapor is naturally drawn through the membrane from the hot to the cold side, and because the seawater need not be boiled, the energy requirements are less than they would be for traditional distillation. However, the energy costs are still significant because heat is continuously lost from the hot side of the membrane to the cold.

“Unlike traditional membrane distillation, NESMD benefits from increasing efficiency with scale,” said Rice’s Naomi Halas, a corresponding author on the paper and the leader of NEWT’s nanophotonics research efforts. “It requires minimal pumping energy for optimal distillate conversion, and there are a number of ways we can further optimize the technology to make it more productive and efficient.”

NEWT’s new technology builds upon research in Halas’ lab to create engineered nanoparticles that harvest as much as 80 percent of sunlight to generate steam. By adding low-cost, commercially available nanoparticles to a porous membrane, NEWT has essentially turned the membrane itself into a one-sided heating element that alone heats the water to drive membrane distillation.

“The integration of photothermal heating capabilities within a water purification membrane for direct, solar-driven desalination opens new opportunities in water purification,” said Yale University ‘s Menachem “Meny” Elimelech, a co-author of the new study and NEWT’s lead researcher for membrane processes.

In the PNAS study, researchers offered proof-of-concept results based on tests with an NESMD chamber about the size of three postage stamps and just a few millimeters thick. The distillation membrane in the chamber contained a specially designed top layer of carbon black nanoparticles infused into a porous polymer. The light-capturing nanoparticles heated the entire surface of the membrane when exposed to sunlight. A thin half-millimeter-thick layer of salt water flowed atop the carbon-black layer, and a cool freshwater stream flowed below.

Li, the leader of NEWT’s advanced treatment test beds at Rice, said the water production rate increased greatly by concentrating the sunlight. “The intensity got up 17.5 kilowatts per meter squared when a lens was used to concentrate sunlight by 25 times, and the water production increased to about 6 liters per meter squared per hour.”

Li said NEWT’s research team has already made a much larger system that contains a panel that is about 70 centimeters by 25 centimeters. Ultimately, she said, NEWT hopes to produce a modular system where users could order as many panels as they needed based on their daily water demands.

“You could assemble these together, just as you would the panels in a solar farm,” she said. “Depending on the water production rate you need, you could calculate how much membrane area you would need. For example, if you need 20 liters per hour, and the panels produce 6 liters per hour per square meter, you would order a little over 3 square meters of panels.”

Established by the National Science Foundation in 2015, NEWT aims to develop compact, mobile, off-grid water-treatment systems that can provide clean water to millions of people who lack it and make U.S. energy production more sustainable and cost-effective. NEWT, which is expected to leverage more than $40 million in federal and industrial support over the next decade, is the first NSF Engineering Research Center (ERC) in Houston and only the third in Texas since NSF began the ERC program in 1985. NEWT focuses on applications for humanitarian emergency response, rural water systems and wastewater treatment and reuse at remote sites, including both onshore and offshore drilling platforms for oil and gas exploration.

There is a video but it is focused on the NEWT center rather than any specific water technologies,

For anyone interested in the technology, here’s a link to and a citation for the researchers’ paper,

Nanophotonics-enabled solar membrane distillation for off-grid water purification by Pratiksha D. Dongare, Alessandro Alabastri, Seth Pedersen, Katherine R. Zodrow, Nathaniel J. Hogan, Oara Neumann, Jinjian Wu, Tianxiao Wang, Akshay Deshmukh,f, Menachem Elimelech, Qilin Li, Peter Nordlander, and Naomi J. Halas. PNAS {Proceedings of the National Academy of Sciences] doi: 10.1073/pnas.1701835114 June 19, 2017

This paper appears to be open access.

Nanophotonics transforms Raman spectroscopy at Rice University (US)

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This new technique for sensing molecules is intriguing. From a July 15, 2014 news item on Azonano,

Nanophotonics experts at Rice University [Texas, US] have created a unique sensor that amplifies the optical signature of molecules by about 100 billion times. Newly published tests found the device could accurately identify the composition and structure of individual molecules containing fewer than 20 atoms.

The new imaging method, which is described this week in the journal Nature Communications, uses a form of Raman spectroscopy in combination with an intricate but mass reproducible optical amplifier. Researchers at Rice’s Laboratory for Nanophotonics (LANP) said the single-molecule sensor is about 10 times more powerful that previously reported devices.

A July 15, 2014 Rice University news release (also on EurekAlert), which originated the news item, provides more detail about the research,

“Ours and other research groups have been designing single-molecule sensors for several years, but this new approach offers advantages over any previously reported method,” said LANP Director Naomi Halas, the lead scientist on the study. “The ideal single-molecule sensor would be able to identify an unknown molecule — even a very small one — without any prior information about that molecule’s structure or composition. That’s not possible with current technology, but this new technique has that potential.”

The optical sensor uses Raman spectroscopy, a technique pioneered in the 1930s that blossomed after the advent of lasers in the 1960s. When light strikes a molecule, most of its photons bounce off or pass directly through, but a tiny fraction — fewer than one in a trillion — are absorbed and re-emitted into another energy level that differs from their initial level. By measuring and analyzing these re-emitted photons through Raman spectroscopy, scientists can decipher the types of atoms in a molecule as well as their structural arrangement.

Scientists have created a number of techniques to boost Raman signals. In the new study, LANP graduate student Yu Zhang used one of these, a two-coherent-laser technique called “coherent anti-Stokes Raman spectroscopy,” or CARS. By using CARS in conjunction with a light amplifier made of four tiny gold nanodiscs, Halas and Zhang were able to measure single molecules in a powerful new way. LANP has dubbed the new technique “surface-enhanced CARS,” or SECARS.

“The two-coherent-laser setup in SECARS is important because the second laser provides further amplification,” Zhang said. “In a conventional single-laser setup, photons go through two steps of absorption and re-emission, and the optical signatures are usually amplified around 100 million to 10 billion times. By adding a second laser that is coherent with the first one, the SECARS technique employs a more complex multiphoton process.”

Zhang said the additional amplification gives SECARS the potential to address most unknown samples. That’s an added advantage over current techniques for single-molecule sensing, which generally require a prior knowledge about a molecule’s resonant frequency before it can be accurately measured.

Another key component of the SECARS process is the device’s optical amplifier, which contains four tiny gold discs in a precise diamond-shaped arrangement. The gap in the center of the four discs is about 15 nanometers wide. Owing to an optical effect called a “Fano resonance,” the optical signatures of molecules caught in that gap are dramatically amplified because of the efficient light harvesting and signal scattering properties of the four-disc structure.

Fano resonance requires a special geometric arrangement of the discs, and one of LANP’s specialties is the design, production and analysis of Fano-resonant plasmonic structures like the four-disc “quadrumer.” In previous LANP research, other geometric disc structures were used to create powerful optical processors.

Zhang said the quadrumer amplifiers are a key to SECARS, in part because they are created with standard e-beam lithographic techniques, which means they can be easily mass-produced.

“A 15-nanometer gap may sound small, but the gap in most competing devices is on the order of 1 nanometer,” Zhang said. “Our design is much more robust because even the smallest defect in a one-nanometer device can have significant effects. Moreover, the larger gap also results in a larger target area, the area where measurements take place. The target area in our device is hundreds of times larger than the target area in a one-nanometer device, and we can measure molecules anywhere in that target area, not just in the exact center.”

Halas, the Stanley C. Moore Professor in Electrical and Computer Engineering and a professor of biomedical engineering, chemistry, physics and astronomy at Rice, said the potential applications for SECARS include chemical and biological sensing as well as metamaterials research. She said scientific labs are likely be the first beneficiaries of the technology.

“Amplification is important for sensing small molecules because the smaller the molecule, the weaker the optical signature,” Halas said. “This amplification method is the most powerful yet demonstrated, and it could prove useful in experiments where existing techniques can’t provide reliable data.”

Here’s a link to and a citation for the paper,

Coherent anti-Stokes Raman scattering with single-molecule sensitivity using a plasmonic Fano resonance by Yu Zhang, Yu-Rong Zhen, Oara Neumann, Jared K. Day, Peter Nordlander & Naomi J. Halas. Nature Communications 5, Article number: 4424 doi:10.1038/ncomms5424 Published 14 July 2014

This paper is behind a paywall.