Tag Archives: Wenhao Sun

How memristors retain information without a power source? A mystery solved

A September 10, 2024 news item on ScienceDaily provides a technical explanation of how memristors, without a power source, can retain information,

Phase separation, when molecules part like oil and water, works alongside oxygen diffusion to help memristors — electrical components that store information using electrical resistance — retain information even after the power is shut off, according to a University of Michigan led study recently published in Matter.

A September 11, 2024 University of Michigan press release (also on EurekAltert but published September 10, 2024), which originated the news item, delves further into the research,

Up to this point, explanations have not fully grasped how memristors retain information without a power source, known as nonvolatile memory, because models and experiments do not match up.

“While experiments have shown devices can retain information for over 10 years, the models used in the community show that information can only be retained for a few hours,” said Jingxian Li, U-M doctoral graduate of materials science and engineering and first author of the study.

To better understand the underlying phenomenon driving nonvolatile memristor memory, the researchers focused on a device known as resistive random access memory or RRAM, an alternative to the volatile RAM used in classical computing, and are particularly promising for energy-efficient artificial intelligence applications. 

The specific RRAM studied, a filament-type valence change memory (VCM), sandwiches an insulating tantalum oxide layer between two platinum electrodes. When a certain voltage is applied to the platinum electrodes, a conductive filament forms a tantalum ion bridge passing through the insulator to the electrodes, which allows electricity to flow, putting the cell in a low resistance state representing a “1” in binary code. If a different voltage is applied, the filament is dissolved as returning oxygen atoms react with the tantalum ions, “rusting” the conductive bridge and returning to a high resistance state, representing a binary code of “0”. 

It was once thought that RRAM retains information over time because oxygen is too slow to diffuse back. However, a series of experiments revealed that previous models have neglected the role of phase separation. 

“In these devices, oxygen ions prefer to be away from the filament and will never diffuse back, even after an indefinite period of time. This process is analogous to how a mixture of water and oil will not mix, no matter how much time we wait, because they have lower energy in a de-mixed state,” said Yiyang Li, U-M assistant professor of materials science and engineering and senior author of the study.

To test retention time, the researchers sped up experiments by increasing the temperature. One hour at 250°C is equivalent to about 100 years at 85°C—the typical temperature of a computer chip.

Using the extremely high-resolution imaging of atomic force microscopy, the researchers imaged filaments, which measure only about five nanometers or 20 atoms wide, forming within the one micron wide RRAM device.  

“We were surprised that we could find the filament in the device. It’s like finding a needle in a haystack,” Li said. 

The research team found that different sized filaments yielded different retention behavior. Filaments smaller than about 5 nanometers dissolved over time, whereas filaments larger than 5 nanometers strengthened over time. The size-based difference cannot be explained by diffusion alone.

Together, experimental results and models incorporating thermodynamic principles showed the formation and stability of conductive filaments depend on phase separation. 

The research team leveraged phase separation to extend memory retention from one day to well over 10 years in a rad-hard memory chip—a memory device built to withstand radiation exposure for use in space exploration. 

Other applications include in-memory computing for more energy efficient AI applications or memory devices for electronic skin—a stretchable electronic interface designed to mimic the sensory capabilities of human skin. Also known as e-skin, this material could be used to provide sensory feedback to prosthetic limbs, create new wearable fitness trackers or help robots develop tactile sensing for delicate tasks.

“We hope that our findings can inspire new ways to use phase separation to create information storage devices,” Li said.

Researchers at Ford Research, Dearborn; Oak Ridge National Laboratory; University at Albany; NY CREATES; Sandia National Laboratories; and Arizona State University, Tempe contributed to this study.

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

Thermodynamic origin of nonvolatility in resistive memory by Jingxian Li, Anirudh Appachar, Sabrina L. Peczonczyk, Elisa T. Harrison, Anton V. Ievlev, Ryan Hood, Dongjae Shin, Sangmin Yoo, Brianna Roest, Kai Sun, Karsten Beckmann, Olya Popova, Tony Chiang, William S. Wahby, Robin B. Jacobs-Godrim, Matthew J. Marinella, Petro Maksymovych, John T. Heron, Nathaniel Cady, Wei D. Lu, Suhas Kumar, A. Alec Talin, Wenhao Sun, Yiyang Li. Matter DOI: https://doi.org/10.1016/j.matt.2024.07.018 Published online: August 26, 2024

This paper is behind a paywall.

Largest database of elemental crystal surfaces and shapes in the world

A Sept. 13, 2016 news item on Nanowerk describes the database,

Nanoengineers at the University of California San Diego [UCSD], in collaboration with the Materials Project at Lawrence Berkeley National Laboratory (Berkeley Lab), have created the world’s largest database of elemental crystal surfaces and shapes to date. Dubbed Crystalium, this new open-source database can help researchers design new materials for technologies in which surfaces and interfaces play an important role, such as fuel cells, catalytic converters in cars, computer microchips, nanomaterials and solid-state batteries.

rystalium is a new open-source database with the largest collection of elemental crystal surfaces and shapes to date. Image courtesy of the Materials Virtual Lab at UC San Diego

Crystalium is a new open-source database with the largest collection of elemental crystal surfaces and shapes to date. Image courtesy of the Materials Virtual Lab at UC San Diego

A Sept. 13, 2016 UCSD news release reveals more about the goals for the database and the database itself (Note: Links have been removed),

“This work is an important starting point for studying the material surfaces and interfaces, where many novel properties can be found. We’ve developed a new resource that can be used to better understand surface science and find better materials for surface-driven technologies,” said Shyue Ping Ong, a nanoengineering professor at UC San Diego and senior author of the study.

For example, fuel cell performance is partly influenced by the reaction of molecules such as hydrogen and oxygen on the surfaces of metal catalysts. Also, interfaces between the electrodes and electrolyte in a rechargeable lithium-ion battery host a variety of chemical reactions that can limit the battery’s performance. The work in this study is useful for these applications, said Ong, who is also part of a larger effort by the UC San Diego Sustainable Power and Energy Center to design better battery materials.

“Researchers can use this database to figure out which elements or materials are more likely to be viable catalysts for processes like ammonia production or making hydrogen gas from water,” said Richard Tran, a nanoengineering PhD student in Ong’s Materials Virtual Lab and the study’s first author. Tran did this work while he was an undergraduate at UC San Diego.

The work, published Sept. 13 [2016] in the journal Scientific Data, provides the surface energies and equilibrium crystal shapes of more than 100 polymorphs of 72 elements in the periodic table. Surface energy describes the stability of a surface; it is a measure of the excess energy of atoms on the surface relative to those in the bulk material. Knowing surface energies is useful for designing materials that perform their functions primarily on their surfaces, like catalysts and nanoparticles.

The surface energies of some elements in their crystal form have been measured experimentally, but this is not a trivial task. It involves melting the crystal, measuring the resulting liquid’s surface tension at the melting temperature, then extrapolating that value back to room temperature. This process also requires that the sample have a clean surface, which is challenging because other atoms and molecules (like oxygen and water) can easily adsorb to the surface and modify the surface energy.

Surface energies obtained by this method are averaged values that lack the facet-specific resolution that is necessary for design, Ong said. “This is one of the areas where the ’virtual laboratory’ can create the most value—by allowing us to precisely control the models and conditions in a way that is extremely difficult to do in experiments.”

Also, the surface energy is not just a single number for each crystal because it depends on the crystal’s orientation. “A crystal is a regular arrangement of atoms. When you cut a crystal in different places and at different angles, you expose different facets with unique arrangements of atoms,” explained Ong, who teaches the course NANO106 – Crystallography of Materials at UC San Diego.

To carry out this ambitious project, Ong and his team developed highly sophisticated automated workflows to calculate surface energies from first principles. These workflows are built on the popular open-source Python Materials Genomics library and FireWorks workflow codes of the Materials Project, which were co-authored by Ong.

“The techniques for calculating surface energies have been known for decades. The major accomplishment is the codification of how to generate surface models and run these complex calculations in a robust and efficient manner,” Tran said. The surface model generation software code developed by the team has already been extended by others to study substrates and interfaces. Powerful supercomputers at the San Diego Supercomputer Center and the National Energy Research Scientific Computing Center at the Lawrence Berkeley National Lab were used for the calculations.

Ong’s team worked with researchers from the Berkeley Lab’s Materials Project to develop and construct Crystalium’s website. Co-founded and directed by Berkeley Lab scientist Kristin Persson, the Materials Project is a Google-like database of material properties calculated by supercomputers.

“The Materials Project was designed to be an open and accessible tool for scientists and engineers to accelerate materials innovation,” Persson said. “In five years, it has attracted more than 20,000 users working on everything from batteries to photovoltaics to thermoelectrics, and it’s extremely gratifying to see scientists like Ong providing lots of high quality computed data of high interest and making it freely available and easily accessible to the public.”

The researchers pointed out that their database is the most extensive collection of calculated surface energies for elemental crystalline solids to date. Compared to previous compilations, Crystalium contains surface energies for far more elements, including both metals and non-metals, and for more facets in each crystal. The elements that have been excluded from their calculations are gases and radioactive elements. Notably, Ong and his team have validated their calculated surface energies with those from experiments, and the values are in excellent agreement.

Moving forward, the team will work on expanding the scope of the database beyond single elements to multi-element compounds like alloys, which are made of two or more different metals, and binary oxides, which are made of oxygen and one other element. Efforts are also underway to study the effect of common adsorbates, such as hydrogen, on surface energies, which is key to understanding the stability of surfaces in aqueous media.

“As we continue to build this database, we hope that the research community will see it as a useful resource for the rational design of target surface or interfacial properties,” said Ong,

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

Surface energies of elemental crystals by Richard Tran, Zihan Xu, Balachandran Radhakrishnan, Donald Winston, Wenhao Sun, Kristin A. Persson, & Shyue Ping Ong.  Scientific Data 3, Article number: 160080 (2016)  doi:10.1038/sdata.2016.80 Published online: 13 September 2016

This paper is open access.

Here, too, is a link to Crystalium.