A number of advanced energy technologies — including fuel cells, electrolyzers, and an emerging class of low-power electronics — use protons as the key charge carrier. Whether or not these devices will be widely adopted hinges, in part, on how efficiently they can move protons.
One class of materials known as metal oxides has shown promise in conducting protons at temperatures above 400 degrees Celsius. But researchers have struggled to find the best materials to increase the proton conductivity at lower temperatures and improve efficiency.
Now, MIT researchers have developed a physical model to predict proton mobility across a wide range of metal oxides. In a new paper, the researchers ranked the most important features of metal oxides for facilitating proton conduction, and demonstrated for the first time how much the flexibility of the materials’ oxide ions improves their ability to transfer protons.
The researchers believe their findings can guide scientists and engineers as they develop materials for more efficient energy technologies enabled by protons, which are lighter, smaller, and more abundant than more common charge carriers like lithium ions.
“If you understand the mechanism of a process and what material traits govern that mechanism, then you can tune those traits to improve the speed of that process — in this case, proton conduction,” says Bilge Yildiz, the Breen M. Kerr Professor in the departments of Nuclear Science and Engineering (NSE) and Materials Science and Engineering (DMSE) at MIT and the senior author of a paper describing the work. “For this application, we need to understand these quantitative relations between the proton transfer and the material’s structural, chemical, electronic, and dynamic traits. Establishing these relations can help us screen material databases to find compounds that satisfy those material traits, or even go beyond screening. There could be ways to use generative AI tools to create compounds that optimize for those traits.”
The paper appears in the journal Matter. Joining Yildiz are Heejung W. Chung, the paper’s first author and an MIT PhD student in DMSE; Pjotrs Žguns, a former postdoc in DMSE; and Ju Li, the Carl Richard Soderberg Professor of Power Engineering in NSE and DMSE.
Making protons hop
Protons are already used at scale in electrolyzers for hydrogen production and in fuel cells. They are also expected to be used in promising energy-storage technologies such as proton batteries, which could be water-based and rely on cheaper materials than lithium-ion batteries. A more recent and exciting application is low-energy, brain-inspired computing to emulate synaptic functions in devices for artificial intelligence.
“Proton conductors are important materials in different energy conversion technologies for clean electricity, clean fuels, and clean industrial chemical synthesis,” explains Yildiz. “Inorganic, scalable proton conductors that work at room temperature are also needed for energy-efficient brain-inspired computing.”
Protons, which are the positively charged state of hydrogen, are different from lithium or sodium ions because they don’t have their own electrons — protons consist of just the bare nucleus. Therefore, protons prefer to embed into the electron clouds of nearby ions, hopping from one to the next. In metal oxides, protons embed into oxygen ions, forming a covalent bond, and hop to a nearby oxygen ion through a hydrogen bond. After every hop, the covalent H-O bond rotates to prevent the proton from shuttling back and forth.
All that hopping and rotating got MIT’s researchers thinking that the flexibility of those oxide ion sublattices must be important for conducting protons. Indeed, their previous studies in another class of proton conductors had shown how lattice flexibility impacts proton transport.
For their study, the researchers created a metric to quantify lattice flexibility across materials that they call “O…O fluctuation,” which measures the change in spacing between oxygen ions contributed by phonons at finite temperature. They also created a dataset of other material features that influence proton mobility and set out to quantify how important each one is for facilitating proton conduction.
“We were trying to better understand how protons move through these inorganic materials so that we can optimize them and improve the efficiency of downstream energy and computing applications,” Chung explains.
The researchers ranked the importance of all seven features they studied, which also included structural and chemical traits of materials, and trained a model on the findings to predict how well materials would conduct protons. The model found that the two most important features in predicting proton transfer barriers are the hydrogen bond length and the oxygen sublattice flexibility characterized by the O…O fluctuation metric. The shorter the hydrogen bond length, the better the material was at transporting protons, which aligned with previous studies of metal oxides. The researchers’ O…O fluctuation metric was the new and the second most important feature they studied. The more flexible the oxygen ion chains, the better the proton conduction.
Better proton conductors
The researchers believe their model could be used to estimate proton conduction across a broader range of materials.
“We always have to be cautious about generalizing findings, but the local chemistries and structures we studied have a wide enough spectrum that we think this finding is broadly applicable to a range of inorganic proton conductors,” Yildiz says.
Beyond being used to screen for promising materials, the researchers say their findings could also be used to train generative AI models to create materials optimized for proton transfer. As our understanding of materials improves, that could enable a new class of hyper-efficient clean energy technologies.
“There are very large materials databases generated recently in the field, for example those by Google and Microsoft, that could be screened for these relations we’ve found,” Yildiz says. “If the material compound that satisfies these parameters does not exist, we could also use these parameters to generate new compounds. That would enable increases in the energy efficiency and viability of clean energy conversion and low-power computing devices. For that, we need to figure out how to get more flexible oxide ion sublattices that are percolated. What are the composition and structure metrics that I can use to design the material to have that flexibility? Those are the next steps.”
The research was supported by the U.S. Department of Energy’s Energy Frontier Center – Hydrogen in Energy and Information Sciences – and the National Science Foundation’s Graduate Research Fellowship Program.
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Written by Zach Winn, MIT News
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