http://materialsvirtuallab.org/

Materials Virtual Lab, 9500 Gilman Drive, San Diego, CA (2026)

11/29/2022

Dr Chi Chen’s swansong work in our group, “A Universal Graph Deep Learning Potential for the Periodic Table” is now published in Nature Computational Science! Interatomic potentials (IAPs), which describe the potential energy surface of atoms, are a fundamental input for atomistic simulations. However, existing IAPs are either fitted to narrow chemistries or too inaccurate for general applications. In this work, we combine graph neural networks with traditional 3-body interactions to develop a flexible, yet accurate architecture for machine learning of materials properties. Using the massive database of structural relaxations performed by the Materials Project over the past ten years, we train a universal IAP for 89 elements of the periodic table with broad applications in structural relaxation, dynamic simulations and property prediction of materials across diverse chemical spaces.

Using the new capabilities of the M3GNet universal IAP, we are proud to launch matterverse.ai, a ML database of yet-to-be-synthesized materials. Matterverse.ai currently contains about 31 million hypothetical crystal structures, of which about 1.8 million materials were identified to be potentially stable. The database also provides ML properties using state-of-the-art multi-fidelity MEGNet models, such as experimental, HSE and PBE band gaps, bulk and shear moduli, etc.

Dr Chi Chen’s swansong work in our group, “A Universal Graph Deep Learning Potential for the Periodic Table” is now published in Nature Computational Science! Interatomic potentia…

10/07/2022

Congrats to Hideyuki Komatsu, our visiting scientist from Nissan, on his first author work “Interfacial Stability of Layered LiNixMnyCo1−x−yO2 Cathodes with Sulfide Solid Electrolytes in All-Solid-State Rechargeable Lithium-Ion Batteries from First-Principles Calculations” published in the Journal of Physical Chemistry C as part of the Esther Sans Takeuchi Festschrift special issue! The other authors are Sw****ka Banerjee, Manas Likhit Holekevi Chandrappa, Ji Qi, Balachandran (Bala) G Radhakrishnan, Shigemasa Kuwata and Kazuyuki Sakamoto.

In this work, we explore the relationship between the composition of layered LiNixMnyCo1−x−yO2 (NMC) cathodes and interfacial stability in all-solid-state lithium-ion batteries. A key insight is that the broader commercial trend towards high Ni content to reduce cost leads to significantly more reactive interfaces with the Li6PS5Cl argyrodite solid electrolyte. This suggests that current efforts to reduce the Co content in cathodes may compromise potential applications in all-solid-state architectures. Nevertheless, we find that common SEI phases such as Li2CO3, surface phases such as NiO, and oxide buffer layers such as LiNbO3 can provide effective protection between NMC and LPSCl.

Congrats to Hideyuki Komatsu, our visiting scientist from Nissan, on his first author work “Interfacial Stability of Layered LiNixMnyCo1−x−yO2 Cathodes with Sulfide Solid Electrolytes in All-…

09/24/2022

Our work on "Thermodynamics and Kinetics of the Cathode−Electrolyte Interface in All-Solid-State Li−S Batteries" has been published in the Journal of the American Chemical Society! This work is authored by Manas Likhit Holekevi Chandrappa together with co-authors Ji Qi, Chi Chen and Sw****ka Banerjee.

Lithium−sulfur batteries (LSBs) use cheap and abundant sulfur in place of expensive metal-based cathodes. Using a solid electrolyte in place of traditional liquid electrolytes mitigates polysulfide shuttling, a key impediment to LSB commercialization. In this work, we present a comprehensive study of the thermodynamics and kinetics of the cathode−electrolyte interface in all-solid-state LSBs. Using DFT calculations, we show that among the major solid electrolyte chemistries (oxides, sulfides, nitrides, and halides), sulfides are the most stable solid electrolytes against the S cathode, as well as the most promising buffer layers if the use of other SE chemistries is desired. Finally, MD simulations with an accurate machine learning interatomic potential revealed that the most stable Li3PS4(100)/S interfaces form 2D channels with lower activation barriers for Li diffusion. These results provide critical new insights into the cathode−electrolyte interface design for next-generation all-solid-state LSBs.

We gratefully acknowledge Nissan Motor Corporation and Nissan North America for their generous support for this work!

This work has been published open access and can be found on our website or at the JACS website.

Congratulations to Manas Likhit Holekevi Chandrappa, Ji Qi, Chi Chen and Sw****ka Banerjee on the publication of “Thermodynamics and Kinetics of the Cathode−Electrolyte Interface in All-Solid…

06/09/2021

Manas just published his first paper on “Correlated Octahedral Rotation and Organic Cation Reorientation Assist Halide Ion Migration in Lead Halide Perovskites” in Chemistry of Materials! Halide ion migration is one of the main contributors to instability and hysteresis in lead halide perovskite (LHP) solar cells. In this collaborative work with the David Fenning group, we elucidate the effect of octahedral rotation and organic cation rotation on halide ion migration in APbBr3 (A = Cs or methylammonium/MA) LHPs. While both effects lower halide migration barriers, organic cation rotation plays a much bigger role in hybrid organic-inorganic LHPs, which can be linked to changes in H bonding during the halide migration process. We suggest that “locking” the organic cation via chemical and processing means can help mitigate halide migration-induced instability and reduced hysteresis in LHP solar cells.

Manas just published his first paper on “Correlated Octahedral Rotation and Organic Cation Reorientation Assist Halide Ion Migration in Lead Halide Perovskites” in Chemistry of Material…

05/06/2021

Dr Chi Chen from the Materials Virtual Lab gave a talk at the Global XAS Journal Club on our efforts at constructing large X-ray absorption spectra databases using high-throughput computation and the development of machine learning models that can supercharge the interpretation of such spectra. Check out his inspiring talk below!

Dr Chi Chen gave a talk at the Global XAS Journal Club on the Materials Virtual Lab's efforts at constructing large XAS databases using high-throughput compu...

02/23/2021

Our collaborative work with the Meng (UCSD) and Clement (UCSB) groups on the discovery of the Na3-xY1-xZrxCl6 (NYZC) ion conductor has just been published in Nature Communications. While rechargeable solid-state sodium-ion batteries (SSSBs) promise to bring about safer and more energy-dense energy storage, the poor interfacial stability between existing solid electrolytes and typical oxide cathodes has limited their long-term cycling performance and practicality. Using DFT calculations and MD simulations with a machine learning interatomic potential, Sw****ka Banerjee and Ji Qi from the Materials Virtual Lab identified NYZC as a promising new ion conductor that is both electrochemically stable up to 3.8 V vs. Na/Na+ and chemically compatible with oxide cathodes. NYZC’s ionic conductivity of 6.6 × 10−5 S/cm at ambient temperature, several orders of magnitude higher than oxide coatings, is due to abundant Na vacancies and cooperative MCl6 rotation. A SSSB comprising a NaCrO2 + NYZC composite cathode, Na3PS4 electrolyte, and Na-Sn anode exhibits an exceptional first-cycle Coulombic efficiency of 97.1% at room temperature and can cycle over 1000 cycles with 89.3% capacity retention at 40 °C.

Our collaborative work with the Meng (UCSD) and Clement (UCSB) groups on the discovery of the Na3-xY1-xZrxCl6 (NYZC) ion conductor has just been published in Nature Communications. While rechargeab…

02/05/2021

Our collaborative work with Prof Hu’s group at Florida State University on “Tunable Lithium-Ion Transport in Mixed-Halide Argyrodites Li6-xPS5-xClBrx: An Unusual Compositional Space” has been published in Chemistry of Materials. In this work, we report a new compositional space of argyrodite superionic conductors, Li6−xPS5−xClBrx [0 ≤ x ≤ 0.8]. In particular, Li5.3PS4.3ClBr0.7 has a remarkably high ionic conductivity of 24 mS/cm at 25 °C and an extremely low lithium migration barrier of 0.155 eV that makes it highly promising for low-temperature operation. Using NMR and DFT calculations (performed by Sw****ka Banerjee from the Materials Virtual Lab), we show that bromination leads to co-occupancy of Cl-, Br- , and S2- at 4a/4d sites eventually resulting in a “liquid-like” Li-sublattice with a ﬂattened energy landscape when x approaches 0.7.

Our collaborative work with Prof Hu’s group at Florida State University on “Tunable Lithium-Ion Transport in Mixed-Halide Argyrodites Li6-xPS5-xClBrx: An Unusual Compositional Space& #82…

02/04/2021

Chi Chen gave a talk at nanoHub’s Hands-on Data Science and Machine Learning Training Series on how to develop MatErials Graph Network (MEGNet) models for predicting various materials properties from crystal structure. He also demonstrates how the MEGNet framework can be adapted to work with multi-fidelity data sources to improve predictions on high-value small datasets (e.g., experimental data). Extensive examples are shown using Jupyter notebooks. The video is available on the Materials Virtual Lab Youtube Channel.

In this talk, Chi Chen from the Materials Virtual Lab gives a tutorial on how to develop MatErials Graph Network (MEGNet) models for predicting various mater...

01/28/2021

Yunxing gave a talk at NanoHUB’s Hands-on Data Science and Machine Learning Training Series today on how to conveniently develop machine learning interatomic potentials (ML-IAPs) using the Materials Machine Learning (maml) library. ML-IAPs describe the potential energy surface using local environment descriptors and has been demonstrated to be able to achieve near-DFT accuracy with linear scaling with respect to the number of atoms. The recording of this talk is now available on the Materials Virtual Lab’s Youtube channel.

Yunxing gave a talk at NanoHUB’s Hands-on Data Science and Machine Learning Training Series today on how to conveniently develop machine learning interatomic potentials (ML-IAPs) using the Ma…

01/14/2021

Our paper on “Learning properties of ordered and disordered materials from multi-fidelity data” has just been published in the inaugural issue of Nature Computational Science! In this work, we address two major impediments to ML for materials science. The first impediment is that valuable accurate data is much more expensive to obtain than less accurate data. Using multi-fidelity materials graph networks (MEGNet), we show that we can use the lower quality data to improve underlying structural representations in models, and in the process significantly improve predictions on smaller, more valuable data (e.g., experimental measurements). The second impediment is that making predictions on disordered materials, which is the vast majority of known materials, is much more difficult than on ordered materials. We show that the elemental representations (embeddings) learned by our MEGNet models can be used to directly model disordered materials.

Our paper on “Learning properties of ordered and disordered materials from multi-fidelity data” has just been published in the inaugural issue of Nature Computational Science! In this w…

01/05/2021

Zhuoying’s paper on “Design Principles for Cation-Mixed Sodium Solid Electrolytes” is the first publication from the Materials Virtual Lab in 2021! All-solid-state sodium-ion batteries are highly promising for next-generation grid energy storage with improved safety. Published in Advanced Energy Materials, this work develops design rules for the highly promising family of cation-mixed Na superionic conductors Na3PnS4-Na4TtS4. We show that cation mixing results in the “worst of both worlds” in terms of electrochemical stability, but can potentially lead to improved ionic conductivity and moisture stability. In particular, Na11Sn2AsS12 is identified as a hitherto unexplored superionic conductor with higher Na + conductivity and better moisture stability than those already reported experimentally.

Zhuoying’s paper on “Design Principles for Cation-Mixed Sodium Solid Electrolytes” is the first publication from the Materials Virtual Lab in 2021! All-solid-state sodium-ion batt…

12/15/2020

Our joint publication with Prof Hailong Chen’s group on “Multiprincipal Component P2-Na0.6(Ti0.2Mn0.2Co0.2Ni0.2Ru0.2)O2 as a High-Rate Cathode for Sodium-Ion Batteries” has just been published in JACS Au. In this work, we extended the “high-entropy” concept in metal alloys and ceramics to layered oxide cathode materials, which stabilizes the crystal structure and enhances diffusion. Chi Chen from our group showed using AIMD calculations and NEB calculations that the high-entropy concept leads to a percolating network of low barrier pathways for fast, macroscopic Na diffusion, resulting in the observed high rate performance.

Our joint publication with Prof Hailong Chen’s group on “Multiprincipal Component P2-Na0.6(Ti0.2Mn0.2Co0.2Ni0.2Ru0.2)O2 as a High-Rate Cathode for Sodium-Ion Batteries” has just b…

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