Category: Publications

Publications

Enhancing Energy Density of Li3V2O5 anode

In 2020, Prof Ping Liu’s group and our group proposed a highly promising anode material – disordered rock salt (DRS) Li3V2O5 (LVO) – which had a near-ideal voltage of 0.6V vs Li/Li+ and fast Li diffusion. In this work, we show that we can further increase the energy density of this anode by Mg doping. Due to the increase in site energy due to Mg doping, the voltage of the LVO anode is reduced by a further 10%, while still retaining low Li migration barriers. Mg-doped LVO retains over 95% of its capacity over 1000 cycles at a rate of 5 C. Full cells with a LiNi0.8Co0.1Mn0.1O2 cathode demonstrate the expected increase in cell voltage and energy density while retaining 91% of their capacity over 250 cycles at 5 C. Check out the work here.

Publications

Proton-exchange induced reactivity in NCM cathodes

Xingyu’s collaborative research with the Chen group, titled “Proton-Exchange Induced Reactivity in Layered Oxides for Lithium-Ion Batteries,” has been published in Nature Communications! This study addresses a critical challenge in the manufacturing, storage, transportation, processing, and recycling of LiNixCoyMn1-x-yO2 (NCM, 0 < x, y < 1), the dominant cathode material for state-of-the-art lithium-ion batteries. Through an integration of experimental and computational approaches, the team reveals how protons intercalate into the layered NCM structure, triggering Li⁺ leaching and the formation of protonated NCM. This protonation process significantly disrupts the structural integrity of the material, promoting cation rearrangement and the development of impurity phases. These effects are particularly severe in NCMs with higher nickel content. The study also demonstrates a solution-based approach to mitigate Li deficiencies in NCM materials by leveraging controlled proton concentrations and the presence of Li⁺ ions. The underlying relithiation mechanism is further elucidated through detailed materials characterization and kinetics modeling. This work provides essential insights into managing structural and compositional defects in NCM cathodes, paving the way for improved performance and stability in next-generation lithium-ion batteries. Check out this work here.

Publications

Cation Ordering in P2 Na-Ion Cathodes

Congratulations to Zishen for his co-authored paper on “Influence of Interlayer Cation Ordering on Na Transport in P2-Type Na0.67–xLiy Ni0.33–zMn0.67+zO2 for Sodium-Ion Batteries” published in JACS together with the group of Prof Claire Xiong at Boise State University! In this work, we studied the P2-type Na2/3Ni1/3Mn2/3O2 (PNNMO) cathode for Na-ion batteries. Zishen’s contribution is showing via DFT calculations that Li doping (Na2/3Li0.05Ni1/3Mn2/3O2, LFN5) promotes ABC-type interplanar Ni/ Mn ordering without disrupting the Na+/vacancy ordering and creates low-energy Li−Mn-coordinated diffusion pathways. These result are in line with those from neutron/X-ray diffraction. Quasielastic neutron scattering reveals that the Na+ diffusivity in LFN5 is enhanced by an order of magnitude over PNNMO, increasing its capacity at a high current. These results suggest that the interlayer ordering can be tuned through the control of composition, which has an equal or greater impact on Na+ diffusion than the Na+/vacancy ordering. Check out the work here.

Publications

Congrats to Ji Qi on the successful defense of his thesis!

Congratulations to Ji Qi for successfully defending his PhD thesis on Apr 12 2024. During his time in the Materials Virtual Lab, Ji has made extremely valuable contributions in the development and application of machine learning interatomic potentials (MLPs). He has applied MLPs to solid electrolytes, pushing the envelope of their application to extremely complex chemistries (7 element oxides!!!). He also developed an innovative DIRECT sampling method that enables the fitting of MLPs with much fewer / zero active learning steps. We wish him all the best in his new job at CATL. Check out the recording of his PhD thesis defense below.

Publications

Healable Sulfur Cathode for Solid-State Li-S Batteries

Repaired Sulfur Cathode Interface

Manas’ final work on “Healable and conductive sulfur iodide for solid-state Li–S batteries” is now out in Nature! This work is a collaboration between Prof Ping Liu’s group and our group. Solid-state Li–S batteries (SSLSBs) are made of low-cost and abundant materials free of supply chain concerns. In this work, we report an S9.3I molecular crystal, which shows a semiconductor-level electrical conductivity. Our group’s main contribution is showing that iodine disrupts the molecular bonding in sulfur to lower its melting point, as well as introduce new states into the band gap of sulfur. This lowered melting point enables periodical remelting of the cathode to repair interfaces. Check out this work here as well as the UCSD press release on this discovery.

Publications

DIRECT Sampling for Robust MLPs

Ji’s work on “Robust training of machine learning interatomic potentials with dimensionality reduction and stratified sampling” is now out in npj Computational Materials! Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond that accessible by ab initio methods. In this work, we present DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling as an approach to select a robust training set of structures from a large and complex configuration space. By applying DIRECT sampling on the Materials Project relaxation trajectories dataset with over one million structures and 89 elements, we develop an improved materials 3-body graph network (M3GNet) universal potential that extrapolates more reliably to unseen structures. We further show that molecular dynamics (MD) simulations with the M3GNet universal potential can be used instead of expensive ab initio MD to rapidly create a large configuration space for target systems. We combined this scheme with DIRECT sampling to develop a reliable moment tensor potential for titanium hydrides without the need for iterative augmentation of training structures. Check out this work here. If you want to use DIRECT sampling for your work, please check out our implementation available on our MAML repository on Github.

Publications

Li diffusivity at the grain boundaries

Randy’s work on “Lithium dynamics at grain boundaries of β-Li3PS4 solid electrolyte” has just been published in Energy Advances! Randy was a visiting scientist in the Materials Virtual Lab from NIMS Japan in 2021-2023. Lithium diffusivity at the grain boundaries of solid electrolytes (SEs) can strongly impact the final performance of all-solid-state Li ion batteries (SSLBs). In this study, we systematically investigate the Li ion transport in tilt and twist GBs as well as amorphous/crystal interfaces of β-Li3PS4 by performing large-scale molecular dynamics (MD) simulations with a highly accurate moment tensor interatomic potential (MTP). We find that the Li ion conductivities at the GBs and amorphous/crystal interfaces are 1–2 orders of magnitude higher than that in the bulk crystal. The Li pathway network in twist GBs and amorphous/crystal interfaces comprises persisting large Li ring sub-networks that closely resemble those found in the bulk amorphous structure, whereas more smaller and short-lived Li ring sub-networks are detected in tilt GBs and the bulk crystal. The concentration of persisting large Li ring sub-networks in the GB and amorphous/crystal interfaces is directly proportional to the degree of Li site disordering which in turn correlates with GB conductivity. Our findings provide useful insights that can […]

Publications

Compositionally complex perovskite solid electrolytes

CCPO

The Materials Virtual Lab is proud to be part of a collaborative work titled “Compositionally complex perovskite oxides: Discovering a new class of solid electrolytes with interface-enabled conductivity improvements” recently published in Cell Press Matter! This work was performed under the Materials Research Science and Engineering Center (MRSEC) at UC Irvine together with the groups of Prof Xiaoqing Pan @ UCI and Prof Jian Luo @ UCSD. Compositionally complex ceramics (CCCs), including high-entropy ceramics, offer a vast, unexplored compositional space for materials discovery. Here, we propose non-equimolar compositionally complex perovskite oxide (CCPO) solid electrolytes with improved lithium ionic conductivities beyond the limit of conventional doping. For example, we demonstrate that the ionic conductivity can be improved by >60% in (Li0.375Sr0.4375)(Ta0.375Nb0.375Zr0.125Hf0.125)O3-d. MAVRL group member, Ji Qi, developed a machine learning interatomic potential (MLIP) for this 7-component CCPO using an active learning protocol, and demonstrated this enhanced ionic conductivity can be attributed to enhanced GB diffusitivity that is related to the absence of Li depletion at GB regions, which is observed in the resistive GB of the LLTO. This work suggests new routes for discovering and tailoring CCCs for energy storage and many other applications. Check out this work here.

Publications

243rd ECS Meeting Presentation on Machine Learning for Solid State Batteries: Progress vs Hype

Prof Shyue Ping Ong gave a talk at the 243rd Electrochemical Society (ECS) Meeting in Boston on May 30 2003 on “Machine Learning for Solid State Batteries: Progress vs Hype:. Machine learning in materials science and solid-state batteries are two topics that have captured the imagination of researchers in recent years. Therefore, it is unsurprising that many researchers have attempted to apply the advances in ML to the discovery and study of materials for solid-state batteries. In this talk, Prof Ong discusses the importance of going back to fundamentals in the application of ML to materials for solid-state batteries. I will highlight areas where ML has had a transformative impact on our understanding and discovery of solid electrolytes, and what are some of the remaining challenges that remain to be surmounted.

Publications

Multi-scale investigation of MoNbTi and TaNbTi MPEAs

Hui’s swansong collaborative work on “Multi-scale investigation of short-range order and dislocation glide in MoNbTi and TaNbTi multi-principal element alloys” is now out in npj Computational Materials! This is a really exciting work that showcases an electron (DFT) to atom (machine learning interatomic potentials) to continuum (phase field dislocation dynamics) approach to the study of materials. It is a collaborative work between Hui and Lauren Fey of the group of Irene Beyerlein at UC Santa Barbara. Refractory multi-principal element alloys (RMPEAs) are promising materials for high-temperature structural applications. In this work, we performed an electron-to-atom-to-continuum study of the role of short-range ordering (SRO) on dislocation glide in the MoNbTi and TaNbTi RMPEAs. Monte carlo/molecular dynamics simulations with a moment tensor potential show that MoNbTi exhibits a much greater degree of SRO than TaNbTi and the local composition has a direct effect on the unstable stacking fault energies (USFEs). From mesoscale phase-field dislocation dynamics simulations, we find that increasing SRO leads to higher mean USFEs and stress required for dislocation glide. The gliding dislocations experience significant hardening due to pinning and depinning caused by random compositional fluctuations, with higher SRO decreasing the degree of USFE dispersion and hence, amount of hardening. […]