Bulletin of the American Physical Society
2024 APS March Meeting
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session F64: Advances in Li-ion and Li-S Energy Storage |
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Sponsoring Units: GERA FIAP Chair: Santidan Biswas, University of Pittsburgh Room: 211AB |
Tuesday, March 5, 2024 8:00AM - 8:12AM |
F64.00001: Probing oxygen stability in NMC battery materials through spectroscopy, microscopy, modeling, and AI/ML Yiming Chen, Haili Jia, Chaitanya Kolluru, Guiliang Xu, Chengjun Sun, Wanli Yang, Maria K Chan One of the significant mode of failure, but also an avenue for potential additional energy capacity, for lithium ion battery cathode materials is oxygen reactivity. Previously, we explored the use of computational and experimental x-ray absorption spectroscopy to determine the oxygen activity in lithium- iron [1] and iridium [2] oxide compounds. The issue is particularly important for the leading Ni-Mn-Co (NMC) cathode materials. In this talk, we will describe the use of density functional theory (DFT) together with microscopy and spectroscopy, and machine learning [3] and computer vision based microscopy tool Ingrained [4], to determine oxygen structure and stability in NMC materials and grain boundaries [5]. |
Tuesday, March 5, 2024 8:12AM - 8:24AM |
F64.00002: Electrochemical Activity of Oxygen in Li-ion Battery Cathodes from X-ray Spectroscopy and Modeling Eder G Lomeli, Sean Hsu, Joshua J Kas, John Vinson, John J Rehr, Wanli Yang, Brian Moritz, Thomas P Devereaux As demand for better performance in energy storage increases, a clear understanding of the charge compensating mechanism in Li-ion battery cathodes is essential for developing next generation battery chemistries and materials. X-ray core level spectroscopies, e.g. x-ray absorption spectroscopy (XAS) and resonant inelastic x-ray scattering (RIXS), allow for experimental measurement of the electronic structure of battery materials before and after charge, providing the clearest physical picture of electrochemical device operation. |
Tuesday, March 5, 2024 8:24AM - 8:36AM |
F64.00003: The Energetic Landscape and Influence of Polarization for Site Swapping in Battery Cathode Materials Emma F Cuddy, Eder G Lomeli, Brian Moritz, Thomas P Devereaux Improving energy storage technology to have rechargeable, high capacity, high energy density batteries is essential to transitioning towards renewable energy and vehicle electrification. One of the primary issues in lithium ion batteries is irreversible changes to the lattice structure of the cathode during charging and discharging cycles. These larger structural changes are often precipitated by site swapping between lithium and transition metal ions. While these structural changes are widely observed, the energetic landscape and mechanisms controlling the initial deviations from pristine structure are not yet understood. We have used computational methods including DFT and Madelung energy analysis to look at the atomic scale energetics and polarization effects of defects in a series of lithium iron oxide cathode materials to determine the mechanisms controlling structural stability within cathode materials. |
Tuesday, March 5, 2024 8:36AM - 8:48AM |
F64.00004: Understanding the redox sequence of VFe2Ox and the role of dopants (Al, Zn, Zr) in shifting capacity and cycling profiles Michelle D Johannes, Noam Bernstein, Michael Swift, Ryan DeBlock, Jeffrey Long, Hunter Ford, Rachel Ashmore, Debra R Rolison Vanadium ferrite (VFe2Ox) is a deliberately defective spinel system that can incorporate substantial Li+ and exhibits a high charge-discharge rate, particularly when structured as a nanoscale aerogel. Zr, Zn and Al, can readily be made to enter the structure substitutionally and have strong, but differing effects on the capacity of the material. The earth abundant, cost-effective constituent elements give this class of materials strong potential as future Li ion battery cathodes, but optimizing the stoichiometry for maximum capacity and stability will require understanding the redox sequence and role of intentional dopants. |
Tuesday, March 5, 2024 8:48AM - 9:00AM |
F64.00005: Understanding the redox mechanism of lithium thiophosphates as high-voltage cathode materials Yi-Ting Cheng, Fujii Yuta, Yu Nomata, Madhulika Mazumder, Nataly C Rosero-Navarro, Aichi Yamashita, Yoshikazu Mizuguchi, Chikako Moriyoshi, Takao Mitsudome, Kiyoharu Tadanaga, Akira Miura, Christopher Bartel High-voltage cathode materials are essential for the development of energy-dense batteries. In this work, we synthesized lithium metal thiophosphates, Li2MP2S6 (M = Mn, Fe or Co), and discovered Li2Mn0.902P2S6 as a new compound. Electrochemical measurements demonstrate Li+ extraction from and reinsertion in Li2FeP2S6 and Li2MnP2S6 at ~3 V (significantly higher than other sulfide-based cathodes) with capacities of 40 and 70 mAh/g, respectively. Surprisingly, although Li+ was extracted from Li2FeP2S6 and Li2MnP2S6 at similar voltages, the redox mechanism appears significantly different between the two cations. Density functional theory calculations show that for M = Fe, it is the non-bonding Fe states that account for charge compensation of the first Li+ from Li2FeP2S6 (traditional transition metal redox). In contrast, for M = Mn, antibonding Mn-S and S-S states are oxidized and accompanied by significant rehybridization of Mn and S states during charging. Our findings shed insight into the interplay of cationic and anionic redox in this interesting class of potential cathode materials. |
Tuesday, March 5, 2024 9:00AM - 9:12AM |
F64.00006: Polyvinylidene fluoride (PVDF) - Trimethyl Aluminum (TMA) Chemistry: First-principles Investigation and Experimental Insights M.D. Hashan C Peiris, Heran Huang, Hui Zhou, Hao Liu The preparation of cathode electrodes has adhered to conventional methods, with limited exploration of the potential contributions of a remarkably robust yet relatively obscure reagent, trimethylaluminum (TMA), during atomic layer deposition (ALD). While significant research has focused on the interaction between TMA and cathode material particles, sparse attention has been devoted to investigating the interactions between TMA and polyvinylidene fluoride (PVDF), the predominant binder employed during cathode electrode preparation. This study presents a computational and experimental analysis of the degradation reaction observed between TMA and polyvinylidene fluoride (PVDF) using X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) investigations. An exothermic reaction mechanism was identified for the interaction of TMA with PVDF, yielding CH4, dimethyl aluminum fluoride, and non-saturated carbons at the reaction site in the PVDF backbone. Our computational findings align well with XPS results, offering a robust theoretical-experimental correlation. Additionally, a secondary, slightly endothermic reaction pathway suggests the formation of hydrogen fluoride (HF) facilitated by the dimeric form of TMA, where TMA serves as an accelerant. The newfound chemistry involving TMA and PVDF could have substantial implications for optimizing industrial processes and developing novel materials, especially in energy storage and cleaner production technologies. |
Tuesday, March 5, 2024 9:12AM - 9:24AM |
F64.00007: Improving Solvation Energy Predictions in VASPsol using Machine Learning Eric C Fonseca, Richard G Hennig, Sean Florez Density functional theory (DFT) can accurately predict material properties and reaction barriers. However, due to high computational costs, DFT is often limited to small system sizes. This is especially true in liquid-phase calculations, where free-energy barriers can vary dramatically compared to the gaseous state. To approximate the solvation effect, computational chemists use continuum models to mimic the countless number of solvent molecules in these systems. Continuum models attempt to capture the effect of the solvent on solute molecules and surfaces while dramatically reducing the computational cost. VASPsol uses a polarizable continuum model within VASP, a plane-wave DFT code. We trained machine learning models on VASPsol solvation energies and the accompanying prediction errors relative to experimental data for 450 molecules solvated in water, sourced from the Minnesota Solvation Database. Inputs for each molecule were constructed using the COSMO-SAC descriptors of the solute and the COSMO-SAC predicted Infinite Dilution Activity Coefficient (IDAC). We conduct two separate tasks. 1. Using neural networks to improve the solvation energy prediction of VASPsol and 2. Using the VASPsol solvation energy error as the target to examine features contributing to decreased VASPsol accuracy. Through permutation feature importance analysis, we identified positively charged surface segments as key contributors to errors in VASPsol energy predictions.This research provides insights into the limitations of VASPsol and opens avenues for its improvement, promising better accuracy in DFT simulations in solvent environments. |
Tuesday, March 5, 2024 9:24AM - 9:36AM |
F64.00008: Machine learning interatomic potentials for ionic liquids and battery solvents Zachary A Goodwin, Nicola Molinari, Julia H Yang, Albert Musaelian, Simon L Batzner, Boris Kozinsky We develop machine learning force fields (MLFFs), based on the equivariant graph neural networks with NequIP/Allegro [1,2], for representative ionic liquids and conventional battery solvents. As the intermolecular interactions are subtle, and the dynamics of these electrolytes/solvents are quite slow, training a potential for these systems is not always straightforward. We develop a protocol for training MLFFs for complex, multicomponent solvents and electrolytes, which efficiently samples representative structures, to collect diverse, uncorrelated molecular configurations for training. This approach is shown to yield reliable simulations in the NVT ensemble, but not always in the NPT ensemble, where we find densities significantly lower than expected from our DFT calculations, similar to previous work. We develop an approach to remedy this issue, and test it on a number of electrolytes/solvents to ensure it is a robust method. In addition, we study the question of model transferability, the effect of long-range interactions and uncertainty of the model. |
Tuesday, March 5, 2024 9:36AM - 9:48AM |
F64.00009: Identification of the key parameters for the organic electrolytes selection for lithium-sulfur batteries Mihir Parekh, Nawraj Sapkota, Brooke Henry, Matthew Everette, Ming Hu, Apparao M Rao, Christopher Sutton A key component for long-lasting next-generation lithium-sulfur batteries (LSBs) are electrolytes that facilitate a stable bilateral solid-electrolyte interface (SEI) simultaneously on both the cathode and anode. Other typical factors used for electrolyte selection include dielectric constant (ε), viscosity, dipole moment, donor number, and orbital energy levels. To simplify electrolyte selection, we developed a machine learning (ML) model (based on just 27 samples) whose predicted capacity retention generally agreed well with the experimental data. Additionally, it was found to correlate the most with the ε (R2 = 0.71). High ε also implied a low |%drop| in capacity after rate testing. Therefore, ML was used to predict |%drop| for 51 batteries, which were also prepared and experimentally tested. Nine electrolytes with ε > 35, showed an average |%drop| of 0.8%, well below the average |%drop| of 5.29 % for the entire dataset. However, 3 other electrolytes with ε > 35 (based on diglyme) exhibited a |%drop| > 1.4%. The presence of large diglyme molecules in the solvation shell (obtained using classical molecular dynamics) leads to reduced diffusivity and a high |%drop|. Thus ε > 35 and the absence of large molecules in the solvation shell are good criteria for LSB electrolyte selection. Additionally, ML predicted |%drop| agreed well with experimental data (mean absolute error of < 2.59%). |
Tuesday, March 5, 2024 9:48AM - 10:00AM |
F64.00010: Voltage Profile Calculation of Sulfur Batteries with ab initio Molecular Dynamics Sihe Chen, M.D. Hashan C Peiris, Manuel Smeu Energy storage has become one of the most important topics in the field of green energy production. With the rise in renewable energy generation, the demand for high-energy-density batteries is also increasing to match storage needs. Conventional intercalation-based lithium-ion batteries are reaching a performance ceiling in terms of energy density and face problems with dendritic plating behavior and scarcity of source materials. Unlike intercalation-based batteries, conversion batteries release energy by breaking chemical bonds on the cathode side, rather than inserting ions into a crystalline cathode. Sulfur, as one of the promising cathode materials, has benefits such as low toxicity and cost relative to other cathode materials and large natural abundance. This material consists of multiple eight-membered sulfur rings that are held together by van der Waals forces. By using density functional theory, we modeled reactions for Li-S and Ca-S batteries, where sulfur rings are broken forming various and () polysulfides. We are specifically interested in calculating the voltage profile, reaction mechanisms, structural change upon charge, and discharge process. We demonstrate the importance of including the electrolyte in the voltage simulations, which allows for the proper treatment of the polysulfide species. A voltage profile is constructed for both calcium-sulfur and lithium-sulfur system using one common electrolyte. |
Tuesday, March 5, 2024 10:00AM - 10:12AM |
F64.00011: Novel Polymer Sulfurization for Enhanced Electrochemical Performance in Lithium-Sulfur Cathodes Alan Rowland, Nawraj Sapkota, Sajib Kumar Mohonta, Ramakrishna Podila Sulfurized Polyacrylonitrile, SPAN, shows high electrochemical stability in lithium-sulfur batteries. Our prior work on SPAN indicated the unique role of nitrogen in modifying the quantum capacitance of an electrode. Here, we present a comprehensive investigation of the electrochemical performance of sulfurized polymers, including nylon, polystyrene, polyaniline, and polypropylene. The different sulfurized polymers provide insight into controlling the nitrogen:sulfur ratios while keeping the synthesis method consistent. This talk will discuss the challenges involved in preparing stable sulfurized polymer electrodes with varying nitrogen to sulfur ratios and present the effects of synthesis procedures on the final electrochemical performance. By using a range of analytical techniques, including Scanning Electron Microscopy (SEM), Electrochemical Impedance Spectroscopy (EIS), Cyclic Voltammetry (CV), Charge-Discharge cycling, x-ray photoemission (XPS), we gained deeper insights into the mechanisms in sulfurized electrodes. In combining the insights gained from the analytical techniques, the synthesis methods, and the electrochemical performance across the polymers, we present a conclusive idea of the importance of quantum capacitance in energy storage. |
Tuesday, March 5, 2024 10:12AM - 10:24AM |
F64.00012: Additively Manufactured Battery Thermal Management Systems (B-TMS): Experimental Investigations and Finite-Element Modeling Shinto Francis, Sajib Kumar Mohonta, POOJA PUNEET, Ramakrishna Podila A highly efficient Battery Thermal Management System (B-TMS) in an electric vehicle (EV) achieves a dual-purpose: it simultaneously reduces both the peak average temperature (Tmax) of the battery pack and minimizes temperature variations (ΔT) among individual cells within the pack. This study introduces a comprehensive exploration combining experimental investigations and computational modeling of B-TMS solutions that incorporate advanced two-dimensional materials such as graphene and boron nitride within polymer composites. Our research focuses on evaluating the performance of additively manufactured B-TMS systems, including poly (lactic acid) (PLA), graphene-PLA, graphite-PLA, and BN-PLA. Leveraging empirically derived thermal data, we employ finite element analysis of transient heat conduction to simulate heat distribution in various composite structures. We present the impact of 2D material concentration, material type, and microstructure on Tmax and ΔT, offering valuable insights into their roles within the system. |
Tuesday, March 5, 2024 10:24AM - 10:36AM |
F64.00013: Redox density of states and quantum capacitance in sulfurized polyacrylonitrile Nawraj Sapkota, Alan Rowland, Ramakrishna Podila
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