SA
Siddarth K. Achar
machine learning2-D materialsamorphous chalcogenide alloyscharge transfercore–shell materialscross-point memoryDeep Learningdensity functional theoryelectron densityinterface interdiffusion
On Valency
published · living versionsW_qspcx4nn·v2 · currentpublished
Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potential
with Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal, Siva Dasetty +8
2 versions
Preprints & journals
11 papers in the corpus · 2022–2026Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potential2609.09293v2 · Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal et al.2026 · 0 citationsarXivon Valency
Computational Design of Functionalized Cyclodextrin Probes for Sensitive and Selective PFAS Detection10.26434/chemrxiv.15004563/v1 · Siddarth K. Achar, Srusti Donapati, Marco Piazzi et al.2026 · 0 citationsChemRxiv
Proton Transport on Graphamine: A Deep-Learning Potential Study.41341881 · Ananthabhotla, Lakshmi Y, Achar, Siddarth K, Johnson, J Karl2025 · 0 citationsThe journal of physical chemistry. C, Nanomaterials and interfaces. 2025;129(47):20880-20888
Reactive Active Learning: An Efficient Approach for Training Machine Learning Interatomic Potentials for Reacting Systems.40899594 · Achar, Siddarth K, Shukla, Priyanka B, Mhatre, Chinmay V et al.2025 · 8 citationsJournal of chemical theory and computation. 2025;21(18):8889-8906
Small Data Machine Learning Approaches in Molecular and Materials Science.39719887 · Achar, Siddarth K, Keith, John A2024 · 29 citationsChemical reviews. 2024;124(24):13571-13573
Leveraging Ligand Steric Demand to Control Ligand Exchange and Domain Composition in Stratified Metal-Organic Frameworks.39046732 · He, Yiwen, De Souza, Mattheus, Luo, Tian-Yi et al.2024 · 4 citationsAngewandte Chemie (International ed. in English). 2024;63(42):e202409150
Machine Learning Electron Density Prediction Using Weighted Smooth Overlap of Atomic Positions.37368284 · Achar, Siddarth K, Bernasconi, Leonardo, Johnson, J Karl2023 · 19 citationsNanomaterials (Basel, Switzerland). 2023;13(12)
In Silico Demonstration of Fast Anhydrous Proton Conduction on Graphanol.37192530 · Achar, Siddarth K, Bernasconi, Leonardo, DeMaio, Ruby I et al.2023 · 9 citationsACS applied materials & interfaces. 2023;15(21):25873-25883
Deep-Learning Potentials for Proton Transport in Double-Sided Graphanol10.26434/chemrxiv-2023-zchh5 · Siddarth Achar, Leonardo Bernasconi, Juan Alvarez et al.2023 · 6 citationsChemRxiv
Using Machine Learning Potentials to Explore Interdiffusion at Metal-Chalcogenide Interfaces.36515688 · Achar, Siddarth K, Schneider, Julian, Stewart, Derek A2023 · 18 citationsACS applied materials & interfaces. 2022;14(51):56963-56974
Combined Deep Learning and Classical Potential Approach for Modeling Diffusion in UiO-66.35653218 · Achar, Siddarth K, Wardzala, Jacob J, Bernasconi, Leonardo et al.2022 · 56 citationsJournal of chemical theory and computation. 2022;18(6):3593-3606
Career total: 19 works. 11 are in this corpus.
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