Arghya Bhowmik
Stanford University
H-index: 21
North America-United States
Top articles of Arghya Bhowmik
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
CURATOR: Building Robust Machine Learning Potentials for Atomistic Simulations Autonomously with Batch Active Learning | Xin Yang Martin Hoffmann Petersen Renata Sechi William Sandholt Hansen Sam Walton Norwood | 2024/2/16 | |
Unravelling degradation mechanisms and overpotential sources in aged and non-aged batteries: A non-invasive diagnosis | Journal of Energy Storage | Williams Agyei Appiah Laura Hannemose Rieger Eibar Flores Tejs Vegge Arghya Bhowmik | 2024/4/20 |
OM-DIFF: INVERSE-DESIGN OF ORGANOMETALLIC CATALYSTS WITH GUIDED EQUIVARIANT DENOISING DIFFUSION | François Cornet Bardi Benediktsson Bjarke Hastrup Mikkel N Schmidt Arghya Bhowmik | 2024/3/28 | |
Learning the density matrix, a symmetry rich encoding of the electronic density. | Bulletin of the American Physical Society | Pol Febrer Arghya Bhowmik Miguel Pruneda Alberto Garcia Peter Jorgensen | 2024/3/6 |
Sensitivity analysis methodology for battery degradation models | Electrochimica Acta | Williams Agyei Appiah Jonas Busk Tejs Vegge Arghya Bhowmik | 2023/1/20 |
Neural network ansatz for periodic wave functions and the homogeneous electron gas | Physical Review B | Max Wilson Saverio Moroni Markus Holzmann Nicholas Gao Filip Wudarski | 2023/6/21 |
CURATOR: Autonomous Batch Active-Learning Workflow for Catalysts | Xin Yang Renata Sechi Martin Hoffmann Petersen Arghya Bhowmik Heine Anton Hansen | 2023/11/3 | |
A foundation model for atomistic materials chemistry | arXiv preprint arXiv:2401.00096 | Ilyes Batatia Philipp Benner Yuan Chiang Alin M Elena Dávid P Kovács | 2023/12/29 |
Inverse-design of organometallic catalysts with guided equivariant diffusion | François Raymond J Cornet Bardi Benediktsson Bjarke Arnskjær Hastrup Arghya Bhowmik Mikkel N Schmidt | 2023 | |
Equivariant Graph-Representation-Based Actor–Critic Reinforcement Learning for Nanoparticle Design | Journal of Chemical Information and Modeling | Jonas Elsborg Arghya Bhowmik | 2023/6/5 |
Nanosecond MD of battery cathode materials with electron density description | Energy Storage Materials | Paolo Vincenzo Freiesleben de Blasio Peter Bjørn Jorgensen Juan Maria Garcia Lastra Arghya Bhowmik | 2023/11/1 |
Materials funnel 2.0–data-driven hierarchical search for exploration of vast chemical spaces | Journal of Materials Chemistry A | Raul Ortega Ochoa Bardi Benediktsson Renata Sechi Peter Bjørn Jørgensen Arghya Bhowmik | 2023 |
Genetic algorithm-based re-optimization of the Schrock catalyst for dinitrogen fixation | PeerJ physical chemistry | Magnus Strandgaard Julius Seumer Bardi Benediktsson Arghya Bhowmik Tejs Vegge | 2023/12/5 |
Accelerated Workflow for Antiperovskite‐based Solid State Electrolytes | Batteries & Supercaps | Benjamin H Sjølin Peter B Jørgensen Andrea Fedrigucci Tejs Vegge Arghya Bhowmik | 2023/6 |
Unveiling the plating-stripping mechanism in aluminum batteries with imidazolium-based electrolytes: A hierarchical model based on experiments and ab initio simulations | Chemical Engineering Journal | Williams Agyei Appiah Anna Stark Steen Lysgaard Jonas Busk Piotr Jankowski | 2023/9/15 |
Neural network potentials for accelerated metadynamics of oxygen reduction kinetics at Au–water interfaces | Chemical Science | Xin Yang Arghya Bhowmik Tejs Vegge Heine Anton Hansen | 2023 |
Phase separating electrode materials-chemical inductors? | Energy Storage Materials | Klemen Zelič Igor Mele Arghya Bhowmik Tomaž Katrašnik | 2023/2/1 |
Machine learning guided development of high-performance nano-structured nickel electrodes for alkaline water electrolysis | Applied Materials Today | Veronica Humlebæk Jensen Enzo Raffaele Moretti Jonas Busk Emil Howaldt Christiansen Sofie Marie Skov | 2023/12/1 |
Brokering between tenants for an international materials acceleration platform | Matter | Monika Vogler Jonas Busk Hamidreza Hajiyani Peter Bjørn Jørgensen Nehzat Safaei | 2023/9/6 |
Uncertainty-aware and explainable machine learning for early prediction of battery degradation trajectory | Digital Discovery | Laura Hannemose Rieger Eibar Flores Kristian Frellesen Nielsen Poul Norby Elixabete Ayerbe | 2023 |
