JH
Jason Hattrick-Simpers
cond-mat.mtrl-scics.LGphysics.chem-phphysics.data-ancs.AIcs.CEcs.CLeess.IVEngineeringMaterials science
On Valency
published · living versionsW_8nmtcys9·v1 · currentpublished
Accelerating Electrochemical Impedance Spectroscopy Measurements by Reducing Reliance on Noisy Low-Frequency Data
with Qiuyu Shi, Naohiro Fujinuma, Yonatan Kurniawan, Runze Zhang +2
1 version
Preprints & journals
71 papers in the corpus · 2007–2026AutoRASOR: Autonomous Rapid Scanning Electron Microscope Operator2609.22411v1 · Kevin Zhang, Mohammad Taha, Rafael Espinosa Castaneda et al.2026 · 0 citationsarXiv
Increased Support Layer Hydraulic Resistance Partially Explains Permeability Loss in High-Pressure Reverse Osmosis.42485517 · Zeinali Danalou, Sima, Wang, Hongchen, Sarker, Niher R et al.2026 · 0 citationsEnvironmental science & technology. 2026;60(30):21332-21344
Accelerating Electrochemical Impedance Spectroscopy Measurements by Reducing Reliance on Noisy Low-Frequency Data2607.19307v1 · Qiuyu Shi, Naohiro Fujinuma, Yonatan Kurniawan et al.2026 · 0 citationsarXivon Valency
Physics-informed time-series forecasting of perovskite photoluminescence stability2606.13414v1 · Alexander Wieczorek, Manuel Kober-Czerny, F'abio Lopes et al.2026 · 0 citationsarXiv
Entropy-Enabled Stabilization and Activity Enhancement of Ruthenium Oxides for Acidic Oxygen Evolution.42265827 · Yao, Xue, Huang, Linke, Liu, Yutong et al.2026 · 3 citationsJournal of the American Chemical Society. 2026;148(24):25249-25257
Diversity-Aware Active Learning Builds Materials Datasets for Current and Future Objectives2605.05104v2 · Rafael Espinosa Castaneda, Ashley Dale, Hongchen Wang et al.2026 · 0 citationsarXiv
Building a physics-aware AI ecosystem for solid-state hydrogen storage materials2605.03081v2 · Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu et al.2026 · 2 citationsarXiv
AutoREC: A reinforcement learning platform for equivalent circuit model generation2604.27266v3 · Ali Jaberi, Yonatan Kurniawan, Robert Black et al.2026 · 0 citationsarXiv
Autonomous sampling and SHAP interpretation of deposition-rates in bipolar HiPIMS.42052246 · Wieczorek, Alexander, Rodkey, Nathan, Sommerhäuser, Jan et al.2026 · 0 citationsDigital discovery. 2026;5(5):2221-2231
On the Need for Autonomous Science Instruments: A Call to Action10.26434/chemrxiv.10001836/v1 · Milad Abolhasani, Mahshid Ahmadi, Sterling Baird et al.2026 · 2 citationsChemRxiv
Materials Acceleration Platform for Electrochemistry: a Platform for Autonomous Electrochemistry.42718626 · Persaud, Daniel, Werezak, Mike, Xu, Mark et al.2026 · 0 citationsNpj Materials degradation. 2026;10(1):111
Active learning for the accelerated discovery of complex concentrated NiCoCr alloys in additive manufacturing.42889146 · Talbot, Ajay, Dash, Soumya S, Li, Jialu et al.2026 · 1 citationNPJ advanced manufacturing. 2026;3(1):36
Building Trustworthy AI for Materials Discovery: From Autonomous Laboratories to Z-scores2512.01080v1 · Benhour Amirian, Ashley S. Dale, Sergei Kalinin et al.2025 · 0 citationsarXiv
High-throughput validation of phase formability and simulation accuracy of Cantor alloys2511.19335v1 · Changjun Cheng, Daniel Persaud, Kangming Li et al.2025 · 2 citationsarXiv
Training-Free Active Learning Framework in Materials Science with Large Language Models2511.19730v2 · Hongchen Wang, Rafael Espinosa Castaneda, Jay R. Werber et al.2025 · 4 citationsarXiv
Assessment of different loss functions for fitting equivalent circuit models to electrochemical impedance spectroscopy data2510.09662v1 · Ali Jaberi, Amin Sadeghi, Runze Zhang et al.2025 · 4 citationsarXiv
Developing and Validating a High-Throughput Robotic System for the Accelerated Development of Porous Membranes2508.10973v1 · Hongchen Wang, Sima Zeinali Danalou, Jiahao Zhu et al.2025 · 3 citationsarXiv
Digital generation of the 3-D pore architecture of isotropic membranes using 2-D cross-sectional scanning electron microscopy images2508.06664v1 · Sima Zeinali Danalou, Hooman Chamani, Arash Rabbani et al.2025 · 1 citationarXiv
Human-AI Synergy in Adaptive Active Learning for Continuous Lithium Carbonate Crystallization Optimization2507.19316v1 · Shayan S. Mousavi Masouleh, Corey A. Sanz, Ryan P. Jansonius et al.2025 · 2 citationsarXiv
Exploring the Limitations of kNN Noisy Feature Detection and Recovery for Self-Driving Labs2507.16833v2 · Qiuyu Shi, Kangming Li, Yao Fehlis et al.2025 · 0 citationsarXiv
Kernel Learning Assisted Synthesis Condition Exploration for Ternary Spinel2503.19637v1 · Yutong Liu, Mehrad Ansari, Robert Black et al.2025 · 1 citationarXiv
Open Catalyst Experiments 2024 (OCx24): Bridging Experiments and Computational Models2411.11783v1 · Jehad Abed, Jiheon Kim, Muhammed Shuaibi et al.2024 · 19 citationsarXiv
LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction2411.00177v3 · Andre Niyongabo Rubungo, Kangming Li, Jason Hattrick-Simpers et al.2024 · 25 citations2025 Mach. Learn.: Sci. Technol. 6 020501
Evaluating the Performance and Robustness of LLMs in Materials Science Q&A and Property Predictions2409.14572v2 · Hongchen Wang, Kangming Li, Scott Ramsay et al.2024 · 16 citationsarXiv
An Assessment of Commonly Used Equivalent Circuit Models for Corrosion Analysis: A Bayesian Approach to Electrochemical Impedance Spectroscopy2407.20297v1 · Runze Zhang, Debashish Sur, Kangming Li et al.2024 · 0 citationsarXiv
High-Tc superconductor candidates proposed by machine learning2406.14524v2 · Siwoo Lee, Jason Hattrick-Simpers, Young-June Kim et al.2024 · 1 citationarXiv
Probing out-of-distribution generalization in machine learning for materials2406.06489v1 · Kangming Li, Andre Niyongabo Rubungo, Xiangyun Lei et al.2024 · 84 citationsCommun Mater 6, 9 (2025)
Efficient first principles based modeling via machine learning: from simple representations to high entropy materials2403.15579v1 · Kangming Li, Kamal Choudhary, Brian DeCost et al.2024 · 24 citationsJ. Mater. Chem. A, 2024,12, 12412-12422
Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations2402.16190v2 · Jiahui Zhang, Runbo Jiang, Kangming Li et al.2024 · 13 citationsInternational Journal of Heat and Mass Transfer 250 (2025): 127279
Roadmap on Data-Centric Materials Science10.26434/chemrxiv-2024-m9sk0-v4 · Matthias Scheffler, Stefan Bauer, Peter Benner et al.2024 · 2 citationsChemRxiv
Artificial Intelligence-Enabled Optimization of Battery-Grade Lithium Carbonate Production2402.07000v2 · S. Shayan Mousavi Masouleh, Corey A. Sanz, Ryan P. Jansonius et al.2024 · 4 citationsarXiv
Roadmap on Data-Centric Materials Science2402.10932v3 · Stefan Bauer, Peter Benner, Tristan Bereau et al.2024 · 33 citationsarXiv
Publisher Correction: Exploiting redundancy in large materials datasets for efficient machine learning with less data.38177139 · Li, Kangming, Persaud, Daniel, Choudhary, Kamal et al.2024 · 0 citationsNature communications. 2024;15(1):284
Exploiting redundancy in large materials datasets for efficient machine learning with less data.37949845 · Li, Kangming, Persaud, Daniel, Choudhary, Kamal et al.2024 · 122 citationsNature communications. 2023;14(1):7283
Reproducibility in Computational Materials Science: Lessons from 'A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials'2310.07044v1 · Daniel Persaud, Logan Ward, Jason Hattrick-Simpers2023 · 26 citationsarXiv
Multi-principal element alloy discovery using directed energy deposition and machine learning2310.04021v1 · Phalgun Nelaturu, Jason R. Hattrick-Simpers, Michael Moorehead et al.2023 · 35 citationsarXiv
JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods2306.11688v2 · Kamal Choudhary, Daniel Wines, Kangming Li et al.2023 · 66 citationsarXiv
AutoEIS: automated Bayesian model selection and analysis for electrochemical impedance spectroscopy2305.04841v2 · Runze Zhang, Robert Black, Debashish Sur et al.2023 · 1 citationarXiv
Why is EXAFS analysis for multicomponent metals so hard? Challenges and opportunities for measuring ordering in complex concentrated alloys using x-ray absorption spectroscopy2303.09539v2 · Howie Joress, Bruce Ravel, Elaf Anber et al.2023 · 41 citationsarXiv
A High Throughput Aqueous Passivation Testing Methodology for Compositionally Complex Alloys using Scanning Droplet Cell2302.09804v4 · Debashish Sur, Howie Joress, Jason Hattrick-Simpers et al.2023 · 19 citationsJournal of The Electrochemical Society (2023) Volume 170 Number 081507
An experimental high-throughput to high-fidelity study towards discovering Al-Cr containing corrosion-resistant compositionally complex alloys2302.07988v2 · Debashish Sur, Emily F. Holcombe, William H. Blades et al.2023 · 26 citationsHigh Entropy Alloys and Materials, Nov 2023
Rapid Reconstruction of 3-D Membrane Pore Structure Using a Single 2-D Micrograph2301.10601v1 · Hooman Chamani, Arash Rabbani, Kaitlyn P. Russell et al.2023 · 0 citationsarXiv
High-Throughput Electrochemistry to Study Materials Degradation in Extreme Environments.36419231 · Wang, Yafei, Goh, Bonita, Moorehead, Michael et al.2022 · 11 citationsAnalytical chemistry. 2022;94(48):16528-16537
A critical examination of robustness and generalizability of machine learning prediction of materials properties2210.13597v1 · Kangming Li, Brian DeCost, Kamal Choudhary et al.2022 · 148 citationsnpj Comput Mater 9, 55 (2023)
Integrated High-Throughput and Machine Learning Methods to Accelerate Discovery of Molten Salt Corrosion-Resistant Alloys.35524640 · Wang, Yafei, Goh, Bonita, Nelaturu, Phalgun et al.2022 · 56 citationsAdvanced science (Weinheim, Baden-Wurttemberg, Germany). 2022;9(20):e2200370
Development of an automated millifluidic platform and data-analysis pipeline for rapid electrochemical corrosion measurements: a pH study on Zn-Ni2204.06094v1 · Howie Joress, Brian DeCost, Najlaa Hassan et al.2022 · 19 citationsarXiv
Towards automated design of corrosion resistant alloy coatings with an autonomous scanning droplet cell2203.17049v1 · Brian DeCost, Howie Joress, Suchismita Sarker et al.2022 · 18 citationsarXiv
Reflections on the future of machine learning for materials research2112.09764v1 · Naohiro Fujinuma, Brian L. DeCost, Jason Hattrick-Simpers et al.2021 · 0 citationsarXiv
Aggressively optimizing validation statistics can degrade interpretability of data-driven materials models.34364331 · Lei, Katherine, Joress, Howie, Persson, Nils et al.2021 · 19 citationsThe Journal of chemical physics. 2021;155(5):054105
Accelerated Discovery of Molten Salt Corrosion-resistant Alloy by High-throughput Experimental and Modeling Methods Coupled to Data Analytics2104.10235v1 · Yafei Wang, Bonita Goh, Phalgun Nelaturu et al.2021 · 3 citationsarXiv
Career total: 222 works. 71 are in this corpus.Showing the 50 most recent.
Profile built from the corpus for this byline.
Author records are still filling in while the Hub is in alpha. If this is your page, you'll be able to claim it soon. Spot a mistake? Tell us.