| Infrared spectroscopy data-and physics-driven machine learning for characterizing surface microstructure of complex materials JL Lansford, DG Vlachos Nature communications 11 (1), 1513, 2020 | 97 | 2020 |
| Optimization of the facet structure of transition-metal catalysts applied to the oxygen reduction reaction M Núñez, JL Lansford, DG Vlachos Nature chemistry 11 (5), 449-456, 2019 | 65 | 2019 |
| Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences J Feng, JL Lansford, MA Katsoulakis, DG Vlachos Science advances 6 (42), eabc3204, 2020 | 33 | 2020 |
| Scaling relationships and theory for vibrational frequencies of adsorbates on transition metal surfaces JL Lansford, AV Mironenko, DG Vlachos Nature communications 8 (1), 1842, 2017 | 26 | 2017 |
| Building chemical property models for energetic materials from small datasets using a transfer learning approach JL Lansford, BC Barnes, BM Rice, KF Jensen Journal of Chemical Information and Modeling 62 (22), 5397-5410, 2022 | 19 | 2022 |
| Spectroscopic probe molecule selection using quantum theory, first-principles calculations, and machine learning JL Lansford, DG Vlachos ACS nano 14 (12), 17295-17307, 2020 | 14 | 2020 |
| Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model J Feng, J Lansford, A Mironenko, DB Pourkargar, DG Vlachos, ... AIP Advances 8 (3), 2018 | 9 | 2018 |
| Physics‐informed Transfer Learning for Out‐of‐sample Vapor Pressure Predictions J Lansford, K Jensen, B Barnes Propellants, Explosives, Pyrotechnics, 2023 | 7 | 2023 |
| Prediction of Transition-State Scaling Relationships and Universal Transition-State Vibrational and Entropic Correlations for Dehydrogenations SJ Kurdziel, JL Lansford, DG Vlachos The Journal of Physical Chemistry C 125 (36), 19780-19790, 2021 | 4 | 2021 |
| Scaling of Transition State Vibrational Frequencies and Application of d-Band Theory to the Brønsted–Evans–Polanyi Relationship on Surfaces JL Lansford, SJ Kurdziel, DG Vlachos The Journal of Physical Chemistry C 125 (13), 7119-7129, 2021 | 4 | 2021 |
| Out-of-sample Transition Temperature Predictions via Physics-informed Transfer Learning J Lansford, B Barnes, K Jensen Bulletin of the American Physical Society 68, 2023 | | 2023 |
| Designing Dynamic Materials for Selective Reactions at Ultra-Low Substrate Concentrations, Enabling Direct Air Carbon Capture and Utilization J Lansford 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Data-driven Chemical Property Models for Energetic Materials using Transfer Learning J Lansford, B Barnes, B Rice, K Jensen APS Shock Compression of Condensed Matter Meeting Abstracts, P03. 005, 2022 | | 2022 |
| Building Chemical Property Models for Energetic Materials from Small Datasets using a Transfer Learning Approach B Barnes, J Lansford, B Rice, K Jensen APS March Meeting Abstracts 2022, Z32. 008, 2022 | | 2022 |
| Universal Vibrational and Entropic Scaling Relationships for Dehydrogenations S Kurdziel, J Lansford, D Vlachos 2021 AIChE Annual Meeting, 2021 | | 2021 |
| Vibrational Scaling Relationships for Transition States S Kurdziel, J Lansford, D Vlachos 2020 Virtual AIChE Annual Meeting, 2020 | | 2020 |
| Enabling predictive science for catalysis under uncertainty JL Lansford University of Delaware, 2020 | | 2020 |
| Computational Modeling of Operando Infrared Spectroscopy for Site-Specific Catalyst Characterization J Lansford, D Vlachos 2019 AIChE Annual Meeting, 2019 | | 2019 |
| Coupling Experimental Kinetics and Thermodynamic Modeling with IR Spectroscopy and Machine Learning for Fundamental Studies and Fast Product Quantification NR Quiroz, J Lansford, G Tsilomelekis, D Vlachos 2019 AIChE Annual Meeting, 2019 | | 2019 |
| Catalyst Site Characterization from Complex Infrared Spectroscopy J Lansford, D Vlachos 2019 North American Catalysis Society Meeting, 2019 | | 2019 |
Dionisios G. VlachosUniversity of DelawareVerified email at udel.edu
