J. Lansford

发表

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

Jinchao Feng, D. Vlachos, M. Katsoulakis, 2018 .

Optimization of the facet structure of transition-metal catalysts applied to the oxygen reduction reaction

D. Vlachos, M. Núñez, J. Lansford, 2019, Nature Chemistry.

Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials

D. Vlachos, J. Lansford, 2020, Nature Communications.

Building Chemical Property Models for Energetic Materials from Small Datasets Using a Transfer Learning Approach

Brian C. Barnes, K. Jensen, B. Rice, 2022, J. Chem. Inf. Model..

Spectroscopic Probe Molecule Selection Using Quantum Theory, First-Principles Calculations, and Machine Learning.

D. Vlachos, J. L. Lansford, J. Lansford, 2020, ACS nano.

Scaling relationships and theory for vibrational frequencies of adsorbates on transition metal surfaces

D. Vlachos, A. V. Mironenko, J. Lansford, 2017, Nature Communications.

Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences

Jinchao Feng, D. Vlachos, M. Katsoulakis, 2020, Science Advances.

Prediction of Transition-State Scaling Relationships and Universal Transition-State Vibrational and Entropic Correlations for Dehydrogenations

D. Vlachos, Sophia J. Kurdziel, J. Lansford, 2021, The Journal of Physical Chemistry C.

Physics‐informed Transfer Learning for Out‐of‐sample Vapor Pressure Predictions

K. Jensen, Brian D. Barnes, J. Lansford, 2023, Propellants, explosives, pyrotechnics.

Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials

D. Vlachos, J. L. Lansford, J. Lansford, 2020, Nature Communications.