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Sukriti Manna

Argonne National Laboratory

United States

Research Interests

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Professors in United States Professors in Condensed Matter Physics Condensed Matter Physics professors in United States

Articles (20)

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2026

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Collaborators (7)

Sampath Gamage

Assistant Professor

University of North Carolina at Greensboro

UNITED STATES

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Pierre Darancet

Scientist

Argonne National Laboratory

UNITED STATES

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Tomojit Chowdhury

Assistant Professor

Wayne State University

UNITED STATES

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Karan Patel

University of Tennessee

UNITED STATES

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Suvo Banik

Scientist (R&D Associate)

Oak Ridge National Laboratory

UNITED STATES

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Nan Jiang

Professor

University of Chicago

UNITED STATES

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Subramanian K. R. S. Sankaranarayanan

University of Illinois at Urbana-Champaign

UNITED STATES

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Sukriti Manna

Research Interests

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Articles (20)

Symbolic ensemble learning enables discovery of fast accurate physics-based interatomic potentials

Data-driven discovery of process–structure relationships in additive manufacturing via featurization from kinetic Monte Carlo simulations and interpretable machine learning

Interface and Thermophysical Properties of R32 Refrigerant

Machine Learning an Ab-Initio Based Bond-Order Potential for Bismuthene

Strain-Modified Raman Responses in Monolayer MoS2 Nanobubbles Resolved at 5 nm

Comparison of Deterministic and Probabilistic Machine Learning Algorithms for Precise Dimensional Control and Uncertainty Quantification in Additive Manufacturing

Physically interpretable interatomic potentials via symbolic regression and reinforcement learning

Solid Lubricant Molybdenum Based MXene With Prolonged Macroscale Superlubricity

A Digital Twin for Advanced Manufacturing of Materials

Data driven insights into the characteristics of wide bandgap semiconductors in 2D materials

Development and assessment of hierarchical multi-reward reinforcement learning based potential for silicene with state-of-the-art models

Kelvin Probe Force Microscopy Imaging of Plasticity in Hydrogenated Perovskite Nickelate Multilevel Neuromorphic Devices

Machine learning enabled discovery of superhard and ultrahard carbon polymorphs

Self-Lubricating Tribo-Catalytic Activity of 2D High Entropy Alloy Nanoflakes

Active and Transfer Learning of High-Dimensional Neural Network Potentials for Transition Metals

Machine Learning a Simple Interpretable Short-Range Potential for Silica

Ab Initio-Based Bond Order Potential for Arsenene Polymorphs Developed via Hierarchical Reinforcement Learning

Development of a Machine Learning Potential to Study the Structure and Thermodynamics of Nickel Nanoclusters

Evaluating generalized feature importance via performance assessment of machine learning models for predicting elastic properties of materials

Infrared Nanoimaging of Hydrogenated Perovskite Nickelate Memristive Devices

Collaborators (7)

Sampath Gamage

Pierre Darancet

Tomojit Chowdhury

Karan Patel

Suvo Banik

Nan Jiang

Subramanian K. R. S. Sankaranarayanan

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