Saved in:
| Main Authors: | Hashmi, Israrul H, Karmakar, Rahul, Maniteja, Marripelli, Ayush, Kumar, Patra, Tarak K. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.17357 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Extrapolative ML Models for Copolymers
by: Hashmi, Israrul H., et al.
Published: (2024)
by: Hashmi, Israrul H., et al.
Published: (2024)
Nanobubble size controls gas hydrate nucleation in supercooled water
by: Kanaujiya, Ramkhelavan, et al.
Published: (2025)
by: Kanaujiya, Ramkhelavan, et al.
Published: (2025)
Gas Mixture Diffusion and Distribution in the Porous ZIF-90 Framework
by: Yacham, Ashok, et al.
Published: (2025)
by: Yacham, Ashok, et al.
Published: (2025)
QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space
by: Crespo, Pablo Martínez, et al.
Published: (2026)
by: Crespo, Pablo Martínez, et al.
Published: (2026)
Inverse Design of Inorganic Compounds with Generative AI
by: Kneiding, Hannes, et al.
Published: (2026)
by: Kneiding, Hannes, et al.
Published: (2026)
Molecular Mechanisms of Polymer Crosslinking via Thermal Activation
by: Akhtar, Javed, et al.
Published: (2025)
by: Akhtar, Javed, et al.
Published: (2025)
Foundation Models for Discovery and Exploration in Chemical Space
by: Wadell, Alexius, et al.
Published: (2025)
by: Wadell, Alexius, et al.
Published: (2025)
How accurate are foundational machine learning interatomic potentials for heterogeneous catalysis?
by: Kempen, Luuk H. E., et al.
Published: (2025)
by: Kempen, Luuk H. E., et al.
Published: (2025)
Considerations in the use of ML interaction potentials for free energy calculations
by: Mendible, Orlando A., et al.
Published: (2024)
by: Mendible, Orlando A., et al.
Published: (2024)
General-Purpose Models for the Chemical Sciences: LLMs and Beyond
by: Alampara, Nawaf, et al.
Published: (2025)
by: Alampara, Nawaf, et al.
Published: (2025)
Active Learning Enables Extrapolation in Molecular Generative Models
by: Antoniuk, Evan R., et al.
Published: (2025)
by: Antoniuk, Evan R., et al.
Published: (2025)
Breaking scaling relations with inverse catalysts: a machine learning exploration of trends in $\mathrm{CO_2}$ hydrogenation energy barriers
by: Kempen, Luuk H. E., et al.
Published: (2025)
by: Kempen, Luuk H. E., et al.
Published: (2025)
Discovery of 2D Materials via Symmetry-Constrained Diffusion Model
by: Xu, Shihang, et al.
Published: (2024)
by: Xu, Shihang, et al.
Published: (2024)
Clever Materials: When Models Identify Good Materials for the Wrong Reasons
by: Jablonka, Kevin Maik
Published: (2026)
by: Jablonka, Kevin Maik
Published: (2026)
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
by: Zimmermann, Yoel, et al.
Published: (2024)
by: Zimmermann, Yoel, et al.
Published: (2024)
Building-Block Aware Generative Modeling for 3D Crystals of Metal Organic Frameworks
by: Duan, Chenru, et al.
Published: (2025)
by: Duan, Chenru, et al.
Published: (2025)
Adapting OC20-trained EquiformerV2 Models for High-Entropy Materials
by: Clausen, Christian M., et al.
Published: (2024)
by: Clausen, Christian M., et al.
Published: (2024)
Many-body Expansion Based Machine Learning Models for Octahedral Transition Metal Complexes
by: Meyer, Ralf, et al.
Published: (2024)
by: Meyer, Ralf, et al.
Published: (2024)
Model-free quantification of completeness, uncertainties, and outliers in atomistic machine learning using information theory
by: Schwalbe-Koda, Daniel, et al.
Published: (2024)
by: Schwalbe-Koda, Daniel, et al.
Published: (2024)
Deep Learning for GWP Prediction: A Framework Using PCA, Quantile Transformation, and Ensemble Modeling
by: Rajapriya, Navin, et al.
Published: (2024)
by: Rajapriya, Navin, et al.
Published: (2024)
Learning the action for long-time-step simulations of molecular dynamics
by: Bigi, Filippo, et al.
Published: (2025)
by: Bigi, Filippo, et al.
Published: (2025)
The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture
by: Sriram, Anuroop, et al.
Published: (2025)
by: Sriram, Anuroop, et al.
Published: (2025)
Transferable Learning of Reaction Pathways from Geometric Priors
by: Nam, Juno, et al.
Published: (2025)
by: Nam, Juno, et al.
Published: (2025)
Comparing the latent features of universal machine-learning interatomic potentials
by: Chorna, Sofiia, et al.
Published: (2025)
by: Chorna, Sofiia, et al.
Published: (2025)
Kernel Learning Assisted Synthesis Condition Exploration for Ternary Spinel
by: Liu, Yutong, et al.
Published: (2025)
by: Liu, Yutong, et al.
Published: (2025)
Vibrational Fingerprints of Strained Polymers: A Spectroscopic Pathway to Mechanical State Prediction
by: Konrad, Julian, et al.
Published: (2025)
by: Konrad, Julian, et al.
Published: (2025)
Predicting band gap from chemical composition: A simple learned model for a material property with atypical statistics
by: Ma, Andrew, et al.
Published: (2025)
by: Ma, Andrew, et al.
Published: (2025)
Multimodal machine learning with large language embedding model for polymer property prediction
by: Zhang, Tianren, et al.
Published: (2025)
by: Zhang, Tianren, et al.
Published: (2025)
PET-MAD, a lightweight universal interatomic potential for advanced materials modeling
by: Mazitov, Arslan, et al.
Published: (2025)
by: Mazitov, Arslan, et al.
Published: (2025)
Learning from the electronic structure of molecules across the periodic table
by: Kaniselvan, Manasa, et al.
Published: (2025)
by: Kaniselvan, Manasa, et al.
Published: (2025)
Cartesian-nj: Extending e3nn to Irreducible Cartesian Tensor Product and Contracion
by: Xu, Zemin, et al.
Published: (2025)
by: Xu, Zemin, et al.
Published: (2025)
Artificial Intelligence Driven Workflow for Accelerating Design of Novel Photosensitizers
by: Wang, Hongyi, et al.
Published: (2025)
by: Wang, Hongyi, et al.
Published: (2025)
Learning simple heuristic rules for classifying materials based on chemical composition
by: Ma, Andrew, et al.
Published: (2025)
by: Ma, Andrew, et al.
Published: (2025)
Assessing the impact of contact time on leachate chemistry from recycled concrete aggregates
by: Sanger, Morgan D., et al.
Published: (2025)
by: Sanger, Morgan D., et al.
Published: (2025)
Equivariant Machine Learning Interatomic Potentials with Global Charge Redistribution
by: Maruf, Moin Uddin, et al.
Published: (2025)
by: Maruf, Moin Uddin, et al.
Published: (2025)
Refining Coarse-Grained Molecular Topologies: A Bayesian Optimization Approach
by: Ray, Pranoy, et al.
Published: (2025)
by: Ray, Pranoy, et al.
Published: (2025)
Enhancing Diffusion-Based Sampling with Molecular Collective Variables
by: Nam, Juno, et al.
Published: (2025)
by: Nam, Juno, et al.
Published: (2025)
Spectral/Spatial Tensor Atomic Cluster Expansion with Universal Embeddings in Cartesian Space
by: Xu, Zemin, et al.
Published: (2025)
by: Xu, Zemin, et al.
Published: (2025)
Manifold Diffusion for Structure Generation of Transition Metal Complexes
by: Schaufelberger, Luca, et al.
Published: (2026)
by: Schaufelberger, Luca, et al.
Published: (2026)
A chemical language model for reticular materials design
by: Menon, Dhruv, et al.
Published: (2026)
by: Menon, Dhruv, et al.
Published: (2026)
Similar Items
-
Extrapolative ML Models for Copolymers
by: Hashmi, Israrul H., et al.
Published: (2024) -
Nanobubble size controls gas hydrate nucleation in supercooled water
by: Kanaujiya, Ramkhelavan, et al.
Published: (2025) -
Gas Mixture Diffusion and Distribution in the Porous ZIF-90 Framework
by: Yacham, Ashok, et al.
Published: (2025) -
QT-Net: Rethinking Evaluation of AI Models in Atomic Chemical Space
by: Crespo, Pablo Martínez, et al.
Published: (2026) -
Inverse Design of Inorganic Compounds with Generative AI
by: Kneiding, Hannes, et al.
Published: (2026)