Molecular Dynamics and Machine Learning Unlock Possibilities in Beauty Design -- A Perspective
Fuente:
arXiv
Saved in:
| Main Authors: | Xu, Yuzhi, Ni, Haowei, Gao, Qinhui, Chang, Chia-Hua, Huo, Yanran, Zhao, Fanyu, Hu, Shiyu, Xia, Wei, Zhang, Yike, Grovu, Radu, He, Min, Zhang, John. Z. H., Wang, Yuanqing |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Investigation of the Products and the Migration of Sodium and Chlorine During Pyrolysis of High‐Sodium Coal Mixed With Phosphorite
by: Zhihua Tian, et al.
Published: (2024)
by: Zhihua Tian, et al.
Published: (2024)
Partial Gasification Kinetic and Thermodynamic Parameters of Lignite in Atmospheres With Varying O 2 Percentages Using TG Analysis
by: Bin Zhang, et al.
Published: (2025)
by: Bin Zhang, et al.
Published: (2025)
Effect of non‐ionic frothers on bubble characteristics in flotation: a review
by: Gaochao Pan, et al.
Published: (2024)
by: Gaochao Pan, et al.
Published: (2024)
Scaling Machine Learning Interatomic Potentials with Mixtures of Experts
by: Liu, Yuzhi, et al.
Published: (2026)
by: Liu, Yuzhi, et al.
Published: (2026)
Node-Equivariant Message Passing for Efficient and Accurate Machine Learning Interatomic Potentials
by: Zhang, Yaolong, et al.
Published: (2025)
by: Zhang, Yaolong, et al.
Published: (2025)
Local Pseudopotential Unlocks the True Potential of Neural Network-based Quantum Monte Carlo
by: Fu, Weizhong, et al.
Published: (2025)
by: Fu, Weizhong, et al.
Published: (2025)
The Evolution of Machine Learning Potentials for Molecules, Reactions and Materials
by: Xia, Junfan, et al.
Published: (2025)
by: Xia, Junfan, et al.
Published: (2025)
Machine Learning Framework for Modeling Exciton-Polaritons in Molecular Materials
by: Li, Xinyang, et al.
Published: (2023)
by: Li, Xinyang, et al.
Published: (2023)
Designing Functional Metal/Doped‐Carbon Materials via Sol–Gel Method and their Applications in Catalysis Field
by: Pingyun Li, et al.
Published: (2025)
by: Pingyun Li, et al.
Published: (2025)
EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment
by: Wang, Yuanqing, et al.
Published: (2023)
by: Wang, Yuanqing, et al.
Published: (2023)
Effect of Inorganic Ions on Coal Slurry Conditioning—From the Viewpoint of Energy Dissipation and Mechanical Analysis
by: Ming Yang, et al.
Published: (2025)
by: Ming Yang, et al.
Published: (2025)
Revisiting Sampling Strategies for Molecular Generation
by: Ni, Yuyan, et al.
Published: (2025)
by: Ni, Yuyan, et al.
Published: (2025)
Semiclassical Nonadiabatic Molecular Dynamics for Molecular Exciton-Polaritons
by: Li, Xinyang, et al.
Published: (2024)
by: Li, Xinyang, et al.
Published: (2024)
Gaussian-Based Periodic Grand Canonical Density Functional Theory with Implicit Solvation for Computational Electrochemistry
by: Ni, Anton Z., et al.
Published: (2025)
by: Ni, Anton Z., et al.
Published: (2025)
Performance assessment of the effective core potentials under the Fermionic neural network: first and second row elements
by: Wang, Mengsa, et al.
Published: (2024)
by: Wang, Mengsa, et al.
Published: (2024)
Quantum Machine Learning of Molecular Energies with Hybrid Quantum-Neural Wavefunction
by: Li, Weitang, et al.
Published: (2025)
by: Li, Weitang, et al.
Published: (2025)
Explicit, Machine-Learned Two-Body Potentials for Molecular Simulations
by: Chaton, Kham Lek, et al.
Published: (2026)
by: Chaton, Kham Lek, et al.
Published: (2026)
Developing a Machine-Learning Interatomic Potential for Non-Covalent Interactions in Proteins
by: Zeng, Lejia, et al.
Published: (2026)
by: Zeng, Lejia, et al.
Published: (2026)
Accuracy and Efficiency Benchmarks of Pretrained Machine Learning Potentials for Molecular Simulations
by: Eastman, Peter, et al.
Published: (2026)
by: Eastman, Peter, et al.
Published: (2026)
Molecular Quantum Chemical Data Sets and Databases for Machine Learning Potentials
by: Ullah, Arif, et al.
Published: (2024)
by: Ullah, Arif, et al.
Published: (2024)
Advancing Molecular Machine Learning Representations with Stereoelectronics-Infused Molecular Graphs
by: Boiko, Daniil A., et al.
Published: (2024)
by: Boiko, Daniil A., et al.
Published: (2024)
A Pre-trained Deep Potential Model for Sulfide Solid Electrolytes with Broad Coverage and High Accuracy
by: Wang, Ruoyu, et al.
Published: (2024)
by: Wang, Ruoyu, et al.
Published: (2024)
Wave-Packet Surface Propagation for Light-Induced Molecular Dissociation
by: Pan, Shengzhe, et al.
Published: (2023)
by: Pan, Shengzhe, et al.
Published: (2023)
Molecular Machine Learning in Chemical Process Design
by: Rittig, Jan G., et al.
Published: (2025)
by: Rittig, Jan G., et al.
Published: (2025)
Ionic Liquid Molecular Dynamics Simulation with Machine Learning Force Fields: DPMD and MACE
by: Park, Anseong, et al.
Published: (2025)
by: Park, Anseong, et al.
Published: (2025)
High-Accuracy Molecular Simulations with Machine-Learning Potentials and Semiclassical Approximations to Quantum Dynamics
by: Andreichev, Valerii, et al.
Published: (2026)
by: Andreichev, Valerii, et al.
Published: (2026)
A Machine Learning Pipeline for Molecular Property Prediction using ChemXploreML
by: Marimuthu, Aravindh Nivas, et al.
Published: (2025)
by: Marimuthu, Aravindh Nivas, et al.
Published: (2025)
Cluster Models for Next-Generation, Machine-Learning-Based Energy Functions for Molecular Simulations
by: Wang, JingChun, et al.
Published: (2025)
by: Wang, JingChun, et al.
Published: (2025)
Thermodynamic Descriptors from Molecular Dynamics as Machine Learning Features for Extrapolable Property Prediction
by: Espejo, Nuria H., et al.
Published: (2026)
by: Espejo, Nuria H., et al.
Published: (2026)
Hierarchical Wavepacket Propagation Framework via ML-MCTDH for Molecular Reaction Dynamics
by: Zhang, Xingyu, et al.
Published: (2025)
by: Zhang, Xingyu, et al.
Published: (2025)
Network Pharmacology, Machine Learning, Molecular Docking, and Cell Experiments Reveal the Therapeutic Mechanism of Radix Rehmanniae Praeparata in Psoriasis In Vitro
by: Tingting Zhang, et al.
Published: (2026)
by: Tingting Zhang, et al.
Published: (2026)
Systematically Improvable Numerical Atomic Orbital Basis Using Contracted Truncated Spherical Waves
by: Huang, Yike, et al.
Published: (2026)
by: Huang, Yike, et al.
Published: (2026)
Machine Learning Interatomic Potentials: Advancing Open-Source Software for Efficient and Scalable Molecular Simulation
by: Brunken, Christoph, et al.
Published: (2026)
by: Brunken, Christoph, et al.
Published: (2026)
Cover Picture: Skeletal Editing of Isatins for Heterocycle Molecular Diversity (Chem. Rec. 6/2024)
by: Tiantian Zhang, et al.
Published: (2024)
by: Tiantian Zhang, et al.
Published: (2024)
Molecular Modelling of Aqueous Batteries
by: van Hees, Alicia, et al.
Published: (2024)
by: van Hees, Alicia, et al.
Published: (2024)
Automated Molecular Concept Generation and Labeling with Large Language Models
by: Zhang, Zimin, et al.
Published: (2024)
by: Zhang, Zimin, et al.
Published: (2024)
Unlocking Inverted Singlet-Triplet Gap in Alternant Hydrocarbons with Heteroatoms
by: Majumdar, Atreyee, et al.
Published: (2025)
by: Majumdar, Atreyee, et al.
Published: (2025)
Bipotentiostatic Control Unlocks Flashing Ratchet Features in Ion Pumps
by: Grossman, Eden, et al.
Published: (2025)
by: Grossman, Eden, et al.
Published: (2025)
Prediction of Drug‐Induced Liver Injury: From Molecular Physicochemical Properties and Scaffold Architectures to Machine Learning Approaches
by: Yulong Zhao, et al.
Published: (2024)
by: Yulong Zhao, et al.
Published: (2024)
Clarifying NH2 + O(3P) Reaction Dynamics: A Full-Dimensional MRCI, Machine-Learned PES Unravels High-Temperature Kinetics
by: Xing, Ying, et al.
Published: (2026)
by: Xing, Ying, et al.
Published: (2026)
Similar Items
-
Investigation of the Products and the Migration of Sodium and Chlorine During Pyrolysis of High‐Sodium Coal Mixed With Phosphorite
by: Zhihua Tian, et al.
Published: (2024) -
Partial Gasification Kinetic and Thermodynamic Parameters of Lignite in Atmospheres With Varying O 2 Percentages Using TG Analysis
by: Bin Zhang, et al.
Published: (2025) -
Effect of non‐ionic frothers on bubble characteristics in flotation: a review
by: Gaochao Pan, et al.
Published: (2024) -
Scaling Machine Learning Interatomic Potentials with Mixtures of Experts
by: Liu, Yuzhi, et al.
Published: (2026) -
Node-Equivariant Message Passing for Efficient and Accurate Machine Learning Interatomic Potentials
by: Zhang, Yaolong, et al.
Published: (2025)