Cover Image

Free energy profiles for chemical reactions in solution from high-dimensional neural network potentials: The case of the Strecker synthesis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tokita, Alea Miako, Devergne, Timothée, Saitta, A. Marco, Behler, Jörg
Format:	Preprint
Published:	2025
Subjects:	Chemical Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Machine learning potentials for redox chemistry in solution
by: Kocer, Emir, et al.
Published: (2024)

The seeds of the future are in the present: A blind exploration of metastable states
by: Devergne, Timothée, et al.
Published: (2025)

From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach
by: Devergne, Timothée, et al.
Published: (2024)

Molecular Dynamics Simulations of $γ$-Belite(010)-Water Interfaces with High-Dimensional Neural Network Potentials
by: Prus, Bernadeta, et al.
Published: (2025)

Insights into the Structure and Dynamics of Water at Co$_3$O$_4$(001) Using a High-Dimensional Neural Network Potential
by: Omranpour, Amir, et al.
Published: (2025)

Random sampling versus active learning algorithms for machine learning potentials of quantum liquid water
by: Stolte, Nore, et al.
Published: (2024)

Computation of the heat capacity of water from first principles
by: Shiga, Motoyuki, et al.
Published: (2025)

Targeted energy transfer dynamics and chemical reactions
by: Almazova, N., et al.
Published: (2024)

A neural network-based four-body potential energy surface for parahydrogen
by: Ibrahim, Alexander, et al.
Published: (2025)

Overcoming sampling limitations using machine-learned interatomic potentials: the case of water-in-salt electrolytes
by: Brugnoli, Luca, et al.
Published: (2026)

Accuracy of Charge Densities in Electronic Structure Calculations
by: Gubler, Moritz, et al.
Published: (2024)

Atomistic Simulations of Oxide-Water Interfaces using Machine Learning Potentials
by: Elsner, Jan, et al.
Published: (2025)

Accurate neural-network-based fitting of full-dimensional two-body potential energy surfaces
by: Finenko, Artem
Published: (2022)

Nuclear Quantum Effects in Liquid Water Are Negligible for Structure but Significant for Dynamics
by: Stolte, Nore, et al.
Published: (2024)

Impact of the damping function in dispersion-corrected density functional theory on the properties of liquid water
by: Lausch, K. Nikolas, et al.
Published: (2025)

Investigating the hyperparameter space of deep neural network models for reaction coordinates
by: Kawashima, Kyohei, et al.
Published: (2024)

Machine Learning Potentials for Heterogeneous Catalysis
by: Omranpour, Amir, et al.
Published: (2024)

Universal neural network potentials as descriptors: Towards scalable chemical property prediction using quantum and classical computers
by: Shiota, Tomoya, et al.
Published: (2024)

Machine learning prediction of a chemical reaction over 8 decades of energy
by: Julian, Daniel, et al.
Published: (2025)

Noise-robust chemical reaction networks training artificial neural networks
by: Kang, Sunghwa, et al.
Published: (2024)

Thermodynamic Circuits: Modeling chemical reaction networks with nonequilibrium conductance matrices
by: Raux, Paul, et al.
Published: (2024)

Perspective: Atomistic Simulations of Water and Aqueous Systems with Machine Learning Potentials
by: Omranpour, Amir, et al.
Published: (2024)

Control of chemical reactions in radiofrequency ion traps
by: Paliwal, Prerna, et al.
Published: (2025)

Symmetry enforced solution of the many-body Schrödinger equation with deep neural network
by: Li, Zhe, et al.
Published: (2024)

Optimizing reaction and transport fluxes in temperature gradient-driven chemical reaction-diffusion systems
by: Loukili, Mohammed, et al.
Published: (2024)

Kinetic study of the CN + C2H6 hydrogen abstraction reaction based on an analytical potential energy surface
by: Espinosa-Garcia, Joaquin, et al.
Published: (2023)

Effect of strength of gravitational field on the rate of chemical reactions
by: Baig, Mirza Wasif
Published: (2017)

Navigating chemical reaction space with a steering wheel
by: Steiner, Miguel, et al.
Published: (2023)

Unveiling the hidden reaction kinetic network of carbon dioxide in supercritical aqueous solutions
by: Li, Chu, et al.
Published: (2024)

Ab initio thermodynamics of liquid and solid water
by: Cheng, Bingqing, et al.
Published: (2018)

Accuracy of reaction coordinate based rate theories for modelling chemical reactions: insights from the thermal isomerization in retinal
by: Ghysbrecht, Simon, et al.
Published: (2023)

Ultrafast photodissociation dynamics of dichloromethane on three-dimensional potential energy surfaces and its Coulomb explosion signature
by: Ding, Yijue
Published: (2025)

Modeling the coincident three-ion momentum imaging of diiodomethane photodissociation on reduced-dimensional potential energy surfaces
by: Ding, Yijue
Published: (2025)

Blackbody radiation and thermal effects on chemical reactions and phase transitions in cavities
by: Pannir-Sivajothi, Sindhana, et al.
Published: (2024)

Performance assessment of the effective core potentials under the Fermionic neural network: first and second row elements
by: Wang, Mengsa, et al.
Published: (2024)

A constant potential reactor framework for electrochemical reaction simulations
by: Chen, Letian, et al.
Published: (2024)

Assessing zero-shot generalisation behaviour in graph-neural-network interatomic potentials
by: Mahmoud, Chiheb Ben, et al.
Published: (2025)

Ground and excited potential energy surfaces for CaF+Ca interactions and isotope exchange reactions
by: Sardar, Dibyendu, et al.
Published: (2025)

Stoichiometrically-informed symbolic regression for extracting chemical reaction mechanisms from data
by: Banos, Manuel Palma, et al.
Published: (2025)

A data-driven sparse learning approach to reduce chemical reaction mechanisms
by: Fang, Shen, et al.
Published: (2024)