2.6k citations · 3k across the 39 of their papers we have counts for
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The Interplay of Pauli Repulsion, Electrostatics, and Field Inhomogeneity for Blueshifting and Redshifting Vibrational Probe Molecules
R. Allen LaCour, Ruoqi Zhao, Teresa Head-Gordon
Many molecules' vibrational frequencies are sensitive to intermolecular electric fields, enabling them to probe the field in complex molecular environments. However, it is often un…
Teachers that teach the irrelevant: Pre-training machine learned interaction potentials with classical force fields for robust molecular dynamics simulations
Eric C. -Y. Yuan, Teresa Head-Gordon
Machine learned interaction potentials (MLIPs) have become a critical component of large-scale, high-quality simulations for a range of chemical and biochemical systems. Yet, despi…
Ammonia Synthesis under Ambient Conditions: Insights into Water-Nitrogen-Magnetite Interfaces
Sruthy K. Chandy, Mauricio Lopez Luna, Nykita Z. Rustad +6
New routes for transforming nitrogen into ammonia at ambient conditions would be a milestone toward an energy efficient and economically attractive production route in comparison t…
Can Charge Transfer Across C-H...O Hydrogen Bonds Stabilize Oil Droplets in Water?
Ruoqi Zhao, Hengyuan Shen, R. Allen LaCour +3
Oil-water emulsions resist aggregation due to the presence of negative charges at their surface that leads to mutual repulsion between droplets, but the molecular origin of oil cha…
Foundation Models for Atomistic Simulation of Chemistry and Materials
Eric C. -Y. Yuan, Yunsheng Liu, Junmin Chen +11
Given the power of large language and large vision models, it is of profound and fundamental interest to ask if a foundational model based on data and parameter scaling laws and pr…
The Role of Interfaces and Charge for Chemical Reactivity in Microdroplets
R. Allen LaCour, Joseph P. Heindel, Ruoqi Zhao +1
A wide variety of reactions are reported to be dramatically accelerated in aqueous microdroplets, making them a promising platform for environmentally clean chemical synthesis. How…
Completely Multipolar Model for Many-Body Water-Ion and Ion-Ion Interactions
J. P. Heindel, L. Kim, M. Head-Gordon +1
This work constructs an advanced force field, the Completely Multipolar Model (CMM), to quantitatively reproduce each term of an energy decomposition analysis (EDA) for aqueous sol…
SmileyLlama: Modifying Large Language Models for Directed Chemical Space Exploration
Joseph M. Cavanagh, Kunyang Sun, Andrew Gritsevskiy +4
We show that large language model (LLMs) can be transformed via supervised fine-tuning (SFT) of engineered prompts into SmileyLlama for exploring the chemical space of drug molecul…
Completely Multipolar Model as a General Framework for Many-Body Interactions as Illustrated for Water
Joseph P. Heindel, Selim Sami, Teresa Head-Gordon
We introduce a general framework for many-body force field models, the Completely Multipolar Model (CMM), that utilizes multipolar electrical moments modulated by exponential decay…
Deep Learning of ab initio Hessians for Transition State Optimization
Eric C. -Y. Yuan, Anup Kumar, Xingyi Guan +5
Identifying transition states -- saddle points on the potential energy surface connecting reactant and product minima -- is central to predicting kinetic barriers and understanding…
Water Structure and Electric Fields at the Interface of Oil Droplets
Lixue Shi, R. Allen LaCour, Xiaoqi Lang +3
Mesoscale water-hydrophobic interfaces are of fundamental importance in multiple disciplines, but their molecular properties have remained elusive for decades due to experimental c…
The Role of Charge in Microdroplet Redox Chemistry
Joseph P. Heindel, R. Allen LaCour, Teresa Head-Gordon
In charged water microdroplets, which occur in nature or in the lab upon ultrasonication or in electrospray processes, the thermodynamics for reactive chemistry can be dramatically…
Greater Transferability and Accuracy of Norm-conserving Pseudopotentials using Nonlinear Core Corrections
Wan-Lu Li, Kaixuan Chen, Elliot Rossomme +2
We present an investigation into the transferability of pseudopotentials (PPs) with a nonlinear core correction (NLCC) using the Goedecker, Teter, and Hutter (GTH) protocol across…
Beyond potential energy surface benchmarking: a complete application of machine learning to chemical reactivity
Xingyi Guan, Joseph Heindel, Taehee Ko +2
We train an equivariant machine learning model to predict energies and forces for a real-world study of hydrogen combustion under conditions of finite temperature and pressure. Thi…
Highly Accurate Prediction of NMR Chemical Shifts from Low-Level Quantum Mechanics Calculations Using Machine Learning
Jie Li, Jiashu Liang, Zhe Wang +5
Theoretical predictions of NMR chemical shifts from first-principles can greatly facilitate experimental interpretation and structure identification. However, accurate prediction o…
Using Diffusion Maps to Analyze Reaction Dynamics for a Hydrogen Combustion Benchmark Dataset
Taehee Ko, Joseph Heindel, Xingyi Guan +3
We use local diffusion maps to assess the quality of two types of collective variables (CVs) for a recently published hydrogen combustion benchmark dataset~\cite{guan2022benchmark}…
Efficient Calculation of NMR Shielding Constants Using Composite Method Approximations and Locally Dense Basis Sets
Jiashu Liang, Zhe Wang, Jie Li +5
This paper presents a systematic study of applying composite method approximations with locally dense basis sets (LDBS) to efficiently calculate NMR shielding constants in small an…
NewtonNet: A Newtonian message passing network for deep learning of interatomic potentials and forces
Mojtaba Haghighatlari, Jie Li, Xingyi Guan +10
We report a new deep learning message passing network that takes inspiration from Newton's equations of motion to learn interatomic potentials and forces. With the advantage of dir…
The Critical Role of Thermal Fluctuations for Electrocatalytic Metal Surface Properties and CO Binding Trends
Wan-Lu Li, Christianna N. Lininger, Valerie Vaissier Welborn +4
This work addresses a longstanding theoretical discrepancy using Density Functional Theory (DFT) with experimental observations of CO binding trends on electrocatalytically relevan…
An Isolated Water Droplet in the Aqueous Solution of a Supramolecular Tetrahedral Cage
Federico Sebastiani, Trandon A. Bender, Simone Pezzotti +7
Water under nanoconfinement at ambient conditions has exhibited low-dimensional ice formation and liquid-solid phase transitions, but with structural and dynamical signatures which…
Learning to Make Chemical Predictions: the Interplay of Feature Representation, Data, and Machine Learning Algorithms
Mojtaba Haghighatlari, Jie Li, Farnaz Heidar-Zadeh +3
Recently supervised machine learning has been ascending in providing new predictive approaches for chemical, biological and materials sciences applications. In this Perspective we…
Accurate Prediction of Chemical Shifts for Aqueous Protein Structure for "Real World" Cases using Machine Learning
Jie Li, Kochise C. Bennett, Yuchen Liu +2
Accurate prediction of NMR chemical shifts can in principle help refine aqueous solution structure of proteins to the quality of X-ray structures. We report a new machine learning…
Diels-Alder Reactions in Water are Determined by Microsolvation
Luis Ruiz Pestana, Hongxia Hao, Teresa Head-Gordon
Nanoconfined aqueous environments and the recent advent of accelerated chemistry in microdroplets are increasingly being investigated for catalysis. The mechanisms underlying the e…
Interplay of Water and a Supramolecular Capsule for Catalysis of Reductive Elimination Reaction from Gold
Valerie Vaissier Welborn, Wan-Lu Li, Teresa Head-Gordon
Supramolecular assemblies have gained tremendous attention due to their apparent ability to catalyze reactions with the efficiencies of natural enzymes. Using Born-Oppenheimer mole…