Nicholas Jackson

Assistant Professor

University of Illinois at Urbana-Champaign

United States

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About

Nicholas Jackson is an Assistant Professor at the University of Illinois at Urbana Champaign, USA. His research focuses on polymer reactivity predictions, machine learning applications in chemical processes, and the exploration of soft materials derived from metabolites. Recent publications include studies on copolymer radical reactivity, bond rupture in thermoset networks, and the design of functional monomers for accessible polymers.

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Gül H. Zerze

University of Houston

UNITED STATES

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Charles M. Schroeder

UNITED STATES

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Chun-I Wang

Assistant Professor

Lehman College

UNITED STATES

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Elisa Pieri

Assistant Professor

University of North Carolina at Chapel Hill

UNITED STATES

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Nicholas Jackson

Research Interests

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About

Articles (24)

A Machine Learning Model for Copolymer Radical Reactivity Ratio Predictions with Frontier-Orbital Insights

In Silico Exploration of Metabolite-Derived Soft Materials Using a Chemical Reaction Network

Ten Problems in Polymer Reactivity Prediction

Shortest Paths Govern Bond Rupture in Thermoset Networks

Active learning high coverage sets of complementary reaction conditions

Functional monomer design for synthetically accessible polymers

Secondary structure determines electron transport in peptides

Distilling coarse-grained representations of molecular electronic structure with continuously gated message passing

Accessing the electronic structure of liquid crystalline semiconductors with bottom-up electronic coarse-graining

Closed-loop transfer enables artificial intelligence to yield chemical knowledge

JCTC Early Career Board Selects

Assessing molecular doping efficiency in organic semiconductors with reactive Monte Carlo

Exploring Thermoset Fracture with a Quantum Chemically Accurate Model of Bond Scission

Chemically Transferable Electronic Coarse Graining for Polythiophenes

Introduction to Machine Learning for Molecular Simulation

Excited State Dynamics of a Conformationally Fluxional Copper Coordination Complex

Open Macromolecular Genome: Generative Design of Synthetically Accessible Polymers

Identifying Coarse-Grained Representations for Electronic Predictions

AL4GAP: Active learning workflow for generating DFT-SCAN accurate machine-learning potentials for combinatorial molten salt mixtures

Photophysics in emerging photovoltaics

Machine learning quantum-chemical bond scission in thermosets under extreme deformation

Solution Aggregate Structures of Donor Polymers Determine the Morphology and Processing Resiliency of Non-Fullerene Organic Solar Cells

Bringing Quantum Mechanics to Coarse-Grained Soft Materials Modeling

Electron and ion transport in semi-dilute conjugated polyelectrolytes: view from a coarse-grained tight binding model

Collaborators (11)

Alan Aspuru-Guzik

Bronte Charette

Lisa Olshansky

Emad Tajkhorshid

Michael Webb

Austin Jones

Antonia Statt

Gül H. Zerze

Charles M. Schroeder

Chun-I Wang

Elisa Pieri

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