Welcome to THE Computational Materials Chemistry Laboratory

Led by Prof. De-en Jiang @ UCR Since 1 July 2014


Our research focuses on computational materials chemistry and nanoscience, with a long-term goal to achieve data-driven design of functional materials and molecules for a sustainable society.

PI: De-en Jiang

Professor of Chemistry

Tel: (951) 827-4430

djiang at ucr.edu

  1. Headline:

  2. 9/23/2021: Postdoc position available in Computational Materials Chemistry in the Jiang group. Please email your CV to the PI. If you see this ad, that means the position is still open.

Materials for gas separation

  1. Important for chemical industry

  2. Sorbents and membranes are most commonly used

  3. We study local interaction of gas and separation media with quantum chemistry

  4. We model solubility and diffusivity with molecular simulations including Monte Carlo and molecular dynamics

Current Research Topics:

  1. Computational nanocatalysis: Nanoclusters, single atoms, oxides, perovskites, zeolites, 2D materials

  2. Simulations of molecular and ionic separations via membranes, sorbents,  composite systems, and ionic liquids for carbon capture and rare-earth separations

  3. First principles understanding of electrical energy storage and solid/liquid interfaces

  4. Understanding physical and chemical properties of molten salts from molecular dynamics for nuclear energy applications

Important challenges in nanocatalysis

  1. Convert abundant small molecules to fuels and value-added chemicals

  2. We use electronic structure methods such as DFT coupled with transition-state search to understand and predict catalytic pathways

  3. Catalysts of special interest include gold nanoclusters, 2D materials, transition-metal oxides, and bimetallic materials

Moore’s Law Meets Materials Chemistry via Quantum Mechanics, Classical Mechanics, and Machine Learning. We aim to address the following materials chemistry challenges with computational tools.

Molten salt chemistry for nuclear energy

  1. Molten-salt reactors (MSEs) offer many advantages over the conventional light-water reactors.

  2. Many thermophysical, thermochemical, and transport properties of molten chloride salts relevant to fast-spectrum MSEs are not available.

  3. We use MD simulations to predict structure/coordination, spectral features, and thermophysical properties of molten chlorides.

Electric energy storage

  1. Broad applications in transportation, electronics, and robotics

  2. We work on supercapacitors, including double-layer and pseudo capacitors

  3. We use joint DFT to study the charging behaviors of different materials including advanced carbons and MXenes

Advanced membranes

CO2 reduction on a Cu cluster


Charge storage in H2SO4

Network structures in UCl3-NaCl and UCl4-NaCl from first principles MD

Ligand design and molecular simulations for rare-earth separations

  1. Important for critical materials needs

  2. Coordination chemistry, solvation, and interfacial phenomena

  3. Data-driven predictive modeling of distribution ratios and separation factors via machine learning

Deep learning of hydride locations