A5075737283- Machine Learning in Materials Science
- Zeolite Catalysis and Synthesis
- Catalysis and Oxidation Reactions
- Catalytic Processes in Materials Science
- Nanomaterials for catalytic reactions
- Organometallic Complex Synthesis and Catalysis
- Polyoxometalates: Synthesis and Applications
- Quantum, superfluid, helium dynamics
- Theoretical and Computational Physics
- Protein Structure and Dynamics
- Asymmetric Hydrogenation and Catalysis
- Gas Dynamics and Kinetic Theory
- Catalysis and Hydrodesulfurization Studies
- Robotic Path Planning Algorithms
- Computational Drug Discovery Methods
- Catalysis for Biomass Conversion
- Digital Filter Design and Implementation
- Scientific Computing and Data Management
- NMR spectroscopy and applications
- Inorganic Chemistry and Materials
- Axial and Atropisomeric Chirality Synthesis
- Hydrogen Storage and Materials
- Membrane Separation and Gas Transport
- Graphene research and applications
- Numerical Methods and Algorithms
University of Chicago
2023-2025
University of Arizona
2025
Purdue University West Lafayette
2020-2023
Nanjing University of Science and Technology
2010-2011
Abstract Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of can be greatly expanded by providing access to advanced sampling methods techniques that permit calculation the relevant underlying free energy landscapes. In this sense, software seamlessly adapted a broad range complex systems is essential. Building on past efforts provide open-source community-supported sampling, we introduce PySAGES, Python implementation Software...
Abstract In heterogeneous catalysis, olefin oligomerization is typically performed on immobilized transition metal ions, such as Ni 2+ and Cr 3+ . Here we report that silica-supported, single site catalysts containing immobilized, main group Zn Ga ion sites catalyze ethylene propylene to an equilibrium distribution of linear olefins with rates similar The molecular weight products formed , while forms higher olefins. situ spectroscopic computational studies suggest unexpectedly occurs by the...
Abstract Characterizing the reaction energies and barriers of networks is central to catalyst development. However, heterogeneous catalytic surfaces pose several unique challenges automatic network characterization, including large sizes open-ended reactant sets, that make ad hoc construction current state-of-the-art. Here, we show how automated exploration algorithms can be adapted constraints systems using ethylene oligomerization on silica-supported single-site Ga 3+ as a model system....
Methane activation on stepped Ni(511) surfaces involves the rearrangement of surface atoms as chemical reaction proceeds. This process is particularly sensitive to temperature. Using machine-learned interatomic potentials (MLIPs) coupled with enhanced sampling techniques, we investigate methane under realistic operando conditions. Our analysis reveals that dissociation occurs predominantly at step-edge nickel atoms. As CHx (where x = 3 or 4) species bind additional atoms, their reduced...
The thia-Michael reaction, i.e., the addition of a thiol to an α,β-unsaturated carbonyl moiety, has recently gained significant attention within field dynamic covalent chemistry. Interestingly, including additional electron-withdrawing group at α-position Michael acceptor can result in room temperature (rt), catalyst-free reactions. Importantly, electronic nature be used tune equilibrium constant (Keq) these Herein we report how sterics enhance Keq rt bonds. A series benzalcyanoacetate,...
Water auto-ionization is critical in a wide range of chemical, biological, physical, and industrial processes. In this work, we describe series hitherto unknown collective molecular processes leading to auto-ionization. Specifically, by combining machine-learned interatomic potentials spectral adaptive biasing force techniques, determine the relevant free energy landscape water At ambient conditions, profile reveals two distinct saddle points, each formation three- four-member wires. The...
A combination of machine learned interatomic potentials (MLIPs) and enhanced sampling simulations is used to investigate the activation methane on a Ni(111) surface. The work entails development iterative refinement MLIPs, initially trained data set constructed via ab initio molecular dynamics simulations, supplemented by adaptive biasing forces, enrich catalytically relevant configurations. Our results reveal that upon incorporation collective variables capture behavior reactant molecule,...
Abstract A wide range of methyl esters, including esters aromatic carboxylic acids, alkenyl aliphatic and protected amino were reduced to the corresponding alcohols with NaBH4 in ethanol presence a catalytic amount CeCl3. The reaction was completed within 24 h at ambient temperature showed high functional group compatibility chemoselectivity. With containing nitro, methoxyl, halogen, alkenyl, functionalities, only ester reduced. isolated after evaporation solvent routine aqueous workup good...
The semi-hydrogenation of α,β-unsaturated aldehydes to the desired unsaturated alcohols with both high conversion and selectivity remains a big challenge. Herein, we designed sandwich-structured nanocatalyst for highly selective hydrogenation various (e.g., cinnamaldehyde, furfural, crotonaldehyde, 3-methyl-2-butenal) targeted alcohols. Highly accessible platinum nanoparticles were sandwiched between metal-organic framework (MOF) core (i.e., MIL-88B(Fe)) MOF shell Al-TCPP). In particular,...
Water auto-ionization is critical in a wide range of chemical, biological, physical, and industrial processes. In this work, we describe series hitherto unknown collective molecular processes leading to auto-ionization. Specifically, by combining machine-learned interatomic potentials spectral adaptive biasing force techniques, determine the relevant free energy landscape water At ambient conditions, profile reveals two distinct saddle points, each formation three- four-member wires. The...
Amorphous, single-site, silica-supported main group metal catalysts have recently been found to promote olefin oligomerization with high activity at moderate temperatures and pressures (∼250 °C 1 atm). Herein, we explore the molecular level relationship between active site structures associated mechanisms by developing amorphous, Ga3+ models from periodic, first principles calculations. Representative sites, including three- four-coordinated geometries, are tested for multiple ethylene...
Machine learning interatomic potentials (MLIPs) are rapidly gaining interest for molecular modeling, as they provide a balance between quantum-mechanical level descriptions of atomic interactions and reasonable computational efficiency. However, questions remain regarding the stability simulations using these potentials, well extent to which learned potential energy function can be extrapolated safely. Past studies have encountered challenges when MLIPs applied classical benchmark systems....
Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of can be greatly expanded by providing access to advanced sampling methods techniques that permit calculation the relevant underlying free energy landscapes. In this sense, software seamlessly adapted a broad range complex systems is essential. Building on past efforts provide open-source community supported sampling, we introduce PySAGES, Python implementation Software Suite...
Amorphous, single site, silica-supported main group metal catalysts have recently been found to promote olefin oligomerization with high activity at moderate temperatures and pressures (~250°C 1 atm). Herein, we explore the molecular-level relationship between active site structures associated mechanisms by developing amorphous, Ga3+ models from periodic, first-principles calculations. Representative sites, including three- four-coordinated geometries, are tested for multiple ethylene...
Characterizing the reaction energies and barriers of complex networks is central to catalyst development optimization. Nevertheless, heterogeneous catalytic surfaces pose several unique challenges automatic network characterization, including large system sizes open-ended reactant lists, that make ad hoc construction characterization current state-of-the-art. Here we show how automated algorithms for exploring characterizing can be adapted constraints systems using ethylene oligomerization...
Abstract In heterogeneous catalysis, olefin oligomerization is typically performed on immobilized transition metal ions, such as Ni 2+ and Cr 3+ . Here we report that silica-supported, single site catalysts containing immobilized, main group Zn Ga ions catalyze ethylene propylene to an equilibrium distribution of linear olefins with rates similar The molecular weight products formed ; while forms higher olefins. situ spectroscopic computational studies suggest unexpectedly occurs by the...
Understanding the interactions between molten polymers and inorganic porous solids is critical for heterogeneous catalytic conversion of waste into useful chemicals fabrication nanocomposites nanostructured polymers. Developing experimental theoretical approaches to quantify understand polymer-surface would be extremely design new catalysts composites. Here, we demonstrate that interfacial energy polystyrene (PS) or polyethylene (PE) various surfaces prepared via atomic layer deposition...
Abstract An efficient, chemoselective, and general protocol for the reduction of various methyl esters to corresponding alcohols is described.
Characterizing the reaction energies and barriers of complex networks is central to catalyst development optimization. Nevertheless, heterogeneous catalytic surfaces pose several unique challenges automatic network characterization, including large system sizes open-ended reactant lists, that make ad hoc construction characterization current state-of-the-art. Here we show how automated algorithms for exploring characterizing can be adapted constraints systems using ethylene oligomerization...