University of California, Riverside

Department of Chemistry



Faculty


 

 

De-en Jiang
Associate Professor of Chemistry

 

Peking University – B.S. in Chemistry (1997)
Peking University – M.S. in Chemistry (2000)
University of California, Los Angeles – Ph.D. (2005)
Princeton University – Visiting Student Research Collaborator (2004-2005)
Oak Ridge National Laboratory – Postdoc. Fellow (2005-2006)
Oak Ridge National Laboratory – Staff Scientist (2006-2014)

Office: 136 Chemical Sciences
Phone O/L: (951) 827-4430/3082
Email: djiang@ucr.edu
Research Area: Computational Chemistry, Materials Chemistry, Physical Chemistry
Group Site

Research Overview


My overall research goal is to achieve knowledge-based design of functional materials for a sustainable society. Meeting the increasing energy demand for an ever growing population requires new materials that can lead to breakthroughs in energy efficiency, conversion, and storage and at the same time mitigate or minimize the undesirable environmental impact to our air and water. Beyond the conventional trial-and-error approach, materials by design in the spirit of the White House’s Materials Genome Initiative promises to greatly accelerate the speed of materials discovery. The fast advances in computing hardware in the past two decades provide chemists an invaluable and essential tool to understand and discover new chemistry by computation. And my primary research interest lies in using state-of-the-art computational methods to understand fundamental materials chemistry and to design new materials. 

Nanomaterials play an important role in many energy-critical processes, such as heterogeneous catalysis, fuel cells, and photocatalysis. My first research interest is to understand what makes a nanomaterial nano. More specifically, why are certain-shaped or -sized nanomaterials made? What is their growth mechanism? Atomically precise, monolayer-protected clusters, especially thiolate-protected gold nanoclusters, have now offered such a well-defined system for one to understand the detailed formation mechanism, as many intermediate structures have been identified. By working closely with our experimental collaborators, we will elucidate the detailed elementary steps leading to evolution of the so-called magic clusters based on quantum chemical methods such as density functional theory. 

My second research interest is in structure prediction for nanomaterials. To do structure prediction from first principles for larger systems such as a 2-nm nanoparticle remains challenging. The reason is twofold: (1) first principles method does not scale well with the number of electrons in the system and becomes intractable for large systems; (2) high-quality empirical force fields, which have been extremely successful in simulating biomolecules, are not available for most of the materials which are interesting and important. Here we will pursue a novel force-field approach. In this approach, one generates high-quality force fields for inorganic materials by teaching computers to learn your systems based on simple, high-throughput first principles training sets. Although this method just began to attract attention, it holds great promises in computational materials chemistry. 

My third interest is in nanoporous materials. Porosity is an important characteristic of many energy-relevant materials, such as zeolites, metal-organic frameworks, covalent-organic frameworks, porous carbons, and polymers with intrinsic micropores. These materials are widely used in gas separations, catalysis, and energy storage and conversion. I’m especially interested in porous carbons for their versatility in offering chemical stability, electronic conductivity, and tunable porosity. Here our goal is to establish a structure-property relationship for porous carbons. For example, how can we relate the structure of a carbon molecular sieve (a type of porous carbon) to its O2/N2 separating power? How does a carbon’s porosity affect its performance in Li-S batteries? Structures for porous carbons can be built up from model systems or generated by reverse Monte Carlo simulations, while the property can be addressed by either first principles or classical approaches depending on the problem. Elucidating these structure-property relationships would deliver a fundamental progress in addressing porous carbons’ versatility.

Awards

Selected Publications

 

More Information 

General Campus Information

University of California, Riverside
900 University Ave.
Riverside, CA 92521
Tel: (951) 827-1012

Department Information

Department of Chemistry
Chemical Sciences
501 Big Springs Road

Tel: (951) 827-3789 (Chair's Assistant)
Fax: (951) 827-2435 (confidential)
E-mail: jingsong.zhang@ucr.edu

Footer