ORCID Profile
0000-0002-0421-006X
Current Organisation
Yale University
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Publisher: Elsevier BV
Date: 04-2021
Publisher: Elsevier BV
Date: 04-2019
Publisher: Wiley
Date: 13-03-2019
Publisher: Royal Society of Chemistry (RSC)
Date: 2017
DOI: 10.1039/C7TA03624H
Abstract: Defects have been engineering on the atomically-thin BiOCl nanosheets to tune the electronic structure, build abundant coordination-unsaturated active atoms with dangling bonds acts as active sites and shortens the migration distance of holes to promote holes utilization.
Publisher: Elsevier BV
Date: 11-2020
Publisher: American Chemical Society (ACS)
Date: 30-12-2020
DOI: 10.1021/ACS.NANOLETT.9B04719
Abstract: Lithium-sulfur (Li-S) batteries are promising next-generation energy storage technologies due to their high theoretical energy density, environmental friendliness, and low cost. However, low conductivity of sulfur species, dissolution of polysulfides, poor conversion from sulfur reduction, and lithium sulfide (Li
Publisher: American Chemical Society (ACS)
Date: 20-09-2018
Publisher: Wiley
Date: 14-11-2020
Publisher: Wiley
Date: 07-2019
Publisher: Springer Science and Business Media LLC
Date: 25-03-2021
DOI: 10.1038/S41524-021-00507-7
Abstract: Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or chemical segregation. In these cases, the details of atomic arrangements are generally not explored and analyzed. The knowledge of the generative physics and chemistry of the material can obviate this problem, since defect configuration libraries as stochastic representation of atomic level structures can be generated, or parameters of mesoscopic thermodynamic models can be derived. To obtain such information for improved predictions, we use data from atomically resolved microscopic images that visualize complex structural correlations within the system and translate them into statistical mechanical models of structure formation. Given the significant uncertainties about the microscopic aspects of the material’s processing history along with the limited number of available images, we combine model optimization techniques with the principles of statistical hypothesis testing. We demonstrate the approach on data from a series of atomically-resolved scanning transmission electron microscopy images of Mo x Re 1- x S 2 at varying ratios of Mo/Re stoichiometries, for which we propose an effective interaction model that is then used to generate atomic configurations and make testable predictions at a range of concentrations and formation temperatures.
Publisher: Wiley
Date: 09-02-2018
Abstract: Single‐atom catalysts (SACs) are the smallest entities for catalytic reactions with projected high atomic efficiency, superior activity, and selectivity however, practical applications of SACs suffer from a very low metal loading of 1–2 wt%. Here, a class of SACs based on atomically dispersed transition metals on nitrogen‐doped carbon nanotubes (MSA‐N‐CNTs, where M = Ni, Co, NiCo, CoFe, and NiPt) is synthesized with an extraordinarily high metal loading, e.g., 20 wt% in the case of NiSA‐N‐CNTs, using a new multistep pyrolysis process. Among these materials, NiSA‐N‐CNTs show an excellent selectivity and activity for the electrochemical reduction of CO 2 to CO, achieving a turnover frequency (TOF) of 11.7 s −1 at −0.55 V (vs reversible hydrogen electrode (RHE)), two orders of magnitude higher than Ni nanoparticles supported on CNTs.
No related grants have been discovered for Shize Yang.