Materials Project
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Promising Directions and the Tools to Get Us There
At the halfway point in our five-year charter, we have narrowed our research directions within the three promising energy storage concepts we are pursuing: multivalent intercalation, chemical transformation, non-aqueous redox flow. In converging these directions to proof-of-concept prototypes, we make extensive use of JCESR’s distinguishing tools. Read More
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Spinel Compounds as Multivalent Battery Cathodes: A Systematic Evaluation Based on ab initio Calculations
A high-throughput strategy to systematically screen multivalent cathode materials based on comprehensive computational first-principles property evaluations has been developed and has been used to identify Mn2O4 as a feasible host candidate, with Ca2+ and possibly Mg2+ as mobile cations Read More
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Screening of Novel Multivalent Cathodes
Developed strategies and software infrastructure for generation and design of multivalent intercalation candidates Read More
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Architecture-Controlled Ring-Opening Polymerization for Dynamic Covalent Poly(disulfide)s
We reported a strategy to access different topologies of redox-active poly(disulfide)s by ring-opening polymerization. Control over polymerization enables synthesis of high molecular-weight polymers. The polymers undergo catalytic depolymerization to recycle monomer; a promising feature for sustainable flow batteries. Read More
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Adsorption and Thermal Decomposition of Electrolytes on Nanometer Magnesium Oxide: An in Situ 13C MAS NMR Study
The structural and chemical evolution of electrolyte constituents at the nanometric MgO surface were identified, providing a fundamental understanding of heterogeneous interphase evolution. Read More
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Mechanism-Based Design of a High-Potential Catholyte Enables a 3.2 V All-Organic Nonaqueous Redox Flow Battery
Development of an extremely high-potential catholyte leads to the first 3.2 V all-organic flow battery. Read More
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Shedding X‑ray Light on the Interfacial Electrochemistry of Silicon Anodes for Li-Ion Batteries
Our results shed light on the interfacial electrochemistry of silicon anodes for Lithium-ion batteries (LiBs), providing important mechanistic insight into nanometer scale phenomena and how these influence battery performance. Read More
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Accelerating Electrolyte Discovery for Energy Storage through Machine Learning
Utilized high performance computing to generate a database of highly accurate quantum chemical energies of 133 K organic molecules and used machine learning to enable prediction of energies from low fidelity, low cost quantum chemical calculations. Read More
