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Roberto Olivares-Amaya

Researcher at Harvard University

Publications -  26
Citations -  4278

Roberto Olivares-Amaya is an academic researcher from Harvard University. The author has contributed to research in topics: Density functional theory & Time-dependent density functional theory. The author has an hindex of 15, co-authored 26 publications receiving 3676 citations. Previous affiliations of Roberto Olivares-Amaya include Princeton University & National Autonomous University of Mexico.

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Advances in molecular quantum chemistry contained in the Q-Chem 4 program package

Yihan Shao, +156 more
- 17 Jan 2015 - 
TL;DR: A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided in this paper, covering approximately the last seven years, including developments in density functional theory and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces.
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The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid

TL;DR: This Perspective introduces the Harvard Clean Energy Project (CEP), a theory-driven search for the next generation of organic solar cell materials, and gives a broad overview of its setup and infrastructure, present first results, and outline upcoming developments.
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The ab-initio density matrix renormalization group in practice

TL;DR: By examining a diverse benchmark set of molecules, including π-electron systems, benchmark main-group and transition metal dimers, and the Mn-oxo-salen and Fe-porphine organometallic compounds, some answers are provided to questions about the density matrix renormalization group and how it is used in practice.
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Accelerated computational discovery of high-performance materials for organic photovoltaics by means of cheminformatics

TL;DR: This work focuses on the development of donor materials for organic photovoltaics by means of a cheminformatics approach, and forms empirical models, parametrized using a training set of donor polymers with available experimental data, for the important current–voltage and efficiency characteristics of candidate molecules.