Johannes Hachmann

发表

ChemHTPS - A virtual high-throughput screening program suite for the chemical and materials sciences

Mohammad Atif Faiz Afzal, William Evangelista, Johannes Hachmann, 2017 .

The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid

Alán Aspuru-Guzik, Roberto Olivares-Amaya, Carlos Amador-Bedolla, 2011 .

Accelerated computational discovery of high-performance materials for organic photovoltaics by means of cheminformatics

Alán Aspuru-Guzik, Roberto Olivares-Amaya, Carlos Amador-Bedolla, 2011 .

The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry

Andrew L. Ferguson, Thomas F. Miller, Johannes Hachmann, 2020 .

Machine learning and data science in materials design: a themed collection

Johannes Hachmann, Andrew Ferguson, J. Hachmann, 2018 .

The Harvard organic photovoltaic dataset

Alán Aspuru-Guzik, Edward O. Pyzer-Knapp, Kewei Li, 2016, Scientific Data.

The radical character of the acenes: a density matrix renormalization group study.

Garnet Kin-Lic Chan, Johannes Hachmann, Jonathan J. Dorando, 2007, The Journal of chemical physics.

First-principles screening and design of organic photovoltaic materials on the World Community Grid

Alán Aspuru-Guzik, Roberto Olivares-Amaya, Johannes Hachmann, 2010 .

Fundamentals of Chemical Design and Engineering - Panel Discussion

Rigoberto Hernandez, Kai Leonhard, Johannes Hachmann, 2018 .

Lead candidates for high-performance organic photovoltaics from high-throughput quantum chemistry – the Harvard Clean Energy Project

Alán Aspuru-Guzik, Zhenan Bao, Süleyman Er, 2014 .

The Harvard Clean Energy Project: High-throughput screening of organic photovoltaic materials using first-principles electronic structure theory

Alán Aspuru-Guzik, Roberto Olivares-Amaya, Carlos Amador-Bedolla, 2012 .

The Harvard Clean Energy Project: High-throughput screening of organic photovoltaic materials using cheminformatics, machine learning, and pattern recognition

Alán Aspuru-Guzik, Sergio Boixo, Roberto Olivares-Amaya, 2012 .

Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space

Mohammad Atif Faiz Afzal, Johannes Hachmann, Mojtaba Haghighatlari, 2018 .

ChemML: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data

Srirangaraj Setlur, Bhargava Urala Kota, Johannes Hachmann, 2020 .

The Harvard Clean Energy Project. Large-scale computational screening and design of molecular motifs for organic photovoltaics on the World Community Grid

Alán Aspuru-Guzik, Roberto Olivares-Amaya, Carlos Amador-Bedolla, 2011 .

Topical Plenary: Topical Conference in Molecular and Materials Data Science (Invited Talks)

Jim Pfaendtner, Elizabeth Nance, Johannes Hachmann, 2019 .

Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and a Path to Best Practices for Machine Learning in Chemistry pdf

Johannes Hachmann, Gaurav Vishwakarma, Aditya Sonpal, 2020, ArXiv.

Accelerated Discovery of High-Refractive-Index Polymers Using First-Principles Modeling, Virtual High-Throughput Screening, and Data Mining

Chong Cheng, Mohammad Atif Faiz Afzal, Johannes Hachmann, 2017 .

The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry.

Jim Pfaendtner, Andrew L. Ferguson, Thomas F. Miller, 2020, The journal of physical chemistry. B.

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

Mohammad Atif Faiz Afzal, Johannes Hachmann, Chong Cheng, 2019, The Journal of Physical Chemistry C.

High-speed visualization of acoustically excited cavitation bubbles in a cluster near a rigid boundary

Antonio Delgado, Özgür Ertunç, Johannes Hachmann, 2017, J. Vis..

Multireference correlation in long molecules with the quadratic scaling density matrix renormalization group.

Garnet Kin-Lic Chan, Johannes Hachmann, Wim Cardoen, 2006, The Journal of chemical physics.

Analytic response theory for the density matrix renormalization group.

Garnet Kin-Lic Chan, Johannes Hachmann, Jonathan J. Dorando, 2009, The Journal of chemical physics.

Combining first-principles and data modeling for the accurate prediction of the refractive index of organic polymers.

Chong Cheng, Mohammad Atif Faiz Afzal, Johannes Hachmann, 2018, The Journal of chemical physics.

Orbital optimization in the density matrix renormalization group, with applications to polyenes and beta-carotene.

Debashree Ghosh, Johannes Hachmann, Takeshi Yanai, 2007, The Journal of chemical physics.

ChemML: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data

Srirangaraj Setlur, Bhargava Urala Kota, Johannes Hachmann, 2019, WIREs Computational Molecular Science.

An Introduction to the Density Matrix Renormalization Group Ansatz in Quantum Chemistry

Debashree Ghosh, Garnet Kin-Lic Chan, Johannes Hachmann, 2007, 0711.1398.