Johannes Hachmann

2.6k total citations · 1 hit paper
25 papers, 1.7k citations indexed

About

Johannes Hachmann is a scholar working on Materials Chemistry, Computational Theory and Mathematics and Physical and Theoretical Chemistry. According to data from OpenAlex, Johannes Hachmann has authored 25 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Materials Chemistry, 8 papers in Computational Theory and Mathematics and 7 papers in Physical and Theoretical Chemistry. Recurrent topics in Johannes Hachmann's work include Machine Learning in Materials Science (13 papers), Computational Drug Discovery Methods (8 papers) and Organic Electronics and Photovoltaics (4 papers). Johannes Hachmann is often cited by papers focused on Machine Learning in Materials Science (13 papers), Computational Drug Discovery Methods (8 papers) and Organic Electronics and Photovoltaics (4 papers). Johannes Hachmann collaborates with scholars based in United States, Mexico and Germany. Johannes Hachmann's co-authors include Garnet Kin‐Lic Chan, Alán Aspuru‐Guzik, Roberto Olivares‐Amaya, Şule Atahan-Evrenk, Carlos Amador‐Bedolla, Leslie Vogt-Maranto, Roel S. Sánchez‐Carrera, Takeshi Yanai, Debashree Ghosh and Aryeh Gold‐Parker and has published in prestigious journals such as The Journal of Chemical Physics, Energy & Environmental Science and The Journal of Physical Chemistry B.

In The Last Decade

Johannes Hachmann

24 papers receiving 1.7k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

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

2011 472 citations Johannes Hachmann, Roberto Olivares‐Amaya et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Johannes Hachmann United States	15	941	541	484	341	198	25	1.7k
Roberto Olivares‐Amaya United States	12	786 0.8×	451 0.8×	463 1.0×	244 0.7×	140 0.7×	15	1.5k
Álvaro Vázquez‐Mayagoitia United States	21	1.0k 1.1×	418 0.8×	281 0.6×	326 1.0×	85 0.4×	45	1.6k
Steven A. Lopez United States	21	656 0.7×	457 0.8×	216 0.4×	134 0.4×	209 1.1×	60	1.7k
Konstantinos D. Vogiatzis United States	28	1.6k 1.7×	299 0.6×	266 0.5×	211 0.6×	268 1.4×	78	3.1k
Tomomi Shimazaki Japan	20	709 0.8×	391 0.7×	423 0.9×	147 0.4×	62 0.3×	63	1.4k
Yaolong Zhang China	26	959 1.0×	361 0.7×	703 1.5×	234 0.7×	56 0.3×	75	1.6k
Thijs Stuyver Belgium	27	780 0.8×	788 1.5×	499 1.0×	223 0.7×	54 0.3×	56	2.2k
Nicola Molinari United States	14	1.0k 1.1×	653 1.2×	151 0.3×	287 0.8×	147 0.7×	23	1.8k
Martin Korth Germany	23	540 0.6×	543 1.0×	735 1.5×	184 0.5×	88 0.4×	36	2.1k
Kjell Jorner Sweden	21	935 1.0×	370 0.7×	144 0.3×	243 0.7×	53 0.3×	44	1.8k

Countries citing papers authored by Johannes Hachmann

Since Specialization

Citations

This map shows the geographic impact of Johannes Hachmann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Johannes Hachmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johannes Hachmann more than expected).

Fields of papers citing papers by Johannes Hachmann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Johannes Hachmann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Johannes Hachmann. The network helps show where Johannes Hachmann may publish in the future.

Co-authorship network of co-authors of Johannes Hachmann

This figure shows the co-authorship network connecting the top 25 collaborators of Johannes Hachmann. A scholar is included among the top collaborators of Johannes Hachmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Johannes Hachmann. Johannes Hachmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Hachmann, Johannes, et al.. (2021). Metrics for Benchmarking and Uncertainty Quantification: Quality, Applicability, and Best Practices for Machine Learning in Chemistry. Trends in Chemistry. 3(2). 146–156. 37 indexed citations

2.

Hanwell, Marcus D., Chris Harris, Mojtaba Haghighatlari, et al.. (2020). Open Chemistry, JupyterLab, REST, and quantum chemistry. International Journal of Quantum Chemistry. 121(1). 8 indexed citations

3.

Haghighatlari, Mojtaba, et al.. (2020). ChemML : A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data. Wiley Interdisciplinary Reviews Computational Molecular Science. 10(4). 46 indexed citations

4.

Ferguson, Andrew L., Johannes Hachmann, Thomas F. Miller, & Jim Pfaendtner. (2020). The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry. The Journal of Physical Chemistry A. 124(44). 9113–9118.

5.

Ferguson, Andrew L., Johannes Hachmann, Thomas F. Miller, & Jim Pfaendtner. (2020). The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry. The Journal of Physical Chemistry B. 124(44). 9767–9772. 3 indexed citations

6.

Ferguson, Andrew L., Johannes Hachmann, Thomas F. Miller, & Jim Pfaendtner. (2020). The Journal of Physical Chemistry A/B/C Virtual Special Issue on Machine Learning in Physical Chemistry. The Journal of Physical Chemistry C. 124(44). 24033–24038. 3 indexed citations

7.

Afzal, Mohammad Atif Faiz, et al.. (2019). A deep neural network model for packing density predictions and its application in the study of 1.5 million organic molecules. Chemical Science. 10(36). 8374–8383. 30 indexed citations

8.

Afzal, Mohammad Atif Faiz, et al.. (2019). Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining. The Journal of Physical Chemistry C. 123(23). 14610–14618. 37 indexed citations

9.

Ferguson, Andrew L. & Johannes Hachmann. (2018). Machine learning and data science in materials design: a themed collection. Molecular Systems Design & Engineering. 3(3). 429–430. 4 indexed citations

10.

Hachmann, Johannes, et al.. (2018). Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space. Molecular Simulation. 44(11). 921–929. 23 indexed citations

11.

Asatryan, Rubik, et al.. (2018). Roaming-like Mechanism for Dehydration of Diol Radicals. The Journal of Physical Chemistry A. 122(51). 9738–9754. 8 indexed citations

12.

Afzal, Mohammad Atif Faiz, et al.. (2017). ChemHTPS - A virtual high-throughput screening program suite for the chemical and materials sciences. Bulletin of the American Physical Society. 2017. 2 indexed citations

13.

Asatryan, Rubik, Eli Ruckenstein, & Johannes Hachmann. (2017). Revisiting the polytopal rearrangements in penta-coordinate d⁷-metallocomplexes: modified Berry pseudorotation, octahedral switch, and butterfly isomerization. Chemical Science. 8(8). 5512–5525. 20 indexed citations

14.

Lopez, Steven A., Edward O. Pyzer‐Knapp, Gregor N. C. Simm, et al.. (2016). The Harvard organic photovoltaic dataset. Scientific Data. 3(1). 160086–160086. 99 indexed citations

15.

Ertunç, Özgür, et al.. (2015). High-speed visualization of acoustically excited cavitation bubbles in a cluster near a rigid boundary. Journal of Visualization. 20(2). 359–368. 13 indexed citations

16.

Hachmann, Johannes, Roberto Olivares‐Amaya, Adrián Jinich, et al.. (2013). Lead candidates for high-performance organic photovoltaics from high-throughput quantum chemistry – the Harvard Clean Energy Project. Energy & Environmental Science. 7(2). 698–704. 189 indexed citations

17.

Hachmann, Johannes, Roberto Olivares‐Amaya, Şule Atahan-Evrenk, Carlos Amador‐Bedolla, & Alán Aspuru‐Guzik. (2011). The Harvard Clean Energy Project. Large-scale computational screening and design of molecular motifs for organic photovoltaics on the World Community Grid. Bulletin of the American Physical Society. 2011. 11 indexed citations

18.

Hachmann, Johannes, et al.. (2011). A Theoretical Study of the 3d‐M(smif)₂ Complexes: Structure, Magnetism, and Oxidation States. ChemPhysChem. 12(17). 3236–3244. 8 indexed citations

19.

Hachmann, Johannes, et al.. (2006). Multireference correlation in long molecules with the quadratic scaling density matrix renormalization group. The Journal of Chemical Physics. 125(14). 144101–144101. 151 indexed citations

20.

Hachmann, Johannes, Peter T. A. Galek, Takeshi Yanai, Garnet Kin‐Lic Chan, & Nicholas C. Handy. (2004). The nodes of Hartree–Fock wavefunctions and their orbitals. Chemical Physics Letters. 392(1-3). 55–61. 21 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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