Logan Ward

7.2k total citations · 4 hit papers
77 papers, 4.7k citations indexed

About

Logan Ward is a scholar working on Materials Chemistry, Computational Theory and Mathematics and Mechanical Engineering. According to data from OpenAlex, Logan Ward has authored 77 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Materials Chemistry, 14 papers in Computational Theory and Mathematics and 10 papers in Mechanical Engineering. Recurrent topics in Logan Ward's work include Machine Learning in Materials Science (36 papers), X-ray Diffraction in Crystallography (15 papers) and Computational Drug Discovery Methods (14 papers). Logan Ward is often cited by papers focused on Machine Learning in Materials Science (36 papers), X-ray Diffraction in Crystallography (15 papers) and Computational Drug Discovery Methods (14 papers). Logan Ward collaborates with scholars based in United States, United Kingdom and Egypt. Logan Ward's co-authors include Ankit Agrawal, Christopher Wolverton, Alok Choudhary, Chris Wolverton, Ian Foster, Apurva Mehta, Kyle Chard, Jason Hattrick‐Simpers, Kevin J. Laws and Fang Ren and has published in prestigious journals such as Nature Communications, Chemistry of Materials and Physical Review B.

In The Last Decade

Logan Ward

74 papers receiving 4.6k citations

Hit Papers

align trajectories

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.

A general-purpose machine learning framework for predicting properties of inorganic materials

2016 1.2k citations Logan Ward, Ankit Agrawal et al. npj Computational Materials profile →
Matminer: An open source toolkit for materials data mining

2018 675 citations Logan Ward, Kyle Chard et al. profile →
Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

2018 408 citations Logan Ward, Christopher Wolverton et al. profile →
ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition

2018 334 citations Logan Ward, Alok Choudhary et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Logan Ward United States	24	3.5k	930	867	792	351	77	4.7k
Chiho Kim United States	28	3.2k 0.9×	584 0.6×	1.2k 1.4×	900 1.1×	646 1.8×	65	4.6k
Rohit Batra United States	28	3.2k 0.9×	478 0.5×	1.3k 1.5×	793 1.0×	504 1.4×	54	4.6k
Taylor D. Sparks United States	31	3.0k 0.9×	512 0.6×	1.1k 1.3×	406 0.5×	339 1.0×	112	4.0k
Yunxing Zuo China	14	2.1k 0.6×	596 0.6×	1.0k 1.2×	434 0.5×	228 0.6×	26	3.1k
Bryce Meredig United States	27	5.4k 1.5×	1.1k 1.1×	1.5k 1.7×	777 1.0×	566 1.6×	43	6.7k
Ghanshyam Pilania United States	37	4.8k 1.4×	806 0.9×	1.6k 1.9×	930 1.2×	974 2.8×	103	6.4k
Kamal Choudhary United States	31	3.1k 0.9×	441 0.5×	806 0.9×	486 0.6×	456 1.3×	101	4.1k
Scott Kirklin United States	17	4.4k 1.2×	932 1.0×	1.6k 1.8×	511 0.6×	402 1.1×	23	5.5k
Prasanna V. Balachandran United States	31	3.2k 0.9×	720 0.8×	991 1.1×	487 0.6×	529 1.5×	76	4.3k
Daniel W. Davies United Kingdom	17	2.6k 0.7×	386 0.4×	810 0.9×	693 0.9×	393 1.1×	49	3.9k

Countries citing papers authored by Logan Ward

Since Specialization

Citations

This map shows the geographic impact of Logan Ward'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 Logan Ward with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Logan Ward more than expected).

Fields of papers citing papers by Logan Ward

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Logan Ward. 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 Logan Ward. The network helps show where Logan Ward may publish in the future.

Co-authorship network of co-authors of Logan Ward

This figure shows the co-authorship network connecting the top 25 collaborators of Logan Ward. A scholar is included among the top collaborators of Logan Ward 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 Logan Ward. Logan Ward is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Elliott, Sarah N., Logan Ward, Ian Foster, et al.. (2025). Accurate Dehydrogenation Enthalpies Dataset for Liquid Organic Hydrogen Carriers. Scientific Data. 12(1). 171–171. 2 indexed citations

Ward, Logan, et al.. (2024). Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning. npj Computational Materials. 10(1). 4 indexed citations

Allec, Sarah I., Eric S. Muckley, Nathan S. Johnson, et al.. (2024). A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community. Integrating materials and manufacturing innovation. 13(2). 406–419. 2 indexed citations

Ward, Logan, Steven R. Wangen, Marcus Schwarting, et al.. (2024). Foundry-ML - Software and Services to Simplify Accessto Machine Learning Datasets in Materials Science. The Journal of Open Source Software. 9(93). 5467–5467. 3 indexed citations

Borg, Christopher K. H., Eric S. Muckley, Clara Nyby, et al.. (2023). Quantifying the performance of machine learning models in materials discovery. Digital Discovery. 2(2). 327–338. 25 indexed citations

Elliott, Sarah N., Logan Ward, Ian Foster, et al.. (2023). Uncovering novel liquid organic hydrogen carriers: a systematic exploration of chemical compound space using cheminformatics and quantum chemical methods. Digital Discovery. 2(6). 1813–1830. 11 indexed citations

Hudson, Nathaniel, Logan Ward, Ryan Chard, et al.. (2023). Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. 1–10. 5 indexed citations

Ward, Logan, Heng Ma, Murali Emani, et al.. (2023). Protein Generation via Genome-scale Language Models with Bio-physical Scoring. 95–101. 3 indexed citations

Chen, Wei‐Ying, Zhi-Gang Mei, Logan Ward, et al.. (2023). In-situ TEM investigation of void swelling in nickel under irradiation with analysis aided by computer vision. Acta Materialia. 254. 119013–119013. 11 indexed citations

10.

Ward, Logan, John H. Perepezko, Dan J. Thoma, et al.. (2022). Machine Learning Prediction of the Critical Cooling Rate for Metallic Glasses from Expanded Datasets and Elemental Features. Chemistry of Materials. 34(7). 2945–2954. 18 indexed citations

11.

Sarker, Suchismita, James E. Saal, Logan Ward, et al.. (2022). Machine learned synthesizability predictions aided by density functional theory. Communications Materials. 3(1). 21 indexed citations

12.

Sivaraman, Ganesh, Logan Ward, Nathaniel C. Hoyt, et al.. (2021). Automated Development of Molten Salt Machine Learning Potentials: Application to LiCl. The Journal of Physical Chemistry Letters. 12(17). 4278–4285. 37 indexed citations

13.

Tchoua, Roselyne, Logan Ward, Kyle Chard, et al.. (2019). Active Learning Yields Better Training Data for Scientific Named Entity Recognition. 126–135. 9 indexed citations

14.

Hao, Shiqiang, Logan Ward, Zhong‐Zhen Luo, et al.. (2019). Design Strategy for High-Performance Thermoelectric Materials: The Prediction of Electron-Doped KZrCuSe₃. Chemistry of Materials. 31(8). 3018–3024. 26 indexed citations

15.

Blaiszik, Ben, Logan Ward, Marcus Schwarting, et al.. (2019). A data ecosystem to support machine learning in materials science. MRS Communications. 9(4). 1125–1133. 124 indexed citations

16.

Kim, Kyoungdoc, Logan Ward, Jiangang He, et al.. (2018). Accelerated Discovery of Quaternary Heusler with High-Throughput Density Functional Theory and Machine Learning. Bulletin of the American Physical Society. 2018. 1 indexed citations

17.

Ward, Logan, et al.. (2018). A machine learning approach for engineering bulk metallic glass alloys. Acta Materialia. 159. 102–111. 199 indexed citations

18.

Ward, Logan, Rosanne Liu, Vinay I. Hegde, et al.. (2016). Accurate Models of Formation Enthalpy Created using Machine Learning and Voronoi Tessellations. Bulletin of the American Physical Society. 2016. 1 indexed citations

19.

Ward, Logan. (2012). Predictive Modeling for Developing Novel Metallic Glass Alloys. OhioLink ETD Center (Ohio Library and Information Network). 2 indexed citations

20.

Glasson, Neil, et al.. (2012). Risk Mitigation in the Development of a Roebel Cable Based 1 MVA HTS Transformer. Physics Procedia. 36. 830–834. 2 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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