Matthew R. Carbone

866 total citations
39 papers, 617 citations indexed

About

Matthew R. Carbone is a scholar working on Materials Chemistry, Computational Theory and Mathematics and Electrical and Electronic Engineering. According to data from OpenAlex, Matthew R. Carbone has authored 39 papers receiving a total of 617 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Materials Chemistry, 8 papers in Computational Theory and Mathematics and 8 papers in Electrical and Electronic Engineering. Recurrent topics in Matthew R. Carbone's work include Machine Learning in Materials Science (16 papers), X-ray Diffraction in Crystallography (12 papers) and Computational Drug Discovery Methods (7 papers). Matthew R. Carbone is often cited by papers focused on Machine Learning in Materials Science (16 papers), X-ray Diffraction in Crystallography (12 papers) and Computational Drug Discovery Methods (7 papers). Matthew R. Carbone collaborates with scholars based in United States, South Korea and Netherlands. Matthew R. Carbone's co-authors include Deyu Lu, Shinjae Yoo, Mehmet Topsakal, Joseph H. Montoya, Brian A. Rohr, Yang Ha, Santosh K. Suram, Steven B. Torrisi, Linda Hung and Junko Yano and has published in prestigious journals such as Journal of the American Chemical Society, Physical Review Letters and The Journal of Chemical Physics.

In The Last Decade

Matthew R. Carbone

36 papers receiving 603 citations

Peers

Countries citing papers authored by Matthew R. Carbone

Since Specialization

Citations

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

Fields of papers citing papers by Matthew R. Carbone

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew R. Carbone. 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 Matthew R. Carbone. The network helps show where Matthew R. Carbone may publish in the future.

Co-authorship network of co-authors of Matthew R. Carbone

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew R. Carbone. A scholar is included among the top collaborators of Matthew R. Carbone 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 Matthew R. Carbone. Matthew R. Carbone 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

#	Work	Indexed citations
1	Single-Node Power Demand During AI Training: Measurements on an 8-GPU NVIDIA H100 System 2025 ·IEEE Access ·(unknown), (unknown), Matthew R. Carbone, Arslan Munir, Yuewei Lin, Jonathan Koomey, Xi Yu, (unknown)	3
2	Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential 2025 ·SHILAP Revista de lepidopterología ·Chuntian Cao, (unknown), (unknown), (unknown), Lei Wang, Chunyi Zhang, Matthew R. Carbone, Hubertus J. J. van Dam, Shinjae Yoo, Shan Yan, Esther S. Takeuchi, Kenneth J. Takeuchi, Xifan Wu, Milinda Abeykoon, Amy C. Marschilok, Deyu Lu	2
3	Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE 2025 ·Journal of Applied Crystallography ·(unknown), (unknown), Matthew R. Carbone, (unknown), (unknown), Yugang Zhang, Arthi Jayaraman	0
4	Machine learning for the advancement of membrane science and technology: A critical review 2024 ·Journal of Membrane Science ·Gergő Ignácz, (unknown), (unknown), (unknown), (unknown), Hakkim Vovusha, Matthew R. Carbone, Bernard Ghanem, György Székely	34
5	Machine learning-guided discovery of polymer membranes for CO2 separation with genetic algorithm 2024 ·Journal of Membrane Science ·Yasemin Basdogan, (unknown), (unknown), Matthew R. Carbone, Sanat K. Kumar, Zhen‐Gang Wang	13
6	Prediction of the Cu Oxidation State from EELS and XAS Spectra Using Supervised Machine Learning 2024 ·Microscopy and Microanalysis ·(unknown), Matthew R. Carbone, Deyu Lu, Jim Ciston	2
7	In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination 2024 ·Small Methods ·(unknown), (unknown), Jianming Bai, Hubertus J. J. van Dam, Matthew R. Carbone, (unknown), Hui Zhong, Akhil Tayal, Lu Ma, Özgenur Kahvecioğlu, Krzysztof Pupek, Deyu Lu, Krishna Rajan, Feng Wang	0
8	Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models 2024 ·Machine Learning Science and Technology ·Hyuna Kwon, Tim Hsu, Wenyu Sun, Wonseok Jeong, Fikret Aydin, James Chapman, Xiaohong Chen, Vincenzo Lordi, Matthew R. Carbone, Deyu Lu, Fei Zhou, Tuan Anh Pham	8
9	Machine learning-based discovery of molecular descriptors that control polymer gas permeation 2024 ·Journal of Membrane Science ·(unknown), Yasemin Basdogan, Zhen‐Gang Wang, Sanat K. Kumar, Matthew R. Carbone	7
10	Uncertainty-aware predictions of molecular x-ray absorption spectra using neural network ensembles 2023 ·Physical Review Research ·(unknown), (unknown), (unknown), Zhu Liang, Mark S. Hybertsen, Xiaohui Qu, Eli Stavitski, Shinjae Yoo, Deyu Lu, Matthew R. Carbone	19
11	Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes 2023 ·Scientific Data ·Haoyue Guo, Matthew R. Carbone, Chuntian Cao, Jianzhou Qu, Yonghua Du, Seong‐Min Bak, Conan Weiland, (unknown), Shinjae Yoo, Nongnuch Artrith, Alexander Urban, Deyu Lu	19
12	Self-driving multimodal studies at user facilities 2023 ·Acta Crystallographica Section A Foundations and Advances ·Phillip M. Maffettone, Daniel Allan, Stuart I. Campbell, Matthew R. Carbone, Thomas A Caswell, Brian DeCost, (unknown), Marcus D. Hanwell, Howie Joress, Joshua Lynch, Bruce Ravel, S. B. Wilkins, (unknown), Daniel Olds	1
13	Flexible formulation of value for experiment interpretation and design 2023 ·Matter ·Matthew R. Carbone, Hyeong Jin Kim, (unknown), Shinjae Yoo, Daniel Olds, Howie Joress, Brian DeCost, Bruce Ravel, Yugang Zhang, Phillip M. Maffettone	4
14	Lightshow: a Python package for generatingcomputational x-ray absorption spectroscopy input files 2023 ·The Journal of Open Source Software ·Matthew R. Carbone, (unknown), Christian Vorwerk, (unknown), (unknown), Xiaohui Qu, Eli Stavitski, Claudia Draxl, John Vinson, Deyu Lu	8
15	Competition between energy- and entropy-driven activation in glasses 2022 ·Physical review. E ·Matthew R. Carbone, Marco Baity‐Jesi	2
16	Bond-Peierls polaron: Moderate mass enhancement and current-carrying ground state 2021 ·Physical review. B. ·Matthew R. Carbone, Andrew J. Millis, David R. Reichman, John Sous	18
17	Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships 2020 ·npj Computational Materials ·Steven B. Torrisi, Matthew R. Carbone, Brian A. Rohr, Joseph H. Montoya, Yang Ha, Junko Yano, Santosh K. Suram, Linda Hung	133
18	Effective traplike activated dynamics in a continuous landscape 2020 ·Physical review. E ·Matthew R. Carbone, (unknown), Marco Baity‐Jesi	5
19	Using machine learning to predict local chemical environments from X-ray absorption spectra 2019 ·Bulletin of the American Physical Society ·Deyu Lu, Matthew R. Carbone, Mehmet Topsakal, Shinjae Yoo	4
20	Telehealth Technologies and Applications for Terrorism Response: A Report of the 2002 Coastal North Carolina Domestic Preparedness Training Exercise 2003 ·Journal of the American Medical Informatics Association ·Scott Simmons, (unknown), (unknown), (unknown), David A. Rosenthal, Matthew R. Carbone	26

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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