M. Ross Kunz

966 total citations
31 papers, 724 citations indexed

About

M. Ross Kunz is a scholar working on Materials Chemistry, Catalysis and Electrical and Electronic Engineering. According to data from OpenAlex, M. Ross Kunz has authored 31 papers receiving a total of 724 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Materials Chemistry, 13 papers in Catalysis and 8 papers in Electrical and Electronic Engineering. Recurrent topics in M. Ross Kunz's work include Catalytic Processes in Materials Science (13 papers), Catalysis and Oxidation Reactions (10 papers) and Machine Learning in Materials Science (7 papers). M. Ross Kunz is often cited by papers focused on Catalytic Processes in Materials Science (13 papers), Catalysis and Oxidation Reactions (10 papers) and Machine Learning in Materials Science (7 papers). M. Ross Kunz collaborates with scholars based in United States, Belgium and Italy. M. Ross Kunz's co-authors include Andrew J. Medford, Tammie L. Borders, John H. Kalivas, Eric J. Dufek, Bor‐Rong Chen, Tanvir R. Tanim, Erik Andries, Rebecca Fushimi, Yixiao Wang and Gregory S. Yablonsky and has published in prestigious journals such as Journal of the American Chemical Society, Analytical Chemistry and Journal of Agricultural and Food Chemistry.

In The Last Decade

M. Ross Kunz

31 papers receiving 709 citations

Peers

M. Ross Kunz

EEE

CATAL

Erik Esche Germany

Jiexiang Wang China

Jagdish Kumar India

Pieter Plehiers Belgium

Niranjan Sitapure United States

Juhwan Noh South Korea

Hanwen Zhang China

Rafael Méndez Puerto Rico

C. Zhang United Kingdom

Shuang Xia China

Erik Esche Germany

M. Ross Kunz

188 ×0.6

116 ×0.6

EEE

125 ×0.8

CATAL

41 ×0.3

19 ×0.2

Citations per year, relative to M. Ross Kunz M. Ross Kunz (= 1×) peers Erik Esche

Countries citing papers authored by M. Ross Kunz

Since Specialization

Citations

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

Fields of papers citing papers by M. Ross Kunz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Ross Kunz. 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 M. Ross Kunz. The network helps show where M. Ross Kunz may publish in the future.

Co-authorship network of co-authors of M. Ross Kunz

This figure shows the co-authorship network connecting the top 25 collaborators of M. Ross Kunz. A scholar is included among the top collaborators of M. Ross Kunz 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 M. Ross Kunz. M. Ross Kunz 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

Wang, Shengguang, et al.. (2025). Lowering the barrier to access information-rich transient kinetic data for machine learning methods. Journal of Catalysis. 450. 116306–116306. 3 indexed citations

Hansel, Joshua, et al.. (2023). Autonomous control of heat pipes through digital twins: Application to fission batteries. Progress in Nuclear Energy. 163. 104813–104813. 5 indexed citations

Wang, Yixiao, Sagar Sourav, Bingwen Wang, et al.. (2022). Deciphering the Mechanistic Role of Individual Oxide Phases and Their Combinations in Supported Mn–Na₂WO₄ Catalysts for Oxidative Coupling of Methane. ACS Catalysis. 12(19). 11886–11898. 24 indexed citations

Chen, Bor‐Rong, et al.. (2022). Battery aging mode identification across NMC compositions and designs using machine learning. Joule. 6(12). 2776–2793. 56 indexed citations

Batchu, Rakesh, et al.. (2022). Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters. AIChE Journal. 68(9). 4 indexed citations

Kim, Sang‐Wook, Zonggen Yi, M. Ross Kunz, et al.. (2022). Accelerated battery life predictions through synergistic combination of physics-based models and machine learning. Cell Reports Physical Science. 3(9). 101023–101023. 25 indexed citations

Kunz, M. Ross, Xiaolong He, Rakesh Batchu, et al.. (2022). Internal calibration of transient kinetic data via machine learning. Catalysis Today. 417. 113650–113650. 2 indexed citations

Sabharwall, Piyush, et al.. (2022). Digital Twin to Detect Nuclear Proliferation: A Case Study. Journal of Energy Resources Technology. 144(10). 12 indexed citations

Wang, Yixiao, Bingwen Wang, Sagar Sourav, et al.. (2022). Mechanistic pathways and role of oxygen in oxidative coupling of methane derived from transient kinetic studies. Catalysis Today. 417. 113739–113739. 8 indexed citations

10.

Chen, Yu‐Yen, M. Ross Kunz, Xiaolong He, & Rebecca Fushimi. (2022). Recent progress toward catalyst properties, performance, and prediction with data-driven methods. Current Opinion in Chemical Engineering. 37. 100843–100843. 8 indexed citations

11.

Slaughter, Andrew E., et al.. (2022). Foundations for a Fission Battery Digital Twin. Nuclear Technology. 208(7). 1089–1101. 9 indexed citations

12.

Chen, Bor‐Rong, M. Ross Kunz, Tanvir R. Tanim, & Eric J. Dufek. (2021). A machine learning framework for early detection of lithium plating combining multiple physics-based electrochemical signatures. Cell Reports Physical Science. 2(3). 100352–100352. 55 indexed citations

13.

Fang, Zongtang, Matthew P. Confer, Yixiao Wang, et al.. (2021). Formation of Surface Impurities on Lithium–Nickel–Manganese–Cobalt Oxides in the Presence of CO₂ and H₂O. Journal of the American Chemical Society. 143(27). 10261–10274. 33 indexed citations

14.

Wang, Yixiao, Jin Qian, Zongtang Fang, et al.. (2021). Understanding Reaction Networks through Controlled Approach to Equilibrium Experiments Using Transient Methods. Journal of the American Chemical Society. 143(29). 10998–11006. 12 indexed citations

15.

Talbot, Paul, Cristian Rabiti, Andrea Alfonsi, et al.. (2019). Correlated Synthetic Time Series Generation Using Fourier and ARMA. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 120(1). 465–468. 3 indexed citations

16.

Wang, Yixiao, M. Ross Kunz, Harry W. Rollins, et al.. (2019). Transient Kinetic Experiments within the High Conversion Domain: The Case of Ammonia Decomposition. Catalysts. 9(1). 104–104. 14 indexed citations

17.

Wang, Yixiao, M. Ross Kunz, Zongtang Fang, Gregory S. Yablonsky, & Rebecca Fushimi. (2019). Accumulation Dynamics as a New Tool for Catalyst Discrimination: An Example from Ammonia Decomposition. Industrial & Engineering Chemistry Research. 58(24). 10238–10248. 20 indexed citations

18.

Nair, Shyam K., et al.. (2018). Investigating the Efficacy of Integrating Energy Crops into Non-Profitable Subfields in Iowa. BioEnergy Research. 11(3). 623–637. 4 indexed citations

19.

Kunz, M. Ross & Yiyuan She. (2013). Multivariate calibration maintenance and transfer through robust fused LASSO. Journal of Chemometrics. 27(9). 233–242. 11 indexed citations

20.

Kunz, M. Ross, J. M. Ottaway, John H. Kalivas, Constantinos A. Georgiou, & George A. Mousdis. (2011). Updating a Synchronous Fluorescence Spectroscopic Virgin Olive Oil Adulteration Calibration to a New Geographical Region. Journal of Agricultural and Food Chemistry. 59(4). 1051–1057. 31 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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