Artur M. Schweidtmann

3.2k total citations · 1 hit paper
65 papers, 2.1k citations indexed

About

Artur M. Schweidtmann is a scholar working on Control and Systems Engineering, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Artur M. Schweidtmann has authored 65 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Control and Systems Engineering, 23 papers in Computational Theory and Mathematics and 20 papers in Materials Chemistry. Recurrent topics in Artur M. Schweidtmann's work include Machine Learning in Materials Science (18 papers), Process Optimization and Integration (17 papers) and Advanced Control Systems Optimization (13 papers). Artur M. Schweidtmann is often cited by papers focused on Machine Learning in Materials Science (18 papers), Process Optimization and Integration (17 papers) and Advanced Control Systems Optimization (13 papers). Artur M. Schweidtmann collaborates with scholars based in Netherlands, Germany and United Kingdom. Artur M. Schweidtmann's co-authors include Alexei A. Lapkin, Alexander Mitsos, Eric Bradford, Adam D. Clayton, Richard A. Bourne, Nicholas Holmes, Manuel Dahmen, Jan G. Rittig, Dongda Zhang and Jana M. Weber and has published in prestigious journals such as Chemical Society Reviews, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Artur M. Schweidtmann

58 papers receiving 2.0k 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.

Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives

2018 255 citations Artur M. Schweidtmann, Eric Bradford et al. Chemical Engineering Journal profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Artur M. Schweidtmann Netherlands	26	628	621	558	399	319	65	2.1k
Mario R. Eden United States	26	965 1.5×	686 1.1×	361 0.6×	326 0.8×	453 1.4×	72	2.2k
Vassilios S. Vassiliadis United Kingdom	26	1.2k 1.8×	345 0.6×	305 0.5×	241 0.6×	213 0.7×	88	2.5k
Argimiro R. Secchi Brazil	25	579 0.9×	683 1.1×	340 0.6×	78 0.2×	300 0.9×	220	2.3k
Sandro Macchietto United Kingdom	34	1.9k 3.1×	692 1.1×	384 0.7×	499 1.3×	511 1.6×	129	3.9k
Alexander W. Dowling United States	22	449 0.7×	376 0.6×	277 0.5×	140 0.4×	325 1.0×	76	1.6k
Daniel R. Lewin Israel	23	1.4k 2.2×	464 0.7×	253 0.5×	209 0.5×	590 1.8×	95	2.6k
Fani Boukouvala United States	25	799 1.3×	240 0.4×	155 0.3×	468 1.2×	689 2.2×	50	2.2k
Harvey Arellano‐García Germany	30	690 1.1×	480 0.8×	1.1k 1.9×	111 0.3×	507 1.6×	143	2.8k
José A. Romagnoli United States	36	2.5k 4.0×	518 0.8×	674 1.2×	154 0.4×	685 2.1×	281	4.3k
Chrysanthos E. Gounaris United States	21	651 1.0×	214 0.3×	332 0.6×	240 0.6×	175 0.5×	60	1.8k

Countries citing papers authored by Artur M. Schweidtmann

Since Specialization

Citations

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

Fields of papers citing papers by Artur M. Schweidtmann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Artur M. Schweidtmann

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

Schweidtmann, Artur M., et al.. (2025). Graph-to-SFILES: Control structure prediction from process topologies using generative artificial intelligence. Computers & Chemical Engineering. 199. 109121–109121. 1 indexed citations

Schweidtmann, Artur M., et al.. (2025). Multi-agent systems for chemical engineering: a review and perspective. Current Opinion in Chemical Engineering. 51. 101209–101209.

Schweidtmann, Artur M.. (2024). Mining Chemical Process Information from Literature for Generative Process Design: A Perspective. 3. 84–91.

Gao, Qinghe, et al.. (2024). Self-supervised graph neural networks for polymer property prediction. Molecular Systems Design & Engineering. 9(11). 1130–1143. 5 indexed citations

Daoutidis, Pródromos, Jay H. Lee, Srinivas Rangarajan, et al.. (2023). Machine learning in process systems engineering: Challenges and opportunities. Computers & Chemical Engineering. 181. 108523–108523. 47 indexed citations

Schweidtmann, Artur M., et al.. (2023). Data-driven product-process optimization of N-isopropylacrylamide microgel flow-synthesis. Chemical Engineering Journal. 479. 147567–147567. 8 indexed citations

Schweidtmann, Artur M., Jan G. Rittig, Jana M. Weber, et al.. (2023). Physical pooling functions in graph neural networks for molecular property prediction. Computers & Chemical Engineering. 172. 108202–108202. 27 indexed citations

Schweidtmann, Artur M., et al.. (2023). Toward automatic generation of control structures for process flow diagrams with large language models. AIChE Journal. 70(1). 25 indexed citations

Stocker, Markus, Tina Heger, Artur M. Schweidtmann, et al.. (2022). SKG4EOSC - Scholarly Knowledge Graphs for EOSC: Establishing a backbone of knowledge graphs for FAIR Scholarly Information in EOSC. SHILAP Revista de lepidopterología. 8. 5 indexed citations

10.

Rittig, Jan G., Artur M. Schweidtmann, Jana M. Weber, et al.. (2022). Graph machine learning for design of high‐octane fuels. AIChE Journal. 69(4). 22 indexed citations

11.

Schweidtmann, Artur M., et al.. (2022). Digitization of chemical process flow diagrams using deep convolutional neural networks. SHILAP Revista de lepidopterología. 6. 100072–100072. 31 indexed citations

12.

Schweidtmann, Artur M., Erik Esche, Asja Fischer, et al.. (2021). Machine Learning in Chemical Engineering: A Perspective. Chemie Ingenieur Technik. 93(12). 2029–2039. 157 indexed citations

13.

Russo, Danilo, et al.. (2021). Multi-objective Bayesian optimisation of a two-step synthesis of p-cymene from crude sulphate turpentine. Chemical Engineering Science. 247. 116938–116938. 30 indexed citations

14.

König, Andrea, Artur M. Schweidtmann, Jan G. Rittig, et al.. (2021). Designing production-optimal alternative fuels for conventional, flexible-fuel, and ultra-high efficiency engines. Chemical Engineering Science. 237. 116562–116562. 20 indexed citations

15.

Schweidtmann, Artur M., et al.. (2020). Globally optimal working fluid mixture composition for geothermal power cycles. Energy. 212. 118731–118731. 10 indexed citations

16.

Rall, Deniz, et al.. (2020). Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning. Journal of Membrane Science. 608. 118208–118208. 54 indexed citations

17.

Schweidtmann, Artur M., et al.. (2019). Working fluid selection for organic rankine cycles via deterministic global optimization of design and operation. Optimization and Engineering. 21(2). 517–536. 25 indexed citations

18.

Schweidtmann, Artur M., et al.. (2018). Deterministic global process optimization: Accurate (single-species) properties via artificial neural networks. Computers & Chemical Engineering. 121. 67–74. 38 indexed citations

19.

Bradford, Eric, Artur M. Schweidtmann, & Alexei A. Lapkin. (2018). Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm. Journal of Global Optimization. 71(2). 439–440. 9 indexed citations

20.

Schweidtmann, Artur M., et al.. (2017). The concept of selectivity control by simultaneous distribution of the oxygen feed and wall temperature in a microstructured reactor. Chemical Engineering Journal. 331. 765–776. 7 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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