Daniel Marchand

941 total citations
8 papers, 368 citations indexed

About

Daniel Marchand is a scholar working on Materials Chemistry, Aerospace Engineering and Metals and Alloys. According to data from OpenAlex, Daniel Marchand has authored 8 papers receiving a total of 368 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Materials Chemistry, 5 papers in Aerospace Engineering and 2 papers in Metals and Alloys. Recurrent topics in Daniel Marchand's work include Aluminum Alloy Microstructure Properties (5 papers), Machine Learning in Materials Science (4 papers) and X-ray Diffraction in Crystallography (2 papers). Daniel Marchand is often cited by papers focused on Aluminum Alloy Microstructure Properties (5 papers), Machine Learning in Materials Science (4 papers) and X-ray Diffraction in Crystallography (2 papers). Daniel Marchand collaborates with scholars based in Switzerland, Austria and United States. Daniel Marchand's co-authors include W.A. Curtin, Abhinav Jain, Albert Glensk, W. A. Curtin, David L. McDowell, Xiao Zhou, Jun Song, Ting Zhu, Francisca Méndez Martín and Stefan Pogatscher and has published in prestigious journals such as Physical Review Letters, Acta Materialia and MRS Bulletin.

In The Last Decade

Daniel Marchand

7 papers receiving 363 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Marchand Switzerland	6	285	156	145	86	43	8	368
Marc Tupin France	12	631 2.2×	106 0.7×	353 2.4×	47 0.5×	15 0.3×	29	670
I.I. Novoselov Russia	8	254 0.9×	81 0.5×	27 0.2×	9 0.1×	33 0.8×	12	328
Yoav Lederer Germany	4	131 0.5×	156 1.0×	100 0.7×	3 0.0×	39 0.9×	5	259
J.C. Griess United States	7	86 0.3×	38 0.2×	31 0.2×	32 0.4×	14 0.3×	19	158
Junfeng Wang China	13	241 0.8×	56 0.4×	183 1.3×	1 0.0×	27 0.6×	46	413
Mutsumi Hirai Japan	13	428 1.5×	73 0.5×	310 2.1×	5 0.1×	10 0.2×	39	471
Mohammad Shakiba United States	12	157 0.6×	79 0.5×	82 0.6×		9 0.2×	21	314
K. Shibata Japan	12	171 0.6×	138 0.9×	58 0.4×	4 0.0×	11 0.3×	36	344
Yasushi Hirakawa Japan	11	206 0.7×	21 0.1×	106 0.7×	3 0.0×	10 0.2×	37	271

Countries citing papers authored by Daniel Marchand

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Marchand

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Marchand

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

All Works

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8 of 8 papers shown

1.

Marchand, Daniel. (2025). Foundation models for metallurgy?. MRS Bulletin. 50(7). 805–818.

2.

Marchand, Daniel & W. A. Curtin. (2022). Machine learning for metallurgy IV: A neural network potential for Al-Cu-Mg and Al-Cu-Mg-Zn. Physical Review Materials. 6(5). 27 indexed citations

3.

Jain, Abhinav, Daniel Marchand, Albert Glensk, Michele Ceriotti, & W. A. Curtin. (2021). Machine learning for metallurgy III: A neural network potential for Al-Mg-Si. Physical Review Materials. 5(5). 34 indexed citations

4.

Stemper, Lukas, Matheus A. Tunes, Phillip Dumitraschkewitz, et al.. (2020). Giant Hardening Response in AlMgZn(Cu) Alloys. SSRN Electronic Journal. 1 indexed citations

5.

Stemper, Lukas, Matheus A. Tunes, Phillip Dumitraschkewitz, et al.. (2020). Giant hardening response in AlMgZn(Cu) alloys. Acta Materialia. 206. 116617–116617. 110 indexed citations

6.

Marchand, Daniel, Abhinav Jain, Albert Glensk, & W.A. Curtin. (2020). Machine learning for metallurgy I. A neural-network potential for Al-Cu. Physical Review Materials. 4(10). 73 indexed citations

7.

Zhou, Xiao, Daniel Marchand, David L. McDowell, Ting Zhu, & Jun Song. (2016). Chemomechanical Origin of Hydrogen Trapping at Grain Boundaries in fcc Metals. Physical Review Letters. 116(7). 75502–75502. 98 indexed citations

8.

Snyder, Lloyd R., John R. Dolan, Daniel Marchand, & Peter W. Carr. (2012). The Hydrophobic-Subtraction Model of Reversed-Phase Column Selectivity. PubMed. 50. 297–376. 25 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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