Daniel Scheiber

1.7k total citations
56 papers, 1.4k citations indexed

About

Daniel Scheiber is a scholar working on Materials Chemistry, Mechanical Engineering and Metals and Alloys. According to data from OpenAlex, Daniel Scheiber has authored 56 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Materials Chemistry, 30 papers in Mechanical Engineering and 11 papers in Metals and Alloys. Recurrent topics in Daniel Scheiber's work include Microstructure and mechanical properties (21 papers), Hydrogen embrittlement and corrosion behaviors in metals (11 papers) and Advanced Materials Characterization Techniques (10 papers). Daniel Scheiber is often cited by papers focused on Microstructure and mechanical properties (21 papers), Hydrogen embrittlement and corrosion behaviors in metals (11 papers) and Advanced Materials Characterization Techniques (10 papers). Daniel Scheiber collaborates with scholars based in Austria, Canada and Australia. Daniel Scheiber's co-authors include Lorenz Romaner, Reinhard Pıppan, Peter Puschnig, Vsevolod I. Razumovskiy, Werner Ecker, Xiangyuan Cui, Lin Han, Simon P. Ringer, A. V. Ruban and Maxim N. Popov and has published in prestigious journals such as Acta Materialia, Scientific Reports and Materials Science and Engineering A.

In The Last Decade

Daniel Scheiber

55 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Scheiber Austria 21 1.0k 903 292 231 225 56 1.4k
Vsevolod I. Razumovskiy Austria 27 1.1k 1.1× 1.1k 1.3× 367 1.3× 297 1.3× 279 1.2× 71 1.7k
Margarita Kuzmina Russia 8 852 0.8× 976 1.1× 270 0.9× 250 1.1× 212 0.9× 25 1.3k
Darius Tytko Germany 10 661 0.7× 702 0.8× 121 0.4× 253 1.1× 273 1.2× 14 1.1k
P. Choi Germany 12 921 0.9× 930 1.0× 280 1.0× 167 0.7× 283 1.3× 12 1.3k
C. Pareige France 27 1.4k 1.4× 1.0k 1.1× 516 1.8× 289 1.3× 173 0.8× 61 2.0k
Ryuji Uemori Japan 18 811 0.8× 1.1k 1.3× 215 0.7× 207 0.9× 246 1.1× 68 1.3k
Y. Matsukawa Japan 27 1.7k 1.7× 813 0.9× 295 1.0× 270 1.2× 302 1.3× 68 2.0k
Xiao-Xiang Yu United States 20 865 0.9× 993 1.1× 98 0.3× 315 1.4× 457 2.0× 49 1.5k
David C. Van Aken United States 23 1.1k 1.0× 1.3k 1.5× 200 0.7× 238 1.0× 372 1.7× 83 1.6k
Mao Wen China 20 1.1k 1.0× 833 0.9× 742 2.5× 200 0.9× 257 1.1× 67 1.5k

Countries citing papers authored by Daniel Scheiber

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Scheiber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Scheiber

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

All Works

20 of 20 papers shown
1.
Scheiber, Daniel, et al.. (2025). Ab-initio grain boundary thermodynamics beyond the dilute limit. Acta Materialia. 286. 120725–120725. 2 indexed citations
2.
Romaner, Lorenz, et al.. (2025). Predictive modeling of the bainite start temperature using Bayesian inference. Acta Materialia. 295. 121131–121131. 1 indexed citations
3.
4.
Scheiber, Daniel, et al.. (2025). Influence of carbon and sulfur on austenite grain boundary mobility. Acta Materialia. 288. 120851–120851. 2 indexed citations
5.
Kronberger, Gabriel, et al.. (2025). Comparison of semi-empirical models, symbolic regression, and machine learning approaches for prediction of tensile strength in steels. International Journal of Engineering Science. 212. 104247–104247. 1 indexed citations
6.
Scheiber, Daniel. (2024). Ab initio informed solute drag assessment for ferritic steels. Computational Materials Science. 245. 113328–113328. 2 indexed citations
7.
Scheiber, Daniel, et al.. (2024). Grain boundary segregation for the Fe-P system: Insights from atomistic modeling and Bayesian inference. Acta Materialia. 279. 120215–120215. 8 indexed citations
8.
Stamati, Olga, Christoph Gammer, Julie Villanova, et al.. (2024). Amorphous shear band formation in crystalline Si-anodes governs lithiation and capacity fading in Li-ion batteries. Communications Materials. 5(1). 9 indexed citations
9.
Hammerschmidt, Thomas, et al.. (2024). Descriptors based on the density of states for efficient machine learning of grain-boundary segregation energies. Computational Materials Science. 247. 113493–113493. 3 indexed citations
10.
Scheiber, Daniel, et al.. (2023). Modeling solute-grain boundary interactions in a bcc Ti-Mo alloy using density functional theory. Computational Materials Science. 229. 112393–112393. 4 indexed citations
11.
Scheiber, Daniel, et al.. (2023). Atomistically informed phase field study of austenite grain growth. Computational Materials Science. 228. 112300–112300. 13 indexed citations
12.
Scheiber, Daniel, et al.. (2023). Modification of the Cu/W Interface Cohesion by Segregation. Metals. 13(2). 346–346. 2 indexed citations
13.
Chamasemani, Fereshteh Falah, René Hammer, Jakub Zálešák, et al.. (2023). Probing the composition dependence of residual stress distribution in tungsten-titanium nanocrystalline thin films. Communications Materials. 4(1). 11–11. 9 indexed citations
14.
Han, Lin, Xiangyuan Cui, Daniel Scheiber, Lorenz Romaner, & Simon P. Ringer. (2023). Phosphorus and transition metal co-segregation in ferritic iron grain boundaries and its effects on cohesion. Acta Materialia. 250. 118850–118850. 22 indexed citations
15.
Romaner, Lorenz, et al.. (2023). Machine learning mechanical properties of steel sheets from an industrial production route. Materialia. 30. 101810–101810. 7 indexed citations
16.
Han, Lin, Xiangyuan Cui, Daniel Scheiber, Lorenz Romaner, & Simon P. Ringer. (2022). The segregation of transition metals to iron grain boundaries and their effects on cohesion. Acta Materialia. 231. 117902–117902. 59 indexed citations
17.
Scheiber, Daniel & Lorenz Romaner. (2021). Impact of the segregation energy spectrum on the enthalpy and entropy of segregation. Acta Materialia. 221. 117393–117393. 37 indexed citations
18.
Hajilou, Tarlan, Iman Taji, F. Christien, et al.. (2020). Hydrogen-enhanced intergranular failure of sulfur-doped nickel grain boundary: In situ electrochemical micro-cantilever bending vs. DFT. Materials Science and Engineering A. 794. 139967–139967. 31 indexed citations
19.
Scheiber, Daniel, Lorenz Romaner, Reinhard Pıppan, & Peter Puschnig. (2018). Impact of solute-solute interactions on grain boundary segregation and cohesion in molybdenum. Physical Review Materials. 2(9). 42 indexed citations
20.
Li, Jiehua, Fredrik S. Hage, Lorenz Romaner, et al.. (2015). The roles of Eu during the growth of eutectic Si in Al-Si alloys. Scientific Reports. 5(1). 13802–13802. 50 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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