Graeme E. Murch

8.0k total citations
405 papers, 6.3k citations indexed

About

Graeme E. Murch is a scholar working on Mechanical Engineering, Materials Chemistry and Atmospheric Science. According to data from OpenAlex, Graeme E. Murch has authored 405 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 222 papers in Mechanical Engineering, 184 papers in Materials Chemistry and 84 papers in Atmospheric Science. Recurrent topics in Graeme E. Murch's work include nanoparticles nucleation surface interactions (84 papers), High Temperature Alloys and Creep (83 papers) and Intermetallics and Advanced Alloy Properties (74 papers). Graeme E. Murch is often cited by papers focused on nanoparticles nucleation surface interactions (84 papers), High Temperature Alloys and Creep (83 papers) and Intermetallics and Advanced Alloy Properties (74 papers). Graeme E. Murch collaborates with scholars based in Australia, United States and Germany. Graeme E. Murch's co-authors include Irina V. Belova, Thomas Fiedler, R.J. Thorn, Alexander V. Evteev, Elena V. Levchenko, S. J. Rothman, Mehdi Taherishargh, Andreas Öchsner, L. J. Nowicki and Nima Movahedi and has published in prestigious journals such as Journal of Applied Physics, Physical Review B and Acta Materialia.

In The Last Decade

Graeme E. Murch

393 papers receiving 6.1k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Graeme E. Murch 3.2k 3.0k 800 730 682 405 6.3k
R. Boom 4.0k 1.2× 2.3k 0.8× 876 1.1× 434 0.6× 604 0.9× 130 6.7k
J. B. Vander Sande 1.9k 0.6× 2.7k 0.9× 721 0.9× 206 0.3× 441 0.6× 157 4.9k
P. Haasen 3.2k 1.0× 4.0k 1.3× 803 1.0× 366 0.5× 983 1.4× 210 6.4k
Axel van de Walle 3.0k 0.9× 5.2k 1.7× 697 0.9× 760 1.0× 988 1.4× 129 8.0k
Sheng‐Nian Luo 2.8k 0.9× 5.2k 1.7× 676 0.8× 679 0.9× 1.2k 1.8× 376 8.9k
Yoshio Waseda 6.5k 2.0× 7.6k 2.5× 1.0k 1.3× 611 0.8× 719 1.1× 593 12.7k
R. Birringer 4.8k 1.5× 7.8k 2.6× 1.7k 2.1× 1.1k 1.5× 506 0.7× 163 10.7k
Marcel H. F. Sluiter 2.6k 0.8× 3.9k 1.3× 575 0.7× 493 0.7× 1.0k 1.5× 191 6.3k
Huiqiu Deng 2.1k 0.7× 4.5k 1.5× 536 0.7× 591 0.8× 696 1.0× 380 7.9k
Ihsan Barin 3.3k 1.0× 3.7k 1.2× 981 1.2× 286 0.4× 833 1.2× 11 7.2k

Countries citing papers authored by Graeme E. Murch

Since Specialization
Citations

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

Fields of papers citing papers by Graeme E. Murch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Graeme E. Murch. 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 Graeme E. Murch. The network helps show where Graeme E. Murch may publish in the future.

Co-authorship network of co-authors of Graeme E. Murch

This figure shows the co-authorship network connecting the top 25 collaborators of Graeme E. Murch. A scholar is included among the top collaborators of Graeme E. Murch 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 Graeme E. Murch. Graeme E. Murch 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.
Muralikrishna, G. Mohan, Julia Kundin, Frank Hisker, et al.. (2025). The impact of non-equilibrium vacancies on mobilities and Kirkendall porosity formation in diffusion couples: Experiments and theory for the Cu–Fe–Ni system as a case study. Acta Materialia. 292. 121035–121035. 1 indexed citations
2.
Kozubski, R., et al.. (2025). Direct Kinetic Monte Carlo Simulations of Interdiffusion. Journal of Phase Equilibria and Diffusion. 46(1). 186–203. 1 indexed citations
3.
Tang, Jian, William Yi Wang, De-Ye Lin, et al.. (2019). Activation volume dominated diffusivity of Ni50Al50 melt under extreme conditions. Computational Materials Science. 171. 109263–109263. 7 indexed citations
4.
Belova, Irina V., William Yi Wang, R. Kozubski, et al.. (2019). Computer simulation of thermodynamic factors in Ni-Al and Cu-Ag liquid alloys. Computational Materials Science. 166. 124–135. 2 indexed citations
5.
Ahmed, Tanvir, William Yi Wang, R. Kozubski, et al.. (2018). Mass and thermal transport in liquid Cu-Ag alloys. The Philosophical Magazine A Journal of Theoretical Experimental and Applied Physics. 99(4). 468–491. 10 indexed citations
6.
Ahmed, Tanvir, William Yi Wang, R. Kozubski, et al.. (2018). Interdiffusion and thermotransport in Ni–Al liquid alloys. The Philosophical Magazine A Journal of Theoretical Experimental and Applied Physics. 98(24). 2221–2246. 15 indexed citations
7.
Ahmed, Tanvir, Elena V. Levchenko, Alexander V. Evteev, et al.. (2017). Molecular Dynamics Prediction of the Influence of Composition on Thermotransport in Ni-Al Melts. Diffusion foundations. 12. 93–110. 4 indexed citations
8.
Bąk, T., et al.. (2017). SUSTAINABLE PRACTICES: SOLAR HYDROGEN FUEL AND EDUCATION PROGRAM ON SUSTAINABLE ENERGY SYSTEMS. Alternative Energy and Ecology (ISJAEE). 14–24. 2 indexed citations
9.
Ahmed, Tanvir, Irina V. Belova, & Graeme E. Murch. (2015). Finite Difference Solution of the Diffusion Equation and Calculation of the Interdiffusion Coefficient using the Sauer-Freise and Hall Methods in Binary Systems. Procedia Engineering. 105. 570–575. 16 indexed citations
10.
Belova, Irina V. & Graeme E. Murch. (2013). Interdiffusion in Intermetallics. Metallurgical and Materials Transactions A. 44(10). 4417–4421. 6 indexed citations
11.
Öchsner, Andreas, Graeme E. Murch, Ali Shokuhfar, & João M. P. Q. Delgado. (2012). Diffusion in Solids and Liquids VII. Trans Tech Publications Ltd. eBooks. 1 indexed citations
12.
Öchsner, Andreas, Graeme E. Murch, Ali Shokuhfar, & João M. P. Q. Delgado. (2010). Diffusion in Solids and Liquids V. Trans Tech Publications Ltd. eBooks. 1 indexed citations
13.
Murch, Graeme E., Alexander V. Evteev, Elena V. Levchenko, & Irina V. Belova. (2009). Recent progress in the simulation of diffusion associated with hollow and Bi-metallic nanoparticles. Diffusion fundamentals.. 11. 9 indexed citations
14.
Belova, Irina V., Graeme E. Murch, Thomas Fiedler, & Andreas Öchsner. (2007). lattice Monte Carlo method for solving phenomenological mass andheat transport problems. Diffusion fundamentals.. 4. 21 indexed citations
15.
Murch, Graeme E. & Irina V. Belova. (2005). Phenomenological coefficients in solid-state diffusion. Diffusion fundamentals.. 2.
16.
Murch, Graeme E. & Irina V. Belova. (1999). Diffusion mechanisms in intermetallic compounds. 23. 179–188. 4 indexed citations
17.
Murch, Graeme E., et al.. (1996). Disordered materials -current developments- : proceedings of the International Seminar on Current Developments in Disordered Materials, held in Kurukshetra, India, January 1996 : CDDM-96. 1 indexed citations
18.
Dayananda, M. A. & Graeme E. Murch. (1985). Diffusion in solids : recent developments. 104 indexed citations
19.
Murch, Graeme E.. (1981). Self diffusion in nonstoichiometric compounds†. Journal of Physics and Chemistry of Solids. 42(3). 227–231. 3 indexed citations
20.
Murch, Graeme E.. (1979). A relation between the activation energy for self diffusion and the partial molar energy in interstitial solid solutions. Acta Metallurgica. 27(11). 1701–1704. 4 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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