Daniel R. Cassar

1.3k total citations
45 papers, 960 citations indexed

About

Daniel R. Cassar is a scholar working on Materials Chemistry, Ceramics and Composites and Mechanical Engineering. According to data from OpenAlex, Daniel R. Cassar has authored 45 papers receiving a total of 960 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Materials Chemistry, 26 papers in Ceramics and Composites and 10 papers in Mechanical Engineering. Recurrent topics in Daniel R. Cassar's work include Glass properties and applications (26 papers), Material Dynamics and Properties (26 papers) and Phase-change materials and chalcogenides (10 papers). Daniel R. Cassar is often cited by papers focused on Glass properties and applications (26 papers), Material Dynamics and Properties (26 papers) and Phase-change materials and chalcogenides (10 papers). Daniel R. Cassar collaborates with scholars based in Brazil, United States and Germany. Daniel R. Cassar's co-authors include Edgar Dutra Zanotto, André C. P. L. F. de Carvalho, Alisson Mendes Rodrigues, Tiago Botari, Saulo Martiello Mastelini, Vladimir M. Fokin, Prabhat K. Gupta, Oscar Peitl, Bruno Almeida Pimentel and John C. Mauro and has published in prestigious journals such as Chemical Reviews, The Journal of Chemical Physics and The Journal of Physical Chemistry B.

In The Last Decade

Daniel R. Cassar

39 papers receiving 939 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 R. Cassar Brazil 20 693 548 207 100 96 45 960
Adama Tandia United States 17 528 0.8× 587 1.1× 155 0.7× 54 0.5× 44 0.5× 26 1.0k
П. Д. Саркисов Russia 13 376 0.5× 430 0.8× 59 0.3× 26 0.3× 19 0.2× 69 625
A. Mocellin France 21 539 0.8× 503 0.9× 567 2.7× 42 0.4× 5 0.1× 69 1.1k
Stéphane Gossé France 14 584 0.8× 85 0.2× 207 1.0× 216 2.2× 10 0.1× 54 734
V. Ya. Shevchenko Russia 17 601 0.9× 144 0.3× 239 1.2× 115 1.1× 2 0.0× 142 933
M.A. Ali Egypt 15 365 0.5× 151 0.3× 39 0.2× 191 1.9× 14 0.1× 45 652
Y. H. Elbashar Egypt 17 711 1.0× 587 1.1× 17 0.1× 98 1.0× 16 0.2× 63 1.1k
M. Krishna Murthy India 22 699 1.0× 567 1.0× 207 1.0× 78 0.8× 5 0.1× 89 1.5k
B.L. Butler United States 6 119 0.2× 140 0.3× 188 0.9× 21 0.2× 10 0.1× 18 536
Xiangjun Liu China 21 1.2k 1.7× 62 0.1× 162 0.8× 10 0.1× 5 0.1× 73 1.4k

Countries citing papers authored by Daniel R. Cassar

Since Specialization
Citations

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

Fields of papers citing papers by Daniel R. Cassar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel R. Cassar

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel R. Cassar. A scholar is included among the top collaborators of Daniel R. Cassar 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 R. Cassar. Daniel R. Cassar 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.
Mamo, Julian, Neville Calleja, Daniel R. Cassar, et al.. (2025). The population characteristics and prevalence of visual impairment in a Southern European population. European Journal of Ophthalmology. 36(2). 250–262.
2.
Bradtmüller, Henrik, João V. Campos, Daniel R. Cassar, et al.. (2025). Structure–property relationships in sodium phosphate glasses and glass‐ceramics containing tantalum oxide. Journal of the American Ceramic Society. 108(9).
3.
4.
Cassar, Daniel R., et al.. (2024). Optimizing toughness in high entropy alloys using a genetic algorithm: A combined computational and experimental approach. Materials Today Communications. 41. 110768–110768.
5.
Robey, Edward, et al.. (2024). Leveraging Additive Manufacturing and Coatings for Turbine Thermal Management. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
6.
Cassar, Daniel R., et al.. (2024). Diffusion proxies reveal the dynamic process in supercooled and glassy lithium diborate. Ceramics International. 50(19). 35549–35556. 1 indexed citations
7.
Cassar, Daniel R., et al.. (2024). Using a simple radial basis function neural network to predict the glass transition temperature of alkali borate glasses. Journal of Non-Crystalline Solids. 629. 122870–122870. 4 indexed citations
8.
Cassar, Daniel R., et al.. (2024). Thermal, chemical, and mechanical properties of niobium phosphate glasses and glass-ceramics. Ceramics International. 50(11). 18618–18627. 9 indexed citations
9.
Allec, Sarah I., Xiaonan Lu, Daniel R. Cassar, et al.. (2024). Evaluation of GlassNet for physics‐informed machine learning of glass stability and glass‐forming ability. Journal of the American Ceramic Society. 107(12). 7784–7799. 3 indexed citations
10.
Zanotto, Edgar Dutra, et al.. (2023). Cracking the Kauzmann paradox. Acta Materialia. 254. 118994–118994. 21 indexed citations
11.
Zaki, Mohd, Suresh Bishnoi, Daniel R. Cassar, et al.. (2023). Glass hardness: Predicting composition and load effects via symbolic reasoning-informed machine learning. Acta Materialia. 255. 119046–119046. 21 indexed citations
12.
Cassar, Daniel R.. (2023). GlassNet: A multitask deep neural network for predicting many glass properties. Ceramics International. 49(22). 36013–36024. 37 indexed citations
13.
Cassar, Daniel R.. (2020). Reproducible gray-box neural network for predicting the fragility index and the temperature-dependency of viscosity. arXiv (Cornell University). 2 indexed citations
14.
Cassar, Daniel R.. (2020). drcassar/glasspy: GlassPy 0.3. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
15.
Jiusti, Jeanini, Edgar Dutra Zanotto, Daniel R. Cassar, & M.R.B. Andreeta. (2019). Viscosity and liquidus‐based predictor of glass‐forming ability of oxide glasses. Journal of the American Ceramic Society. 103(2). 921–932. 32 indexed citations
16.
Zanotto, Edgar Dutra & Daniel R. Cassar. (2017). The microscopic origin of the extreme glass-forming ability of Albite and B2O3. Scientific Reports. 7(1). 43022–43022. 35 indexed citations
17.
Rodrigues, Alisson Mendes, Daniel R. Cassar, Vladimir M. Fokin, & Edgar Dutra Zanotto. (2017). Crystal growth and viscous flow in barium disilicate glass. Journal of Non-Crystalline Solids. 479. 55–61. 27 indexed citations
18.
Cassar, Daniel R., et al.. (2016). Structural relaxation in AgPO3 glass followed by in situ ionic conductivity measurements. Journal of Non-Crystalline Solids. 437. 43–47. 11 indexed citations
19.
Gupta, Prabhat K., Daniel R. Cassar, & Edgar Dutra Zanotto. (2016). Role of dynamic heterogeneities in crystal nucleation kinetics in an oxide supercooled liquid. The Journal of Chemical Physics. 145(21). 211920–211920. 42 indexed citations
20.
Cassar, Daniel R., et al.. (2012). Observations on performance characteristics of plastic water-filled barrier-type devices. 1 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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