Pedro Borlido

1.3k total citations
17 papers, 957 citations indexed

About

Pedro Borlido is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Electrical and Electronic Engineering. According to data from OpenAlex, Pedro Borlido has authored 17 papers receiving a total of 957 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Materials Chemistry, 6 papers in Atomic and Molecular Physics, and Optics and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Pedro Borlido's work include Machine Learning in Materials Science (10 papers), 2D Materials and Applications (6 papers) and Graphene research and applications (5 papers). Pedro Borlido is often cited by papers focused on Machine Learning in Materials Science (10 papers), 2D Materials and Applications (6 papers) and Graphene research and applications (5 papers). Pedro Borlido collaborates with scholars based in Germany, Portugal and Belgium. Pedro Borlido's co-authors include Silvana Botti, Miguel A. L. Marques, Jonathan Schmidt, Ahmad W. Huran, Fabien Tran, Jingming Shi, Liming Chen, Tiago F. T. Cerqueira, Hai‐Chen Wang and Claudia Rödl and has published in prestigious journals such as Advanced Materials, Chemistry of Materials and Scientific Reports.

In The Last Decade

Pedro Borlido

17 papers receiving 940 citations

Peers

Countries citing papers authored by Pedro Borlido

Since Specialization

Citations

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

Fields of papers citing papers by Pedro Borlido

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pedro Borlido

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

All Works

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17 of 17 papers shown

#	Title	Journal	Authors	Indexed citations
1	Assessing Exchange-Correlation Functionals for Accurate Densities of Solids	Journal of Chemical Theory and Computation	Pedro Borlido, Miguel A. L. Marques et al.	3
2	High-refractive-index materials screening from machine learning and ab initio methods	Physical Review Materials	Márcio Ferreira, Tiago F. T. Cerqueira et al.	6
3	Ensemble averages of ab initio optical, transport, and thermoelectric properties of hexagonal SixGe1−x alloys	Physical Review Materials	Pedro Borlido, F. Bechstedt et al.	3
4	Searching for ductile superconducting Heusler X2YZ compounds	npj Computational Materials	Tiago F. T. Cerqueira, Pedro Borlido et al.	13
5	Machine‐Learning‐Assisted Determination of the Global Zero‐Temperature Phase Diagram of Materials	Advanced Materials	Jonathan Schmidt, Hai‐Chen Wang et al.	55
6	Computational screening of materials with extreme gap deformation potentials	npj Computational Materials	Pedro Borlido, Jonathan Schmidt et al.	7
7	Bandgap of two-dimensional materials: Thorough assessment of modern exchange-correlation functionals	arXiv (Cornell University)	Fabien Tran, Peter Blaha et al.	38
8	A Global-Optimization Study of the Phase Diagram of Free-Standing Hydrogenated Two-Dimensional Silicon	The Journal of Physical Chemistry C	Pedro Borlido, Miguel A. L. Marques et al.	4
9	Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learning	npj Computational Materials	Pedro Borlido, Jonathan Schmidt et al.	247
10	Novel two-dimensional silicon–carbon binaries by crystal structure prediction	Physical Chemistry Chemical Physics	Pedro Borlido, Ahmad W. Huran et al.	10
11	Large-Scale Benchmark of Exchange–Correlation Functionals for the Determination of Electronic Band Gaps of Solids	Journal of Chemical Theory and Computation	Pedro Borlido, Ahmad W. Huran et al.	199
12	Structural prediction of stabilized atomically thin tin layers	npj 2D Materials and Applications	Pedro Borlido, Ahmad W. Huran et al.	15
13	The ground state of two-dimensional silicon	2D Materials	Pedro Borlido, Claudia Rödl et al.	26
14	Anisotropic layered Bi2Te3-In2Te3 composites: control of interface density for tuning of thermoelectric properties	Scientific Reports	Dongmei Liu, Xinzhong Li et al.	25
15	Local Hybrid Density Functional for Interfaces	Journal of Chemical Theory and Computation	Pedro Borlido, Miguel A. L. Marques et al.	25
16	Predicting the Thermodynamic Stability of Solids Combining Density Functional Theory and Machine Learning	Chemistry of Materials	Jonathan Schmidt, Jingming Shi et al.	258
17	Structural prediction of two-dimensional materials under strain	2D Materials	Pedro Borlido, Nektarios N. Lathiotakis et al.	23

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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