Lukas Turcani

1.1k total citations
12 papers, 427 citations indexed

About

Lukas Turcani is a scholar working on Materials Chemistry, Inorganic Chemistry and Organic Chemistry. According to data from OpenAlex, Lukas Turcani has authored 12 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Materials Chemistry, 8 papers in Inorganic Chemistry and 7 papers in Organic Chemistry. Recurrent topics in Lukas Turcani's work include Metal-Organic Frameworks: Synthesis and Applications (8 papers), Supramolecular Chemistry and Complexes (6 papers) and Machine Learning in Materials Science (5 papers). Lukas Turcani is often cited by papers focused on Metal-Organic Frameworks: Synthesis and Applications (8 papers), Supramolecular Chemistry and Complexes (6 papers) and Machine Learning in Materials Science (5 papers). Lukas Turcani collaborates with scholars based in United Kingdom, Australia and Netherlands. Lukas Turcani's co-authors include Kim E. Jelfs, Enrico Berardo, Rebecca L. Greenaway, Martijn A. Zwijnenburg, Liam Wilbraham, Marcin Miklitz, Andrew I. Cooper, Ben M. Alston, Filip Szczypiński and Reiner Sebastian Sprick and has published in prestigious journals such as The Journal of Chemical Physics, Chemistry of Materials and Journal of Materials Chemistry A.

In The Last Decade

Lukas Turcani

12 papers receiving 423 citations

Peers

Lukas Turcani

RESE

EEE

Thomas Fellowes Australia

Austin M. Mroz United Kingdom

Mandeep K. Chahal Japan

Stephen A. Adalikwu Nigeria

Eric G. Moschetta United States

Pabitra Narayan Samanta India

Maximilian A. Springer Germany

Evgeniy O. Pentsak Russia

Yasemin Basdogan United States

Arunava Agarwala India

Thomas Fellowes Australia

Lukas Turcani

268 ×0.9

113 ×0.8

126 ×0.9

88 ×0.8

RESE

80 ×1.0

EEE

Citations per year, relative to Lukas Turcani Lukas Turcani (= 1×) peers Thomas Fellowes

Countries citing papers authored by Lukas Turcani

Since Specialization

Citations

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

Fields of papers citing papers by Lukas Turcani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lukas Turcani

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

All Works

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12 of 12 papers shown

Turcani, Lukas, et al.. (2024). Streamlining the automated discovery of porous organic cages. Chemical Science. 15(17). 6331–6348. 15 indexed citations

Mroz, Austin M., Lukas Turcani, & Kim E. Jelfs. (2023). Computational workflow for steric assessment using the electric field-derived size. Electronic Structure. 5(4). 45004–45004. 3 indexed citations

Turcani, Lukas, Andrew Tarzia, Filip Szczypiński, & Kim E. Jelfs. (2021). stk : An extendable Python framework for automated molecular and supramolecular structure assembly and discovery. The Journal of Chemical Physics. 154(21). 214102–214102. 37 indexed citations

Szczypiński, Filip, et al.. (2021). Materials Precursor Score: Modeling Chemists’ Intuition for the Synthetic Accessibility of Porous Organic Cage Precursors. Journal of Chemical Information and Modeling. 61(9). 4342–4356. 18 indexed citations

Fare, Clyde, Lukas Turcani, & Edward O. Pyzer‐Knapp. (2020). Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks. ePubs (Science and Technology Facilities Council, Research Councils UK). 8 indexed citations

Miklitz, Marcin, Lukas Turcani, Rebecca L. Greenaway, & Kim E. Jelfs. (2020). Computational discovery of molecular C60 encapsulants with an evolutionary algorithm. Communications Chemistry. 3(1). 10–10. 8 indexed citations

Berardo, Enrico, Rebecca L. Greenaway, Lukas Turcani, et al.. (2018). Computationally-inspired discovery of an unsymmetrical porous organic cage. Nanoscale. 10(47). 22381–22388. 42 indexed citations

Turcani, Lukas, Enrico Berardo, & Kim E. Jelfs. (2018). stk : A python toolkit for supramolecular assembly. Journal of Computational Chemistry. 39(23). 1931–1942. 51 indexed citations

Wilbraham, Liam, Enrico Berardo, Lukas Turcani, Kim E. Jelfs, & Martijn A. Zwijnenburg. (2018). High-Throughput Screening Approach for the Optoelectronic Properties of Conjugated Polymers. Journal of Chemical Information and Modeling. 58(12). 2450–2459. 63 indexed citations

10.

Berardo, Enrico, Lukas Turcani, Marcin Miklitz, & Kim E. Jelfs. (2018). An evolutionary algorithm for the discovery of porous organic cages. Chemical Science. 9(45). 8513–8527. 41 indexed citations

11.

Turcani, Lukas, Rebecca L. Greenaway, & Kim E. Jelfs. (2018). Machine Learning for Organic Cage Property Prediction. Chemistry of Materials. 31(3). 714–727. 47 indexed citations

12.

Sprick, Reiner Sebastian, Catherine M. Aitchison, Enrico Berardo, et al.. (2018). Maximising the hydrogen evolution activity in organic photocatalysts by co-polymerisation. Journal of Materials Chemistry A. 6(25). 11994–12003. 94 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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