Jonathan Lahnsteiner
- Materials Chemistry top 10%
- Electrical and Electronic Engineering top 10%
- Atomic and Molecular Physics, and Optics
- Electronic, Optical and Magnetic Materials
- Computational Theory and Mathematics top 10%
- Co-authors
- Menno BokdamGeorg KresseRyosuke JinnouchiFerenc KarsaiD. D. SarmaCesare FranchiniAbhinav KumarTobias Schäfer
- Topics
- Perovskite Materials and Applications (11 papers)Machine Learning in Materials Science (6 papers)Solid-state spectroscopy and crystallography (6 papers)
- Cited by
- Materials ChemistryElectrical and Electronic EngineeringAtomic and Molecular Physics, and Optics
- Partner nations
- AustriaNetherlandsIndia
In The Last Decade
Jonathan Lahnsteiner
11 papers receiving 741 citations
Hit Papers
Peers
Comparison fields: 5 of 53
- Materials Chemistry 640
- Electrical and Electronic Engineering 429
- Atomic and Molecular Physics, and Optics 129
- Electronic, Optical and Magnetic Materials 68
- Computational Theory and Mathematics 55
Countries citing papers authored by Jonathan Lahnsteiner
This map shows the geographic impact of Jonathan Lahnsteiner'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 Jonathan Lahnsteiner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Lahnsteiner more than expected).
Fields of papers citing papers by Jonathan Lahnsteiner
This network shows the impact of papers produced by Jonathan Lahnsteiner. 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 Jonathan Lahnsteiner. The network helps show where Jonathan Lahnsteiner may publish in the future.
Co-authorship network of co-authors of Jonathan Lahnsteiner
This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Lahnsteiner. A scholar is included among the top collaborators of Jonathan Lahnsteiner 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 Jonathan Lahnsteiner. Jonathan Lahnsteiner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 12 | |
| 4 | 31 | |
| 5 | 26 | |
| 6 | The essence of long-range order in hybrid perovskites | 1 |
| 7 | Phase Transitions of Hybrid Perovskites Simulated by Machine-Learning Force Fields Trained on the Fly with Bayesian Inferencebreakdown → | 415 |
| 8 | 17 | |
| 9 | 2 | |
| 10 | 63 | |
| 11 | 122 | |
| 12 | 59 |
About Jonathan Lahnsteiner
Jonathan Lahnsteiner is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Electronic, Optical and Magnetic Materials, having authored 12 papers that have together received 754 indexed citations. Recurring topics across this work include Perovskite Materials and Applications (11 papers), Machine Learning in Materials Science (6 papers) and Solid-state spectroscopy and crystallography (6 papers). The work is most often cited by research in Materials Chemistry (640 citations), Electrical and Electronic Engineering (429 citations) and Atomic and Molecular Physics, and Optics (129 citations). Jonathan Lahnsteiner has collaborated with scholars based in Austria, Netherlands and India. Frequent co-authors include Menno Bokdam, Georg Kresse, Ryosuke Jinnouchi, Ferenc Karsai, D. D. Sarma, Cesare Franchini, Abhinav Kumar, Tobias Schäfer, Sharada Govinda and Bhushan P. Kore. Their work appears in journals such as Physical Review Letters, The Journal of Chemical Physics and Physical Review B.
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.