Tim Schrader

479 total citations
11 papers, 153 citations indexed

About

Tim Schrader is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Agronomy and Crop Science. According to data from OpenAlex, Tim Schrader has authored 11 papers receiving a total of 153 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Materials Chemistry, 3 papers in Atomic and Molecular Physics, and Optics and 3 papers in Agronomy and Crop Science. Recurrent topics in Tim Schrader's work include Machine Learning in Materials Science (3 papers), Advanced Chemical Physics Studies (3 papers) and Ruminant Nutrition and Digestive Physiology (2 papers). Tim Schrader is often cited by papers focused on Machine Learning in Materials Science (3 papers), Advanced Chemical Physics Studies (3 papers) and Ruminant Nutrition and Digestive Physiology (2 papers). Tim Schrader collaborates with scholars based in Germany, United States and Tunisia. Tim Schrader's co-authors include Kris M. Havstad, D.M. Anderson, Ed L. Fredrickson, Rick E. Estell, Darren K. James, Eva Perlt, Kamel Damak, Marek Sierka, Ramzi Maâlej and Colleen A. Caldwell and has published in prestigious journals such as The Journal of Chemical Physics, Chemical Communications and Physical Chemistry Chemical Physics.

In The Last Decade

Tim Schrader

11 papers receiving 149 citations

Peers

Tim Schrader

ECOLO

ACS

MMPL

FORES

GPC

Lucas Teixeira Costa Brazil

A. Georgoudis Greece

Flávia Freire de Siqueira Brazil

Xueqin Zeng China

Pin Cui China

Masataka Fukuyama Japan

Božidarka Marković Montenegro

F. Hartmann Germany

Viktor Mamontov Russia

Michaela Ernst Germany

Lucas Teixeira Costa Brazil

Tim Schrader

38 ×0.7

ECOLO

79 ×1.7

ACS

15 ×0.6

MMPL

40 ×1.7

FORES

22 ×1.0

GPC

Citations per year, relative to Tim Schrader Tim Schrader (= 1×) peers Lucas Teixeira Costa

Countries citing papers authored by Tim Schrader

Since Specialization

Citations

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

Fields of papers citing papers by Tim Schrader

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tim Schrader

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

All Works

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11 of 11 papers shown

1.

Schrader, Tim, et al.. (2024). Machine-learning to predict anharmonic frequencies: a study of models and transferability. Physical Chemistry Chemical Physics. 26(35). 23495–23502. 2 indexed citations

2.

Schrader, Tim, et al.. (2024). The effect of machine learning predicted anharmonic frequencies on thermodynamic properties of fluid hydrogen fluoride. The Journal of Chemical Physics. 160(12). 1 indexed citations

3.

Schrader, Tim, et al.. (2023). Koopmans' theorem for acidic protons. Chemical Communications. 59(93). 13839–13842. 15 indexed citations

4.

Schrader, Tim, Eva Perlt, Torsten Fritz, & Marek Sierka. (2023). Performance of Common Density Functionals for Excited States of Tetraphenyldibenzoperiflanthene. The Journal of Physical Chemistry A. 127(15). 3265–3273. 1 indexed citations

5.

Both, Andreas, et al.. (2022). Quality Assurance of a German COVID-19 Question Answering Systems using Component-based Microbenchmarking. 1561–1564. 2 indexed citations

6.

Schrader, Tim, et al.. (2021). Atomistic Descriptors for Machine Learning Models of Solubility Parameters for Small Molecules and Polymers. Polymers. 14(1). 26–26. 17 indexed citations

7.

Elias, Emile, D. Scott McVey, Debra P. C. Peters, et al.. (2018). Contributions of Hydrology to Vesicular Stomatitis Virus Emergence in the Western USA. Ecosystems. 22(2). 416–433. 13 indexed citations

8.

Estell, Richard E., Kris M. Havstad, Andrés F. Cibils, D.M. Anderson, & Tim Schrader. (2014). The Changing Role of Shrubs in Rangeland-Based Livestock Production Systems: Can Shrubs Increase Our Forage Supply?. Rangelands. 36(2). 25–31. 7 indexed citations

9.

Caldwell, Colleen A., et al.. (2013). Estimating suitable environments for invasive plant species across large landscapes: A remote sensing strategy using Landsat 7 ETM+. International Journal of Biodiversity and Conservation. 5(3). 122–134. 11 indexed citations

10.

Fellner, Dieter W., et al.. (2012). Workshop: Centers of Excellence for Research Information -- Digital Text and Data Centers for Science and Open Research. TUbilio (Technical University of Darmstadt). 8(1). 1–2. 1 indexed citations

11.

Estell, Rick E., Kris M. Havstad, Ed L. Fredrickson, et al.. (2012). Increasing Shrub Use by Livestock in a World with Less Grass. Rangeland Ecology & Management. 65(6). 553–562. 83 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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