Team

Daniel Horke

Group Leader | Assistant Professor

d.horke@science.ru.nl

+31-24 3652688

Postbus 9010

Nijmegen, 6500 GL

The Netherlands

Short CV

Education

2003 – 2005: International Baccalaureate, Malvern, UK
2005 – 2009: M.Sci. Natural Sciences (Chemistry+Physics), Durham University, UK
2009 – 2012: PhD, Dept. of Chemistry, Durham University, UK (Advisor: Prof. Jan Verlet)

Research Positions

2013 – 2014: Postdoctoral Researcher, Center for Free-Electron Laser Science, DESY, Hamburg, Germany (Supervisor: Prof. Jochen Küpper)
2014 – 2018: Team Leader, Center for Free-Electron Laser Science, DESY, Hamburg, Germany (Supervisor: Prof. Jochen Küpper)
since 2019: Assistant Professor and Group Leader, Institute for Molecules and Materials, Radboud University Nijmegen, Netherlands

Grants and Awards

2019 NWO Start-up grant
2020 NWO VIDI grant

Full CV

Peter Krüger

PostDoc

Imaging chirality using photoelectron circular dichroism (PECD)

peter.krueger@ru.nl

+31-24 365 3280

Yerbolat Dauletyarov

PostDoc

Dynamics of electron-driven processes

yerbolat.dauletyarov@ru.nl

+31-24 365 3280

Grite Abma

PhD Student

Isomer Effects in ultrafast photochemistry

grite.abma@ru.nl

+31-24 365 3280

Siwen Wang

PhD Student

Dynamics of electron-driven processes

siwen.wang@ru.nl

+31-24 365 3280

Ana Caballo

PhD Student

Photoelectron-Photoion coincidence imaging of UV-induced photochemistry

Dynamics of electron-driven processes

ana.caballozulueta@ru.nl

+31-24 365 3280

Olga Duda

PhD Student

Isomer Effects in ultrafast photochemistry

olga.duda@ru.nl

+31-24 365 3280

Saskia Pieters

MSc Student

Photoelectron-Photoion coincidence imaging of UV-induced photochemistry

saskia.pieters@ru.nl

Our group is part of the Spectroscopy of Cold Molecules department and we gratefully acknowledge the support from the entire department, especially from the technical and administrative staff!

Alumni

Dries Kleuskens	MSc	2020-2021
Ana Caballo	MSc	2020-2021
Bhargava Ram	PostDoc	2021
Jantijn Jenniskens	BSc	2022

News

5. September 2022

Yerbolat joins the group as a PostDoc to work on your NWO-funded project on electron-driven reactions - Welcome Yerbolat!

Reply on Twitter 1566744566786662401 Retweet on Twitter 1566744566786662401 Like on Twitter 1566744566786662401 2 . 1566744566786662401

2. August 2022

Our latest paper comparing continuous and pulsed laser-based desorption (LIAD) methods is out now in Eur.Phys.J. D - well done Siwen! https://bit.ly/3cYM5tc

Reply on Twitter 1554486850760413187 Retweet on Twitter 1554486850760413187 Like on Twitter 1554486850760413187 1 . 1554486850760413187

14. June 2022

Our latest paper showing how the electrostatic deflector can be used as a tool for isomer-resolved spectroscopy is out now in @JPhysChem A - well done Grite! https://doi.org/10.1021/acs.jpca.2c02277

Reply on Twitter 1536688857894330368 Retweet on Twitter 1536688857894330368 2 Like on Twitter 1536688857894330368 25 . 1536688857894330368

Recent Publications

10 entries « ‹ 2 of 4 › »

Zhuang, Yulong; Awel, Salah; Barty, Anton; Bean, Richard; Bielecki, Johan; Bergemann, Martin; Daurer, Benedikt J.; Ekeberg, Tomas; Estillore, Armando D.; Fangohr, Hans; Giewekemeyer, Klaus; Hunter, Mark S.; Karnevskiy, Mikhail; Kirian, Richard A.; Kirkwood, Henry; Kim, Yoonhee; Koliyadu, Jayanath; Lange, Holger; Letrun, Romain; Lübke, Jannik; Mall, Abhishek; Michelat, Thomas; Morgan, Andrew J.; Roth, Nils; Samanta, Amit K.; Sato, Tokushi; Shen, Zhou; Sikorski, Marcin; Schulz, Florian; Spence, John C. H.; Vagovic, Patrik; Wollweber, Tamme; Worbs, Lena; Xavier, P. Lourdu; Yefanov, Oleksandr; Maia, Filipe R. N. C.; Horke, Daniel A.; Küpper, Jochen; Loh, N. Duane; Mancuso, Adrian P.; Chapman, Henry N.; Ayyer, Kartik

Unsupervised Learning Approaches to Characterizing Heterogeneous Samples Using X-ray Single-Particle Imaging Journal Article

In: IUCrJ, vol. 9, no. 2, pp. 204–214, 2022, ISSN: 2052-2525.

Abstract | Links | BibTeX

@article{Zhuang:IUCrJ9:204,

title = {Unsupervised Learning Approaches to Characterizing Heterogeneous Samples Using X-ray Single-Particle Imaging},

author = {Yulong Zhuang and Salah Awel and Anton Barty and Richard Bean and Johan Bielecki and Martin Bergemann and Benedikt J. Daurer and Tomas Ekeberg and Armando D. Estillore and Hans Fangohr and Klaus Giewekemeyer and Mark S. Hunter and Mikhail Karnevskiy and Richard A. Kirian and Henry Kirkwood and Yoonhee Kim and Jayanath Koliyadu and Holger Lange and Romain Letrun and Jannik L\"{u}bke and Abhishek Mall and Thomas Michelat and Andrew J. Morgan and Nils Roth and Amit K. Samanta and Tokushi Sato and Zhou Shen and Marcin Sikorski and Florian Schulz and John C. H. Spence and Patrik Vagovic and Tamme Wollweber and Lena Worbs and P. Lourdu Xavier and Oleksandr Yefanov and Filipe R. N. C. Maia and Daniel A. Horke and Jochen K\"{u}pper and N. Duane Loh and Adrian P. Mancuso and Henry N. Chapman and Kartik Ayyer},

url = {https://scripts.iucr.org/cgi-bin/paper?S2052252521012707},

doi = {10.1107/S2052252521012707},

issn = {2052-2525},

year  = {2022},

date = {2022-03-01},

urldate = {2022-03-14},

journal = {IUCrJ},

volume = {9},

number = {2},

pages = {204--214},

abstract = {One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand\textendash maximize\textendash compress ( EMC ) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

Lübke, Jannik; Roth, Nils; Worbs, Lena; Horke, Daniel A.; Estillore, Armando D.; Samanta, Amit K.; Küpper, Jochen

Charge-State Distribution of Aerosolized Nanoparticles Journal Article

In: J. Phys. Chem. C, vol. 125, no. 46, pp. 25794–25798, 2021, ISSN: 1932-7447, 1932-7455.

Abstract | Links | BibTeX

Caballo, Ana; Huits, Anders J. T. M.; Vredenborg, Arno; Balster, Michiel; Parker, David H.; Horke, Daniel A.

Femtosecond 2 + 1 Resonance-Enhanced Multiphoton Ionization Spectroscopy of the C-State in Molecular Oxygen Journal Article

In: J. Phys. Chem. A, vol. 125, no. 41, pp. 9060–9064, 2021, ISSN: 1089-5639.

Abstract | Links | BibTeX

10 entries « ‹ 2 of 4 › »