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Size-induced amorphous structure in tungsten oxide nanoparticles

Nanoscale, 2021-12, Vol.13 (47), p.2144-2156

2021

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Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning

npj computational materials, 2022-10, Vol.8 (1), p.1-11, Article 213

2022

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Simple Setup Miniaturization with Multiple Benefits for Green Chemistry in Nanoparticle Synthesis

ACS omega, 2022-02, Vol.7 (5), p.4714-4721

2022

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Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry

Chemical science (Cambridge), 2023-12, Vol.14 (48), p.143-1419

2023

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We are never ever getting (back to) ideal symmetry: structure and luminescence in a ten-coordinated europium() sulfate crystal

Dalton transactions : an international journal of inorganic chemistry, 2022-06, Vol.51 (23), p.896-8963

2022

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Formation and growth mechanism for niobium oxide nanoparticles: atomistic insight from in situ X-ray total scattering

Nanoscale, 2021-05, Vol.13 (17), p.8087-8097

2021

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Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO2

Dalton transactions : an international journal of inorganic chemistry, 2022-11, Vol.51 (45), p.17150-17161

2022

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Correction: Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO2

Dalton transactions : an international journal of inorganic chemistry, 2023-05, Vol.52 (18), p.6194-6194

2023

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Correction: Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO 2

Dalton transactions : an international journal of inorganic chemistry, 2023-05, Vol.52 (18), p.6194-6194

2023

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POMFinder : identifying polyoxometallate cluster structures from pair distribution function data using explainable machine learning

Journal of applied crystallography, 2024-02, Vol.57 (Pt 1), p.34-43

2024

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Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO 2

Dalton transactions : an international journal of inorganic chemistry, 2022-11, Vol.51 (45), p.17150-17161

2022

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Monitoring the Structural Changes in Iridium Nanoparticles during Oxygen Evolution Electrocatalysis with Operando X‑ray Total Scattering

Journal of the American Chemical Society, 2024-10, Vol.146 (40), p.27517-27527

2024

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Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small‐Angle X‐ray Scattering Analysis

Angewandte Chemie International Edition, 2021-09, Vol.60 (37), p.20407-20416

International ed. in English, 2021

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ClusterFinder: a fast tool to find cluster structures from pair distribution function data

Acta crystallographica. Section A, Foundations and advances, 2024-03, Vol.80 (2), p.213-220

2024

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Atomic structural changes in the formation of transition metal tungstates: the role of polyoxometalate structures in material crystallization

Chemical science (Cambridge), 2023-05, Vol.14 (18), p.486-4816

2023

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Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data

Digital discovery, 2023-06, Vol.2 (3), p.578-59

2023

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Effect of solvothermal synthesis parameters on the crystallite size and atomic structure of cobalt iron oxide nanoparticles

Nanoscale advances, 2024-09

2024

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DeepStruc: towards structure solution from pair distribution function data using deep generative models

Digital discovery, 2023-02, Vol.2 (1), p.69-80

2023

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MLstructureMining: a machine learning tool for structure identification from X-ray pair distribution functions

Digital discovery, 2024-05, Vol.3 (5), p.98-918

2024

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Breaking with the Principles of Coreduction to Form Stoichiometric Intermetallic PdCu Nanoparticles

Small methods, 2022-06, Vol.6 (6), p.e2200420-n/a

2022

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Formation of intermetallic PdIn nanoparticles: influence of surfactants on nanoparticle atomic structure

Nanoscale advances, 2023-12, Vol.5 (24), p.6913-6924

2023

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Rücktitelbild: Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small‐Angle X‐ray Scattering Analysis (Angew. Chem. 37/2021)

Angewandte Chemie, 2021-09, Vol.133 (37), p.20732-20732

2021

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Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small‐Angle X‐ray Scattering Analysis

Angewandte Chemie, 2021-09, Vol.133 (37), p.20570-20579

2021

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Correction: Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO

Dalton transactions : an international journal of inorganic chemistry, 2023-05, Vol.52 (18), p.6194-6194

2023

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Exploring the Composition Space of High-Entropy Alloy Nanoparticles for the Electrocatalytic H 2 /CO Oxidation with Bayesian Optimization

ACS catalysis, 2022-09, Vol.12 (18), p.11263-11271

2022

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Size-induced amorphous structure in tungsten oxide nanoparticles

Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning

Simple Setup Miniaturization with Multiple Benefits for Green Chemistry in Nanoparticle Synthesis

Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry

We are never ever getting (back to) ideal symmetry: structure and luminescence in a ten-coordinated europium() sulfate crystal

Formation and growth mechanism for niobium oxide nanoparticles: atomistic insight from in situ X-ray total scattering

Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO2

Correction: Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO2

Correction: Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO 2

POMFinder : identifying polyoxometallate cluster structures from pair distribution function data using explainable machine learning

Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO 2

Monitoring the Structural Changes in Iridium Nanoparticles during Oxygen Evolution Electrocatalysis with Operando X‑ray Total Scattering

Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small‐Angle X‐ray Scattering Analysis

ClusterFinder: a fast tool to find cluster structures from pair distribution function data

Atomic structural changes in the formation of transition metal tungstates: the role of polyoxometalate structures in material crystallization

Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data

Effect of solvothermal synthesis parameters on the crystallite size and atomic structure of cobalt iron oxide nanoparticles

DeepStruc: towards structure solution from pair distribution function data using deep generative models

MLstructureMining: a machine learning tool for structure identification from X-ray pair distribution functions

Breaking with the Principles of Coreduction to Form Stoichiometric Intermetallic PdCu Nanoparticles

Formation of intermetallic PdIn nanoparticles: influence of surfactants on nanoparticle atomic structure

Rücktitelbild: Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small‐Angle X‐ray Scattering Analysis (Angew. Chem. 37/2021)

Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small‐Angle X‐ray Scattering Analysis

Correction: Characterisation of intergrowth in metal oxide materials using structure-mining: the case of γ-MnO

Exploring the Composition Space of High-Entropy Alloy Nanoparticles for the Electrocatalytic H 2 /CO Oxidation with Bayesian Optimization

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