100 citations · 184 across the 11 of their papers we have counts for
12 papers
Accelerating Combinatorial Electrocatalyst Discovery with Bayesian Optimization: A Case Study in the Quaternary System Ni-Pd-Pt-Ru for the Oxygen Evolution Reaction
F. Thelen, R. Zehl, R. Zerdoumi +4
The discovery of high-performance electrocatalysts is crucial for advancing sustainable energy technologies. Compositionally complex solid solutions comprising multiple metals offe…
Composition-property extrapolation for compositionally complex solid solutions based on word embeddings
Lei Zhang, Lars Banko, Wolfgang Schuhmann +2
Mastering the challenge of predicting properties of unknown materials with multiple principal elements (high entropy alloys/compositionally complex solid solutions) is crucial for…
MatInf -- an Extensible Open-Source Solution for Research Digitalisation in Materials Science
Victor Dudarev, Lars Banko, Alfred Ludwig
Information technology and data science development stimulate transformation in many fields of scientific knowledge. In recent years, a large number of specialized systems for info…
Speeding up high-throughput characterization of materials libraries by active learning: autonomous electrical resistance measurements
Felix Thelen, Lars Banko, Rico Zehl +2
High-throughput experimentation enables efficient search space exploration for the discovery and optimization of new materials. However, large search spaces of, e.g., compositional…
Combinatorial sputter synthesis of single-phase La(XYZ)O perovskite thin film libraries: a new platform for materials discovery
Tobias H. Piotrowiak, Rico Zehl, Ellen Suhr +3
Compositionally complex perovskites provide the opportunity to develop stable and active catalysts for electrochemical applications. The challenge lies in the identification of sin…
Computationally accelerated experimental materials characterization -- drawing inspiration from high-throughput simulation workflows
Markus Stricker, Lars Banko, Nik Sarazin +5
Computational materials science increasingly benefits from data management, automation, and algorithm-based decision-making for the simulation of material properties and behavior.…
Unusual phase formation in reactively sputtered La-Co-O perovskite thin films
Tobias H. Piotrowiak, Rico Zehl, Ellen Suhr +4
La-based perovskites are a versatile class of materials that are of interest for solid oxide fuel cells and electrocatalytic water splitting. During fabrication of composition spre…
Combinatorial materials discovery strategy for high entropy alloy electrocatalysts using deposition source permutations
Lars Banko, Olga A. Krysiak, Bin Xiao +6
High entropy alloys offer a huge search space for new electrocatalysts. Searching for a global property maximum in one quinary system could require, depending on compositional reso…
Bayesian Optimization of High-Entropy Alloy Compositions for Electrocatalytic Oxygen Reduction
Jack K. Pedersen, Christian M. Clausen, Olga A. Krysiak +10
Active, selective and stable catalysts are imperative for sustainable energy conversion, and engineering materials with such properties are highly desired. High-entropy alloys (HEA…
Deep learning for visualization and novelty detection in large X-ray diffraction datasets
Lars Banko, Phillip M. Maffettone, Dennis Naujoks +2
We apply variational autoencoders (VAE) to X-ray diffraction (XRD) data analysis on both simulated and experimental thin-film data. We show that crystal structure representations l…
Crystallography companion agent for high-throughput materials discovery
Phillip M. Maffettone, Lars Banko, Peng Cui +5
The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurem…
Mastering processing-microstructure complexity through the prediction of thin film structure zone diagrams by generative machine learning models
Lars Banko, Yury Lysogorskiy, Dario Grochla +3
Thin films are ubiquitous in modern technology and highly useful in materials discovery and design. For achieving optimal extrinsic properties their microstructure needs to be cont…