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RESEARCH PAPER · Scientific Data · 2018

An open experimental database for exploring inorganic materials

Andriy Zakutayev, Nick Wunder, Marcus Schwarting, John D. Perkins, Robert White, Kristin R. Munch, William Tumas, Caleb T. Phillips

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An open experimental database for exploring inorganic materialsOriginalStabilization of wide band-gap p-type wurtzite MnTe thin films on amorphous substrates34Combinatorial Nitrogen Gradients in Sputtered Thin Films16Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing340Zinc-Stabilized Manganese Telluride with Wurtzite Crystal Structure19Data-centric science for materials innovation42Descriptor–property relationships in heterogeneous catalysis: exploiting synergies between statistics and fundamental kinetic modelling37Predicting structure/property relationships in multi-dimensional nanoparticle data using t-distributed stochastic neighbour embedding and machine learning33Progress and prospects for accelerating materials science with automated and autonomous workflows228Systematic exploration of the mechanical properties of 13 621 inorganic compounds38Accessing Metastability in Heterostructural Semiconductor Alloys9An Inter-Laboratory Study of Zn–Sn–Ti–O Thin Films using High-Throughput Experimental Methods15Composition, structure, and semiconducting properties of Mg x Zr 2− x N 2 thin films27Machine Learning for Computational Heterogeneous Catalysis356COMBIgor: Data-Analysis Package for Combinatorial Materials Science66Opto-electronic properties of Co-Zn-Ni-O films deposited by RF-sputtering at ambient-temperature6Modelling of framework materials at multiple scales: current practices and open questions24Accelerated Development of Perovskite-Inspired Materials via High-Throughput Synthesis and Machine-Learning Diagnosis333Synthesis of Lanthanum Tungsten Oxynitride Perovskite Thin Films22Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management73Ternary nitride semiconductors in the rocksalt crystal structure92Discovery of new materials using combinatorial synthesis and high-throughput characterization of thin-film materials libraries combined with computational methods357Tracking materials science data lineage to manage millions of materials experiments and analyses62Recent advances and applications of machine learning in solid-state materials science2607Data‐Driven Materials Science: Status, Challenges, and Perspectives700Combinatorial Tuning of Structural and Optoelectronic Properties in Cu Zn1−S35Experimental Data Curation at Large Instrument Facilities with Open Source Software1Unexpected Transitions Yield Interesting Science and High-Performance Materials1The Material Indices Method in the Sustainable Engineering Design Process: A Review31Review of high-throughput approaches to search for piezoelectric nitrides17Battery 2030+ Roadmap46Machine-learning-assisted search for functional materials over extended chemical space25Templated Growth of Metastable Polymorphs on Amorphous Substrates with Seed Layers11Wurtzite materials in alloys of rock salt compounds3A Critical Review of Machine Learning of Energy Materials606Artificial Intelligence to Power the Future of Materials Science and Engineering154Metaheuristic-based inverse design of materials – A survey46Combined Spatially Resolved Characterization of Antireflection and Antisoiling Coatings for PV Module Glass4Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery99Metastability at Defective Metal Oxide Interfaces and Nanoconfined Structures45High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses127Recent advances in knowledge discovery for heterogeneous catalysis using machine learning130Fast-Track to Research Data Management in Experimental Material Science–Setting the Ground for Research Group Level Materials Digitalization16$Mg_xZn_{1-x}O$ contact to $CuGa_3Se_5$ absorber for photovoltaic and photoelectrochemical devices1Machine learning in materials design: Algorithm and application*62Phase formation of manganese oxide thin films using pulsed laser deposition15The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design541Data-driven materials research enabled by natural language processing and information extraction302The Earth Mover’s Distance as a Metric for the Space of Inorganic Compositions69Mg x Zn1−x O contact to CuGa3Se5 absorber for photovoltaic and photoelectrochemical devices10An open-source, end-to-end workflow for multidimensional photoemission spectroscopy22An open-source, end-to-end workflow for multidimensional photoemission spectroscopy21Accelerating organic solar cell material's discovery: high-throughput screening and big data129Combinatorial screening of the crystal structure in Ba–Sr–Mn–Ce perovskite oxides with ABO 3 stoichiometry20Energy Material Network Data Hubs2Proof of Concept: Calibration of an Overhead Line Conductors’ Movements Simulation Model Using Ensemble-Based Machine Learning Model3Identification of the dominant recombination process for perovskite solar cells based on machine learning61Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration65Machine learning for material characterization with an application for predicting mechanical properties139Lessons learned from device modeling of organic & perovskite solar cells0Chalcogenide perovskites for photovoltaics: current status and prospects94Density Prediction Models for Energetic Compounds Merely Using Molecular Topology55Synthesis of Zn 2 NbN 3 ternary nitride semiconductor with wurtzite-derived crystal structure22NexusLIMS: A Laboratory Information Management System for Shared-Use Electron Microscopy Facilities25Functional and Material Properties in Nanocatalyst Design: A Data Handling and Sharing Problem8Influence of Protection Layers on Thermal Stability of Nitride Thin Films12ChemDataExtractor 2.0: Autopopulated Ontologies for Materials Science153Innovative Materials Science via Machine Learning194Synthesis, Properties and Applications of Lead-Free Perovskites:A Review3Research data infrastructure for high-throughput experimental materials science38Data-driven thermoelectric modeling: Current challenges and prospects25Implications of the BATTERY 2030+ AI‐Assisted Toolkit on Future Low‐TRL Battery Discoveries and Chemistries65Addressing the critical need for open experimental databases in materials science7HV-KIC property charts of cemented carbides: A comprehensive data collection98Accelerating research on novel photovoltaic materials10Artificial Intelligence based Approach for Rapid Material Discovery: From Chemical Synthesis to Quantum Materials0From evaluating the performance of approximations in Density Functional Theory to a Machine Learning design0Local chemical origin of ferroelectric behavior in wurtzite nitrides65Nitrogen stabilizes the wurtzite polymorph in ZnSe 1− x Te x thin films6Perspectives in the new era of materials intelligent design7Prediction of dielectric constants of ABO 3 -type perovskites using machine learning and first-principles calculations34Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis65Reduced synthesis temperatures of SrNbO2N perovskite films for photoelectrochemical fuel production2A Roadmap for Transforming Research to Invent the Batteries of the Future Designed within the European Large Scale Research Initiative BATTERY 2030+235Machine Learning in Materials Chemistry: An Invitation46Co-design of zinc titantium nitride semiconductor towards durable photoelectrochemical applications0Text Mining for Energy Materials3Recent advances and applications of deep learning methods in materials science1161A Perspective on Digital Knowledge Representation in Materials Science and Engineering40Role of disorder in the synthesis of metastable zinc zirconium nitrides37Materials Data toward Machine Learning: Advances and Challenges62A database of refractive indices and dielectric constants auto-generated using ChemDataExtractor46How statistical modeling and machine learning could help in the calibration of numerical simulation and fluid mechanics models? Application to the calibration of models reproducing the vibratory behavior of an overhead line conductor3CatS: A predictive and user-friendly framework based on machine learning models for the screening of heterogeneous catalysts7Codesigning Alloy Compositions of CdSeyTe1−y Absorbers and MgxZn1−xO Contacts to Increase Solar Cell Efficiency1Crystallize It before It Diffuses: Kinetic Stabilization of Thin-Film Phosphorus-Rich Semiconductor CuP 213Machine-Learning-Assisted Acceleration on High-Symmetry Materials Search: Space Group Predictions from Band Structures6Zinc Titanium Nitride Semiconductor toward Durable Photoelectrochemical Applications38Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery552A Generative Approach to Materials Discovery, Design, and Optimization121Machine learning aided synthesis and screening of HER catalyst: Present developments and prospects41Antimony nitride discovered by theoretical structure prediction, rapid thermal annealing, and in situ X-ray diffraction12High-Throughput Selection and Experimental Realization of Two New Ce-Based Nitride Perovskites: CeMoN3 and CeWN340Human- and machine-centred designs of molecules and materials for sustainability and decarbonization137Recent Developments in Process Digitalisation for Advanced Nanomaterial Syntheses11The role of Co valence in charge transport in the entropy‐stabilized oxide (Mg 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )O11Synthesis and Calculations of Wurtzite Al 1– x Gd x N Heterostructural Alloys10Autonomous optimization of an organic solar cell in a 4-dimensional parameter space50Discovery Pipelines as Epistemic Filters: What Computational Workflows Exclude0ESAMP: event-sourced architecture for materials provenance management and application to accelerated materials discovery18Stability and synthesis across barium tin sulfide material space12The materials experiment knowledge graph25Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics137Is Cu3–xP a Semiconductor, a Metal, or a Semimetal?21Combinatorial Synthesis of Cation-Disordered Manganese Tin Nitride MnSnN 2 Thin Films with Magnetic and Semiconducting Properties16Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics27TEXplorer.org: Thermoelectric material properties data platform for experimental and first-principles calculation results16The Materials Provenance Store8A method to computationally screen for tunable properties of crystalline alloys6Machine-Learning-Assisted Understanding of Polymer Nanocomposites Composition–Property Relationship: A Case Study of NanoMine Database28Materials cartography: A forward-looking perspective on materials representation and devising better maps13Discovery of high energy and stable prismane derivatives by the high-throughput computation and machine learning combined strategy9Machine Learning for Chemistry: Basics and Applications102Structural and optoelectronic properties of thin film LaWN312Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations32Experimental data management platform for data-driven investigation of combinatorial alloy thin films11Alloy synthesis and processing by semi-supervised text mining28Management and application of research data in condensed matter science2NOMAD: A distributed web-based platform for managing materials science research data167A Workflow for Accelerating Multimodal Data Collection for Electrodeposited Films19Learning Stability Scores from Computationally Generated Kinetic Data0Complimentary Computational Cues for Water Electrocatalysis: A DFT and ML Perspective76Advancing high-throughput combinatorial aging studies of hybrid perovskite thin films via precise automated characterization methods and machine learning assisted analysis14Autonomous generation of single photon emitting materials1Combinatorial synthesis and characterization of thin film Al 1− x RE x N (RE = Pr 3+ and Tb 3+ ) heterostructural alloys3Improving Machine-Learning Models in Materials Science Through Large Datasets6Machine learning of stability scores from kinetic data5Sustainably transforming biomass into advanced carbon materials for solid-state supercapacitors: a review19Mining experimental data from Materials Science literature with Large Language Models: an evaluation study0Mn Additive Improves Zr Grain Boundary Diffusion for Sintering of a Y-Doped BaZrO3 Proton Conductor21A Case Study of Multimodal, Multi-institutional Data Management for the Combinatorial Materials Science Community6Navigating phase diagram complexity to guide robotic inorganic materials synthesis82Data-Intensive Exploration of the Photoelectrochemical Responses of Main-Group Metal Sulfides2Mining experimental data from materials science literature with large language models: an evaluation study27Illustrating an Effective Workflow for Accelerated Materials Discovery14Synthesizability of materials stoichiometry using semi-supervised learning21Automated transient grating spectroscopy mapping and signal control for large samples3Accelerating electrocatalyst design for CO2 conversion through machine learning: Interpretable models and data-driven innovations21Materials Properties Prediction (MAPP): Empowering the Prediction of Material Properties Solely Based on Chemical Formulas12Synthesis pathways to thin films of stable layered nitrides18Revolutionizing Materials Research with Quantum Computation: The Role of High-Throughput Experimental Materials Databases0

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  1. Stabilization of wide band-gap p-type wurtzite MnTe thin films on amorphous substrates

    Journal of Materials Chemistry C · 2018-01-01

    Sebastian Siol, Yanbing Han, John S. Mangum, Philip Schulz, Aaron M. Holder, Talysa R. Klein, Maikel F. A. M. van Hest, Brian P. Gorman, Andriy Zakutayev

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  2. Combinatorial Nitrogen Gradients in Sputtered Thin Films

    ACS Combinatorial Science · 2018-05-17

    Yanbing Han, Bethany E. Matthews, Dennice M. Roberts, Kevin R. Talley, Sage R. Bauers, Craig L. Perkins, Qun Zhang, Andriy Zakutayev

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  3. Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing

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    Juan‐Pablo Correa‐Baena, Kedar Hippalgaonkar, Jeroen van Duren, Shaffiq A. Jaffer, Vijay Chandrasekhar, Vladan Stevanović, Cyrus Wadia, Supratik Guha, Tonio Buonassisi

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  4. Zinc-Stabilized Manganese Telluride with Wurtzite Crystal Structure

    The Journal of Physical Chemistry C · 2018-07-23

    Yanbing Han, Aaron M. Holder, Sebastian Siol, Stephan Lany, Qun Zhang, Andriy Zakutayev

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  5. Data-centric science for materials innovation

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  6. Descriptor–property relationships in heterogeneous catalysis: exploiting synergies between statistics and fundamental kinetic modelling

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    Laura Pirro, Pedro S.F. Mendes, Stijn Paret, Bart D. Vandegehuchte, Guy B Marin, Joris W. Thybaut

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  7. Predicting structure/property relationships in multi-dimensional nanoparticle data using t-distributed stochastic neighbour embedding and machine learning

    Nanoscale · 2019-01-01

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  8. Progress and prospects for accelerating materials science with automated and autonomous workflows

    Chemical Science · 2019-01-01

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  9. Systematic exploration of the mechanical properties of 13 621 inorganic compounds

    Chemical Science · 2019-01-01

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  10. Accessing Metastability in Heterostructural Semiconductor Alloys

    physica status solidi (a) · 2019-02-25

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  11. An Inter-Laboratory Study of Zn–Sn–Ti–O Thin Films using High-Throughput Experimental Methods

    ACS Combinatorial Science · 2019-03-19

    Jason R. Hattrick-Simpers, Andriy Zakutayev, Sara C. Barron, Zachary Trautt, Nam Nguyen Van, Kamal Kumar Choudhary, Brian DeCost, Caleb T. Phillips, Aaron Gilad Kusne, Feng Yi, Apurva Mehta, Ichiro Takeuchi, John D. Perkins, Martin L. Green

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  12. Composition, structure, and semiconducting properties of Mg x Zr 2− x N 2 thin films

    Japanese Journal of Applied Physics · 2019-05-03

    Sage R. Bauers, Danielle M. Hamann, Ashlea R. Patterson, John D. Perkins, Kevin R. Talley, Andriy Zakutayev

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  13. Machine Learning for Computational Heterogeneous Catalysis

    ChemCatChem · 2019-05-15

    Philomena Schlexer, Kirsten T. Winther, José Antonio Garrido Torres, Verena Streibel, Meng Zhao, Michal Bajdich, Frank Abild‐Pedersen, Thomas Bligaard

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  14. COMBIgor: Data-Analysis Package for Combinatorial Materials Science

    ACS Combinatorial Science · 2019-05-23

    Kevin R. Talley, Sage R. Bauers, Celeste L. Melamed, Meagan C. Papac, Karen N. Heinselman, Imran Khan, Dennice M. Roberts, Valerie Jacobson, Allison V. Mis, Geoff L. Brennecka, John D. Perkins, Andriy Zakutayev

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  15. Opto-electronic properties of Co-Zn-Ni-O films deposited by RF-sputtering at ambient-temperature

    Journal of Alloys and Compounds · 2019-05-24

    Joshua Cody Ford, Andriy Zakutayev, Paul F. Ndione, Ajaya K. Sigdel, N. Edwin Widjonarko, Philip A. Parilla, Bart Van Zeghbroeck, Joseph J. Berry, David S. Ginley, John D. Perkins

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  16. Modelling of framework materials at multiple scales: current practices and open questions

    Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · 2019-05-27

    Guillaume Fraux, Siwar Chibani, François‐Xavier Coudert

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  17. Accelerated Development of Perovskite-Inspired Materials via High-Throughput Synthesis and Machine-Learning Diagnosis

    Joule · 2019-06-01

    Shijing Sun, Noor Titan Putri Hartono, Zekun Ren, Felipe Oviedo, Antonio M. Buscemi, Mariya Layurova, De Xin Chen, Tofunmi Ogunfunmi, Janak Thapa, Savitha Ramasamy, Charles M. Settens, Brian DeCost, Aaron Gilad Kusne, Zhe Liu, Siyu Isaac Parker Tian, Ian Marius Peters, Juan‐Pablo Correa‐Baena, Tonio Buonassisi

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  18. Synthesis of Lanthanum Tungsten Oxynitride Perovskite Thin Films

    Advanced Electronic Materials · 2019-06-03

    Kevin R. Talley, John S. Mangum, Craig L. Perkins, Rachel Woods‐Robinson, Apurva Mehta, Brian P. Gorman, Geoff L. Brennecka, Andriy Zakutayev

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  19. Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management

    MRS Communications · 2019-06-04

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  20. Ternary nitride semiconductors in the rocksalt crystal structure

    Proceedings of the National Academy of Sciences · 2019-07-03

    Sage R. Bauers, Aaron M. Holder, Wenhao Q. Sun, Celeste L. Melamed, Rachel Woods‐Robinson, John S. Mangum, John D. Perkins, William Tumas, Brian P. Gorman, Adele C. Tamboli, Gerbrand Ceder, Stephan Lany, Andriy Zakutayev

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  21. Discovery of new materials using combinatorial synthesis and high-throughput characterization of thin-film materials libraries combined with computational methods

    npj Computational Materials · 2019-07-10

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  22. Tracking materials science data lineage to manage millions of materials experiments and analyses

    npj Computational Materials · 2019-07-26

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  23. Recent advances and applications of machine learning in solid-state materials science

    npj Computational Materials · 2019-08-08

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  24. Data‐Driven Materials Science: Status, Challenges, and Perspectives

    Advanced Science · 2019-09-01

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  25. Combinatorial Tuning of Structural and Optoelectronic Properties in Cu Zn1−S

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  26. Experimental Data Curation at Large Instrument Facilities with Open Source Software

    International Journal of Digital Curation · 2019-09-11

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  27. Unexpected Transitions Yield Interesting Science and High-Performance Materials

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  28. The Material Indices Method in the Sustainable Engineering Design Process: A Review

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  29. Review of high-throughput approaches to search for piezoelectric nitrides

    Journal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2019-10-24

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  30. Battery 2030+ Roadmap

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  31. Machine-learning-assisted search for functional materials over extended chemical space

    Materials Horizons · 2020-01-01

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  32. Templated Growth of Metastable Polymorphs on Amorphous Substrates with Seed Layers

    Physical Review Applied · 2020-01-08

    Yanbing Han, Ryan M. Trottier, Sebastian Siol, Bethany E. Matthews, Matthew R. Young, Charles B. Musgrave, Stephan Lany, Janet Tate, Qun Zhang, Aaron M. Holder, Andriy Zakutayev

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  33. Wurtzite materials in alloys of rock salt compounds

    Journal of materials research/Pratt's guide to venture capital sources · 2020-01-24

    Yanbing Han, Samantha L. Millican, Jun Liu, Sage R. Bauers, Sebastian Siol, Stephan Lany, Mowafak M. Al-Jassim, Charles B. Musgrave, Aaron M. Holder, Andriy Zakutayev

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  34. A Critical Review of Machine Learning of Energy Materials

    Advanced Energy Materials · 2020-01-29

    Chi Chen, Yunxing Zuo, Weike Ye, Xiangguo Li, Zhi Deng, Shyue Ping Ong

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  35. Artificial Intelligence to Power the Future of Materials Science and Engineering

    Advanced Intelligent Systems · 2020-02-11

    Wuxin Sha, Yaqing Guo, Qing Min Yuan, Shun Tang, Xinfang Zhang, Songfeng Lu, Xin Guo, Yuan‐Cheng Cao, Shijie Cheng

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  36. Metaheuristic-based inverse design of materials – A survey

    Journal of Materiomics · 2020-02-22

    Thunshun Warren Liao, Guoqiang Li

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  37. Combined Spatially Resolved Characterization of Antireflection and Antisoiling Coatings for PV Module Glass

    ACS Combinatorial Science · 2020-03-02

    Stephanie L. Moffitt, Conor T. Riley, Benjamin H. Ellis, Robert A. Fleming, Corey S. Thompson, Patrick D. Burton, Margaret Ellen Gordon, Andriy Zakutayev, Laura T. Schelhas

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  38. Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery

    Annual Review of Materials Research · 2020-04-21

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  39. Metastability at Defective Metal Oxide Interfaces and Nanoconfined Structures

    Advanced Materials Interfaces · 2020-05-19

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  40. High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses

    npj Computational Materials · 2020-05-27

    Kamal Kumar Choudhary, Kevin F. Garrity, Vinit Sharma, Adam J. Biacchi, Angela R. Hight Walker, Francesca Tavazza

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  41. Recent advances in knowledge discovery for heterogeneous catalysis using machine learning

    Catalysis Reviews · 2020-06-02

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  42. Fast-Track to Research Data Management in Experimental Material Science–Setting the Ground for Research Group Level Materials Digitalization

    ACS Combinatorial Science · 2020-06-19

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  43. $Mg_xZn_{1-x}O$ contact to $CuGa_3Se_5$ absorber for photovoltaic and photoelectrochemical devices

    arXiv (Cornell University) · 2020-10-04

    Imran Khan, Christopher P. Muzzillo, Craig L. Perkins, Andrew G. Norman, James L. Young, Nicolas M. Gaillard, Andriy Zakutayev

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  44. Machine learning in materials design: Algorithm and application*

    Chinese Physics B · 2020-10-14

    Zhilong Song, Xiwen Chen, Fanbin Meng, Guanjian Cheng, Chen Wang, Zhongti Sun, Wan‐Jian Yin

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  45. Phase formation of manganese oxide thin films using pulsed laser deposition

    Materials Advances · 2020-10-23

    Lauren M. Garten, Selvarasu Praneetha, John D. Perkins, David S. Ginley, Andriy Zakutayev

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  46. The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

    npj Computational Materials · 2020-11-12

    Kamal Choudhary, Kevin F. Garrity, Andrew C. E. Reid, Brian DeCost, Adam J. Biacchi, Angela R. Hight Walker, Zachary Trautt, Jason Hattrick-Simpers, A. Gilad Kusne, Andrea Centrone, Albert Davydov, Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan J. Reed, Ankit Agrawal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei V. Kalinin, Bobby G. Sumpter, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, Kristjan Haule, David Vanderbilt, Karin Rabe, Francesca Tavazza

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  47. Data-driven materials research enabled by natural language processing and information extraction

    Applied Physics Reviews · 2020-12-01

    Elsa Olivetti, Jacqueline M. Cole, Edward Kim, Olga Kononova, Gerbrand Ceder, T. Yong-Jin Han, Anna M. Hiszpanski

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  48. The Earth Mover’s Distance as a Metric for the Space of Inorganic Compositions

    Chemistry of Materials · 2020-12-02

    Cameron J. Hargreaves, Matthew Stephen Dyer, Michael W. Gaultois, Vitaliy A. Kurlin, Matthew J. Rosseinsky

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  49. Mg x Zn1−x O contact to CuGa3Se5 absorber for photovoltaic and photoelectrochemical devices

    Journal of Physics Energy · 2020-12-15

    Imran Khan, Christopher P. Muzzillo, Craig L. Perkins, Andrew G. Norman, James L. Young, Nicolas M. Gaillard, Andriy Zakutayev

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  50. An open-source, end-to-end workflow for multidimensional photoemission spectroscopy

    Scientific Data · 2020-12-17

    Rui Patrick Xian, Yves Acremann, Steinn Y. Agustsson, Maciej Dendzik, Kevin Bühlmann, Davide Curcio, Dmytro Kutnyakhov, Federico Pressacco, Michael Heber, Shuo Dong, Tommaso Pincelli, Jure Demsar, Wilfried Wurth, Philip Hofmann, Martin Wolf, Markus Scheidgen, Laurenz Rettig, Ralph Ernstorfer

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