Battery Interface Genome - Materials Acceleration Platform

Informations projet

BIG-MAP

N° de convention de subvention: 957189

DOI 10.3030/957189

Projet clôturé

Date de signature de la CE 22 Juin 2020

Date de début 1 Septembre 2020

Date de fin 29 Février 2024

Financé au titre de

• EXCELLENT SCIENCE - Future and Emerging Technologies (FET)

Coût total € 19 997 812,50

Contribution de l’UE € 19 997 812,50

Coordonné par

DANMARKS TEKNISKE UNIVERSITET
Denmark

Livrables

Documents, reports (21)

Design of robotic system for organic synthesis completed

Full design of robotic system for organic synthesis completed

Report on inorganic coatings prepared by combinatorial syntheses

Report/paper submitted on inorganic coatings prepared by combinatorial syntheses.

Proceedings from Early Stage Research Seminar

Submission of report with proceedings from the Early Stage Research Seminar

First stable release of battery interface ontology
Report on ontology standards and development strategy

Reportpaper submitted on ontology standards and development strategy

Advanced direct SEI investigations for chemistry neutral lithium-based batteries by integrated high throughput electrochemistry with ex situ high throughput spectroscopy

Report/paper submitted on the use of advanced direct SEI investigations for chemistry neutral lithium-based batteries by integrated high throughput electrochemistry with ex situ high throughput spectroscopy.

Report on lab-scale and large-scale facilities automated and standardized data analysis

Report/paper submitted on lab-scale and large-scale facilities automated and standardized data analysis.

Global BIG-MAP experimental matrix, proof-of-concept of BIG-MAP experimental workflow and definition of perspectives and future vision towards the European multimodal platform

Report submitted on a global BIG-MAP experimental matrix, proof-of-concept of BIG-MAP experimental workflow and definition of perspectives and future vision towards the European multimodal platform.

Final Dissemination report

Submission of the Final Dissemination report.

State-of-the art experimental matrix, tier 1 experimental plan and workflow

Report on stateofthe art experimental matrix tier 1 experimental plan and workflow submitted

Battery Interface Ontology published according to standards in the European modelling community

The Battery Interface Ontology (BIO) has been published according to standards in the European modelling community.

Design of workflow for a European experimental multimodal platform completed
Design of robotic system for inorganic synthesis completed

Full design of robotic system for inorganic synthesis completed

Tiered theory and experiment screening pipeline as first test case for automatic reasoning calibration

Report/paper on tiered theory and experiment screening pipeline as first test case for automatic reasoning calibration.

Report on battery interface ontology case study

Report/paper submitted on a battery interface ontology case study.

Specification (flow chart) of hardware and software architecture

Report with specification flow chart of hardware and software architecture submitted

Proceeding from international workshop/conference

Submission of report with proceedings from the international workshopconference

Protocol for SEI composition and degradation prediction

Publication of protocol for computational prediction of SEI composition and degradation.

Initial protocols for experimental spectra prediction

Release ofinitial protocols for calculational prediction of experimental spectra

Initial version of battery ontology

Initial version of battery ontology submitted

Identification of interphase descriptor dynamics for test system

Reportpaper on the identification of interphase descriptor dynamics for test system

Demonstrators, pilots, prototypes (5)

Demonstration of the capability to run coordinated multi-techniques experiments to acquire multi-scale data, and practical application to a selected chemistry

Completion of a demonstration of the capability to run coordinated multi-techniques experiments to acquire multi-scale data, and practical application to a selected chemistry.

Demonstration of automated synthesis procedure

Demonstration of automated synthesis procedure completed.

Demonstrate transfer of select model(s) to novel battery materials/chemistry

Demonstration of transfer of select model(s) to novel battery materials/chemistry completed.

Demonstrator of a simulation run by an experiment, and an experiment run by a simulation

Demonstrator of a simulation run by an experiment, and an experiment run by a simulation.

Active learning package/module demonstrated to work on pre-generated simulation or experimental data sets

Active learning packagemodule demonstrated to work on pregenerated simulation or experimental data sets

Open Research Data Pilot (2)

Data Management Plan

A Data Management Plan will be prepared which complies with the Open Research Data Pilot ORDP Requirements and the specific data requirements in the project

Updated BIG-MAP App-store

Launch of updated BIG-MAP App-store, including tools providing access to Open Data from the project deposited in the Materials Cloud repository.

Websites, patent fillings, videos etc. (4)

Online data analysis tools made available to the whole community

Online data analysis tools made available to the whole community.

Prototype of the BIG-MAP App-store

Prototype of the BIGMAP Appstore developed

BIG-MAP website

Launch of the httpwwwBIGMAPeu web site with information about the project

First European platform open to researchers/industries outside of the consortium where batteries can be tested following the tests protocols defined in BIG-MAP

First European platform open to researchers/industries outside of the consortium where batteries can be tested following the tests protocols defined in BIG-MAP.

Publications

Peer reviewed articles (95)

Implications of the BATTERY 2030+ AI-assisted toolkit on future low-TRL battery discoveries and chemistries

Auteurs: Bhowmik, Berecibar, Casas-Cabanas, Csanyi, Dominko, Hermansson, Palacin, Stein, Vegge
Publié dans: Advanced Energy Materials, 2021, ISSN 1614-6840
Éditeur: Wiley
DOI: 10.1002/aenm.202102698

Learning the laws of lithium-ion transport in electrolytes using symbolic regression

Auteurs: Eibar Flores, Christian Wölke, Peng Yan, Martin Winter, Tejs Vegge, Isidora Cekic-Laskovic and Arghya Bhowmik
Publié dans: Digital Discovery, Numéro 1, 2022, Page(s) 440-447, ISSN 2635-098X
Éditeur: Royal Society of Chemistry
DOI: 10.1039/d2dd00027j

An orbital-based representation for accurate quantum machine learning

Auteurs: Konstantin Karandashev, O. Anatole von Lilienfeld
Publié dans: J. Chem. Phys., Numéro 156, 2022, Page(s) 114101, ISSN 0021-9606
Éditeur: American Institute of Physics
DOI: 10.1063/5.0083301

High-Throughput Experimentation and Computational Freeway Lanes for Accelerated Battery Electrolyte and Interface Development Research

Auteurs: Anass Benayad, Diddo Diddens, Andreas Heuer, Anand Narayanan Krishnamoorthy, Moumita Maiti, Frederic Le Cras, Maxime Legallais, Fuzhan Rahmanian, Yuyoung Shin, Helge Stein, Martin Winter, Christian Wölke, Peng Yan, Isidora Cekic-Laskovic
Publié dans: Advanced Energy Materials, 2021, ISSN 1614-6840
Éditeur: Wiley
DOI: 10.1002/aenm.202102678

Accelerated Workflow for Antiperovskite‐based Solid State Electrolytes

Auteurs: Benjamin H. Sjølin; Peter B. Jørgensen; Andrea Fedrigucci; Tejs Vegge; Arghya Bhowmik; Ivano E. Castelli
Publié dans: Batteries and Supercaps, Numéro 6 (6), 2023, Page(s) e202300041, ISSN 2566-6223
Éditeur: Wiley-VCH
DOI: 10.1002/batt.202300041

Density Functional Geometries and Zero-Point Energies in Ab Initio Thermochemical Treatments of Compounds with First-Row Atoms (H, C, N, O, F)

Auteurs: Dirk Bakowies, O. Anatole von Lilienfeld
Publié dans: Journal of Chemical Theory and Computation, Numéro 17/8, 2021, Page(s) 4872-4890, ISSN 1549-9618
Éditeur: American Chemical Society
DOI: 10.1021/acs.jctc.1c00474

Cascading Degradations Artificially Improving the Lifetime of Li-ion Full Cells using DMC-based Highly Concentrated Electrolyte

Auteurs: V. Meunier, F. Capone, R. Dedryvère, A. Grimaud
Publié dans: J. Electrochem. Soc., Numéro 170, 2023, Page(s) 060551, ISSN 1945-7111
Éditeur: The Electrochemical Society
DOI: 10.1149/1945-7111/ace031

Leveraging Composition-Based Material Descriptors for Machine Learning Optimization

Auteurs: Trezza, Giovanni; Chiavazzo, Eliodoro
Publié dans: Materials Today Communications, Numéro 36, 2023, Page(s) 106579, ISSN 2352-4928
Éditeur: Elsevier BV
DOI: 10.1016/j.mtcomm.2023.106579

NeuralNEB—neural networks can find reaction paths fast

Auteurs: Mathias Schreiner; Arghya Bhowmik; Tejs Vegge; Peter Bjørn Jørgensen; Ole Winther
Publié dans: Machine Learning: Science and Technology, Numéro 3, 2022, Page(s) 045022, ISSN 2632-2153
Éditeur: IOP Publishing
DOI: 10.1088/2632-2153/aca23e

Ab Initio Machine Learning in Chemical Compound Space

Auteurs: Bing Huang, O. Anatole von Lilienfeld
Publié dans: Chemical Reviews, Numéro 121/16, 2021, Page(s) 10001-10036, ISSN 0009-2665
Éditeur: American Chemical Society
DOI: 10.1021/acs.chemrev.0c01303

Neural network ansatz for periodic wave functions and the homogeneous electron gas

Auteurs: Max Wilson, Saverio Moroni, Markus Holzmann, Nicholas Gao, Filip Wudarski, Tejs Vegge, Arghya Bhowmik
Publié dans: Phys. Rev. B, Numéro 107, 2023, Page(s) 235139, ISSN 2469-9950
Éditeur: American Physical Society
DOI: 10.1103/physrevb.107.235139

OSSCAR, an open platform for collaborative development of computational tools for education in science

Auteurs: D. Du, T. J. Baird, S. Bonella, G. Pizzi
Publié dans: Computer Physics Communications, Numéro 282, 2023, Page(s) 108546, ISSN 0010-4655
Éditeur: Elsevier BV
DOI: 10.1016/j.cpc.2022.108546

Phase-field investigation of lithium electrodeposition under different applied overpotentials and operating temperatures

Auteurs: Joonyeob Jeon; Gil Ho Yoon; Tejs Vegge; Jin Hyun Chang
Publié dans: ACS Appl. Mater. Interfaces, 2022, ISSN 1944-8244
Éditeur: American Chemical Society
DOI: 10.1021/acsami.2c00900

Deconvoluting the benefits of porosity distribution in layered electrodes on the electrochemical performance of Li-ion batteries

Auteurs: Abbos Shodiev, Mehdi Chouchane, Miran Gaberscek, Oier Arcelus, Jiahui Xu, Hassan Oularbi, Jia Yu, Jianlin Li, Mathieu Morcrette, Alejandro A. Franco
Publié dans: Energy Storage Materials, Numéro 47, 2022, Page(s) 462-471, ISSN 2405-8289
Éditeur: Elsevier
DOI: 10.1016/j.ensm.2022.01.058

Conformer-specific polar cycloaddition of dibromobutadiene with trapped propene ions.

Auteurs: Ardita Kilaj; Jia Wang; Patrik Straňák; Max Schwilk; Max Schwilk; Uxía Rivero; Lei Xu; O. Anatole von Lilienfeld; O. Anatole von Lilienfeld; Jochen Küpper; Stefan Willitsch
Publié dans: Nature Communications, Numéro 12, 2021, Page(s) 6047, ISSN 2041-1723
Éditeur: Nature Publishing Group
DOI: 10.3204/pubdb-2021-02598

Design of workflows for crosstalk detection and lifetime deviation onset in Li-ion batteries

Auteurs: Valentin Meunier, Matheus Leal De Souza, Mathieu Morcrette, Alexis Grimaud
Publié dans: Joule, Numéro 7, 2022, Page(s) 42-56, ISSN 2542-4351
Éditeur: Cell Press
DOI: 10.1016/j.joule.2022.12.004

Time and Space Resolved Operando Synchrotron X-Ray and Neutron Diffraction Study of Nmc811/Si-Gr 5 Ah Pouch Cells

Auteurs: Kristoffer Visti Graae; Xinyu Li; Daniel Risskov Sørensen; Elixabete Ayerbe; Iker Boyano; Denis Sheptyakov; Mads Ry Vogel Jørgensen; Poul Norby
Publié dans: Journal of Power Sources, Numéro 570, 2023, Page(s) 232993, ISSN 1873-2755
Éditeur: Elsevier
DOI: 10.1016/j.jpowsour.2023.232993

Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks

Auteurs: Jonas Busk; Peter Bjørn Jørgensen; Arghya Bhowmik; Mikkel N. Schmidt; Ole Winther; Tejs Vegge
Publié dans: Machine Learning: Science and Technology, Numéro 3, 2022, Page(s) 015012, ISSN 2632-2153
Éditeur: IOP
DOI: 10.1088/2632-2153/ac3eb3

Training sets based on uncertainty estimates in the cluster-expansion method

Auteurs: David Kleiven; Jaakko Akola; Andrew A Peterson; Tejs Vegge; Jin Hyun Chang
Publié dans: JPhys Energy, Numéro 3, 2021, Page(s) 034012, ISSN 2515-7655
Éditeur: IOPscience
DOI: 10.1088/2515-7655/abf9ef

Transition1x - a dataset for building generalizable reactive machine learning potentials

Auteurs: Mathias Schreiner; Arghya Bhowmik; Tejs Vegge; Jonas Busk; Ole Winther
Publié dans: Scientific Data, Numéro 9, 2022, ISSN 2052-4463
Éditeur: Springer Nature
DOI: 10.1038/s41597-022-01870-w

Functional data-driven framework for fast forecasting of electrode slurry rheology simulated by molecular dynamics

Auteurs: Marc Duquesnoy; Teo Lombardo; Fernando Caro; Florent Haudiquez; Alain C. Ngandjong; Jiahui Xu; Hassan Oularbi; Alejandro A. Franco
Publié dans: npj Computational Materials, Numéro 8, 2022, ISSN 2057-3960
Éditeur: Nature Publishing Group
DOI: 10.1038/s41524-022-00819-2

Towards better and smarter batteries by combining AI with multisensory and self-healing approaches

Auteurs: Tejs Vegge, Jean-Marie Tarascon and Kristina Edström
Publié dans: Adv. Energy Mater., Numéro 11, 2021, Page(s) 2100362, ISSN 1614-6840
Éditeur: Wiley-VCH GmbH
DOI: 10.1002/aenm.202100362

Advances in studying interfacial reactions in rechargeable batteries by photoelectron spectroscopy

Auteurs: Ida Källquist; Ronan Le Ruyet; Haidong Liu; Ronnie Mogensen; Ming-Tao Lee; Kristina Edström; Andrew J. Naylor
Publié dans: J. Mater. Chem. A, Numéro 10, 2022, Page(s) 19466-19505, ISSN 1364-5501
Éditeur: Royal Society of Chemistry
DOI: 10.1039/d2ta03242b

Materials funnel 2.0 – data-driven hierarchical search for exploration of vast chemical spaces

Auteurs: Raul Ortega Ochoa; Bardi Benediktsson; Renata Sechi; Peter Bjørn Jørgensen; Arghya Bhowmik
Publié dans: Journal of Materials Chemistry A, Numéro 11, 2023, Page(s) 26551, ISSN 2050-7496
Éditeur: The royal society of chemistry
DOI: 10.1039/d3ta05860c

Phase Separating Electrode Materials – Chemical Inductors?

Auteurs: Klemen Zelič; Igor Mele; Arghya Bhowmik; Tomaž Katrašnik
Publié dans: Energy storage materials, Numéro 56, 2023, Page(s) 489-494, ISSN 2405-8297
Éditeur: Elsevier
DOI: 10.1016/j.ensm.2023.01.008

Towards autonomous high-throughput multiscale modelling of battery interfaces

Auteurs: Zeyu Deng; Vipin Kumar; Felix T. Bölle; Fernando Caro; Alejandro A. Franco; Ivano E. Castelli; Pieremanuele Canepa; Zhi Wei Seh
Publié dans: Energy & Environmental Science, Numéro 15, 2022, Page(s) 579-594, ISSN 1754-5706
Éditeur: Royal Society of Chemistry
DOI: 10.1039/d1ee02324a

Machine learning force fields for molecular liquids: Ethylene Carbonate/Ethyl Methyl Carbonate binary solvent

Auteurs: I.-B. Magdău, D.J. Arismendi-Arrieta, H.E. Smith, C.P. Grey, K. Hermansson, G Csányi
Publié dans: npj Computational Materials, Numéro 9, 2023, Page(s) 146, ISSN 2057-3960
Éditeur: Springer Nature
DOI: 10.1038/s41524-023-01100-w

Machine learning 3D-resolved prediction of electrolyte infiltration in battery porous electrodes

Auteurs: Abbos Shodiev; Abbos Shodiev; Marc Duquesnoy; Marc Duquesnoy; Oier Arcelus; Oier Arcelus; Mehdi Chouchane; Mehdi Chouchane; Jianlin Li; Alejandro A. Franco
Publié dans: Journal of Power Sources, Numéro 511, 2021, Page(s) 230384, ISSN 0378-7753
Éditeur: Elsevier BV
DOI: 10.1016/j.jpowsour.2021.230384

Data Management Plans: the Importance of Data Management in the BIG-MAP Project

Auteurs: Ivano Eligio Castelli, Daniel J. Arismendi-Arrieta, Arghya Bhowmik, Isidora Cekic-Laskovic, Simon Clark, Robert Dominko, Eibar Flores, Jackson Flowers, Karina Ulvskov Frederiksen, Jesper Friis, Alexis Grimaud, Karin Vels Hansen, Laurence J. Hardwick, Kersti Hermansson, Lukas Königer, Hanne Lauritzen, Frédéric Le Cras, Hongjiao Li, Sandrine Lyonnard, Henning Lorrmann, Nicola Marzari, Leszek Nied
Publié dans: Batteries & Supercaps, 2021, ISSN 2566-6223
Éditeur: Wiley-VCH on behalf of Chemistry Europe
DOI: 10.1002/batt.202100117

An Overview on Transport Phenomena within Solid Electrolyte Interphase and Their Impact on the Performance and Durability of Lithium-Ion Batteries

Auteurs: Roberta Cappabianca; Paolo De Angelis; Matteo Fasano; Eliodoro Chiavazzo; Pietro Asinari
Publié dans: Energies, Numéro 16 (13), 2023, Page(s) 5003, ISSN 1996-1073
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/en16135003

Unravelling degradation mechanisms and overpotential sources in aged and non-aged batteries: A non-invasive diagnosis

Auteurs: Williams Agyei Appiah, Laura Hannemose Rieger, Eibar Flores, Tejs Vegge, Arghya Bhowmik
Publié dans: Journal of Energy Storage, Numéro 84, 2024, Page(s) 111000, ISSN 2352-1538
Éditeur: Elsevier
DOI: 10.1016/j.est.2024.111000

Enhancing ReaxFF for molecular dynamics simulations of lithium-ion batteries: an interactive reparameterization protocol

Auteurs: Paolo De Angelis, Roberta Cappabianca, Matteo Fasano, Pietro Asinari, Eliodoro Chiavazzo
Publié dans: Scientific Reports, Numéro 14, 2024, Page(s) 978, ISSN 2045-2322
Éditeur: Nature Publishing Group
DOI: 10.1038/s41598-023-50978-5

Selected machine learning of HOMO-LUMO gaps with improved data-efficiency.

Auteurs: Bernard Mazouin; Alexandre Alain Schöpfer; O. Anatole von Lilienfeld
Publié dans: Materials Advances, Numéro 3, 2022, Page(s) 8306-8316, ISSN 2633-5409
Éditeur: Royal society of chemistry
DOI: 10.1039/d2ma00742h

Sensitivity analysis methodology for battery degradation models

Auteurs: Williams Agyei Appiah, Jonas Busk, Tejs Vegge, Arghya Bhowmik
Publié dans: Electrochimica Acta, Numéro Vol 439, 2023, Page(s) 141430, ISSN 0013-4686
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.electacta.2022.141430

Dynamic Structure Discovery Applied to the Ion Transport in the Ubiquitous Lithium-ion Battery Electrolyte LP30

Auteurs: Rasmus Andersson, Oleg Borodin, Patrik Johansson
Publié dans: Journal of The Electrochemical Society, Numéro 169, 2022, Page(s) 100540, ISSN 0013-4651
Éditeur: Electrochemical Society, Inc.
DOI: 10.1149/1945-7111/ac96af

Evolutionary Monte Carlo of QM Properties in Chemical Space: Electrolyte Design

Auteurs: Konstantin Karandashev, Jan Weinreich, Stefan Heinen, Daniel Jose Arismendi Arrieta, Guido Falk von Rudorff, Kersti Hermansson, and O. Anatole von Lilienfeld
Publié dans: J. Chem. Theory Comput., Numéro 19 (23), 2023, Page(s) 8861–8870, ISSN 1549-9626
Éditeur: American Chemical Society
DOI: 10.1021/acs.jctc.3c00822

Modeling the Solid Electrolyte Interphase - Machine Learning as a Game Changer?

Auteurs: D Diddens, WA Appiah, Y Mabrouk, A Heuer, T Vegge, A Bhowmik
Publié dans: Advanced Materials Interfaces, 2022, ISSN 2196-7350
Éditeur: Wiley
DOI: 10.1002/admi.202101734

Machine learning for optimal electrode wettability in lithium ion batteries

Auteurs: Amina El Malki, Mark Asch, Oier Arcelus, Abbos Shodiev, Jia Yu, Alejandro A. Franco
Publié dans: Journal of Power Sources Advances, Numéro 20, 2023, Page(s) 100114, ISSN 2666-2485
Éditeur: Elsevier
DOI: 10.1016/j.powera.2023.100114

Understanding Battery Interfaces by Combined Characterization and Simulation Approaches: Challenges and Perspectives

Auteurs: Duncan Atkins; Elixabete Ayerbe; Anass Benayad; Federico G. Capone; Ennio Capria; Ivano E. Castelli; Isidora Cekic‐Laskovic; Raul Ciria; Lenart Dudy; Kristina Edström; Mark R. Johnson; Hongjiao Li; Juan Maria Garcia Lastra; Matheus Leal De Souza; Valentin Meunier; Mathieu Morcrette; Harald Reichert; Patrice Simon; Jean‐Pascal Rueff; Jonas Sottmann; Wolfgang Wenzel; Alexis Grimaud
Publié dans: Advanced Energy Materials, 2021, Page(s) 2102687, ISSN 1614-6840
Éditeur: Wiley-VCH GmbH
DOI: 10.1002/aenm.202102687

Brokering between tenants for demonstration of an international materials acceleration platform

Auteurs: M. Vogler, J. Busk, H. Hajiyani, P.B. Jørgensen, N. Safaei, I.E. Castelli, F.F. Ramirez, J. Carlsson, G. Pizzi, S. Clark, F. Hanke, A. Bhowmik, H.S. Stein
Publié dans: Matter, Numéro 6 (9), 2023, Page(s) 2647-2665, ISSN 2590-2385
Éditeur: Cellpress
DOI: 10.1016/j.matt.2023.07.016

Principles of the Battery Data Genome

Auteurs: L. Ward, S. Babinec, E.J. Dufek, D.A. Howey, V. Viswanathan, M. Aykol, D.A.C. Beck, B. Blaiszik, B.-R. Chen, G. Crabtree, S. Clark, V. De Angelis, P. Dechent, M. Dubarry, E.E. Eggleton, D.P. Finegan, I. Foster, C.B. Gopal, P.K. Herring, V.W. Hu, N.H. Paulson, Y. Preger, D. Uwe-Sauer, K. Smith, S.W. Snyder, S. Sripad, T.R. Tanim, L. Teo
Publié dans: Joule, Numéro 6, 2022, Page(s) 2253-2271, ISSN 2542-4351
Éditeur: Cellpress
DOI: 10.1016/j.joule.2022.08.008

Artificial Intelligence Applied to Battery Research: Hype or Reality?

Auteurs: Teo Lombardo; Marc Duquesnoy; Hassna El-Bouysidy; Fabian Årén; Alfonso Gallo-Bueno; Peter Bjørn Jørgensen; Arghya Bhowmik; Arnaud Demortière; Elixabete Ayerbe; Francisco Alcaide; Marine Reynaud; Javier Carrasco; Alexis Grimaud; Chao Zhang; Tejs Vegge; Patrik Johansson; Alejandro A. Franco
Publié dans: Chemical Reviews, 2021, ISSN 0009-2665
Éditeur: American Chemical Society
DOI: 10.1021/acs.chemrev.1c00108

NMRium: Teaching nuclear magnetic resonance spectra interpretation in an online platform

Auteurs: Luc Patiny; Hamed Musallam; Alejandro Bolaños; Michaël Zasso; Julien Wist; Metin Karayilan; Eva Ziegler; Johannes C Liermann; Nils E Schlörer
Publié dans: Beilstein J. Org. Chem., Numéro 20, 2024, Page(s) 25-31, ISSN 1860-5397
Éditeur: Beilstein-Institut
DOI: 10.3762/bjoc.20.4

Electrochemical Protocols to Assess the Effects of Dissolved Transition Metal in Graphite/LiNiO₂ Cells Performance

Auteurs: Valentin Meunier; Matheus Leal De Souza; Mathieu Morcrette; Alexis Grimaud
Publié dans: Journal of The Electrochemical Society, Numéro 169, 2022, Page(s) 070506, ISSN 0013-4651
Éditeur: Electrochemical Society, Inc.
DOI: 10.1149/1945-7111/ac7e7a

Designing electrode architectures to facilitate electrolyte infiltration for lithium-ion batteries

Auteurs: Abbos Shodiev; Franco M. Zanotto; Jia Yu; Mehdi Chouchane; Jianlin Li; Alejandro A. Franco
Publié dans: Energy Storage Materials, Numéro 49, 2022, Page(s) 268-277, ISSN 2405-8297
Éditeur: Elsevier B.V.
DOI: 10.1016/j.ensm.2022.03.049

The potential of scanning electrochemical probe microscopy and scanning droplet cells in battery research

Auteurs: Sven Daboss, Fuzhan Rahmanian, Helge Stein, Christine Kranz
Publié dans: Electrochemical Science Advances, 2021, ISSN 2698-5977
Éditeur: Wiley
DOI: 10.1002/elsa.202100122

Enabling Modular Autonomous Feedback-Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration

Auteurs: Fuzhan Rahmanian, Jackson Flowers, Dan Guevarra, Matthias Richter, John M. Gregoire, Helge S. Stein
Publié dans: Advanced Materials interfaces, Numéro 9, 2022, Page(s) 2101987, ISSN 2196-7350
Éditeur: Wiley-VCH GmbH
DOI: 10.1002/admi.202101987

Near Infrared Sensor Setup for General Interface Detection in Automatic Liquid-Liquid Extraction Processes

Auteurs: R. Moreno, A. Faina and K. Stoy
Publié dans: IEEE Sensors Journal, Numéro vol. 22, no. 10, 2022, Page(s) 9857-9867, ISSN 1530-437X
Éditeur: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jsen.2022.3164188

Robotic cell assembly to accelerate battery research

Auteurs: Bojing Zhang; Leon Merker; Alexey Sanin; Helge S. Stein
Publié dans: Digital Discovery, Numéro 1, 2022, Page(s) 733, ISSN 2635-098X
Éditeur: Royal Society of Chemistry
DOI: 10.1039/d2dd00046f

Blended-salt electrolyte design for advanced NMC811ǁGraphite cell performance

Auteurs: Peng Yan, Mykhailo Shevchuk, Christian Wölke, Felix Pfeiffer, Debbie Berghus, Masoud Baghernejad, Gerd-Volker Röschenthaler, Martin Winter, Isidora Cekic-Laskovic
Publié dans: Small Structures, Numéro 2300425, 2023, ISSN 2688-4062
Éditeur: Wiley-VCH GmbH
DOI: 10.1002/sstr.202300425

Ionic conductivity, viscosity, and self-diffusion coefficients of novel imidazole salts for lithium-ion battery electrolytes

Auteurs: Anna Szczęsna-Chrzan; Monika Vogler; Peng Yan; Grażyna Zofia Żukowska; Christian Wölke; Agnieszka Ostrowska; Sara Szymańska; Marek Marcinek; Martin Winter; Isidora Cekic-Laskovic; Władysław Wieczorek; Helge S. Stein
Publié dans: Journal of Materials Chemistry A, Numéro 11, 2023, Page(s) 13483-13492, ISSN 2050-7496
Éditeur: Royal Society of Chemistry
DOI: 10.1039/d3ta01217d

A Fully-Reduced, Highly-Disordered Nitride-Halide Electrolyte for Solid-State Batteries with Lithium-Metal Anodes

Auteurs: Victor Landgraf; Theodosios Famprikis; Joris de Leeuw; Lars Johannes Bannenberg; Swapna Ganapathy; Marnix Wagemaker
Publié dans: Applied Energy Materials, Numéro 6, 2023, Page(s) 1661−1672, ISSN 2574-0962
Éditeur: ACS Publications
DOI: 10.1021/acsaem.2c03551

Data-Driven Analysis of High-Throughput Experiments on Liquid Battery Electrolyte Formulations: Unraveling the Impact of Composition on Conductivity

Auteurs: Anand Narayanan Krishnamoorthy, Christian Wölke, Diddo Diddens, Moumita Maiti, Youssef Mabrouk, Peng Yan, Mariano Grünebaum, Martin Winter, Andreas Heuer, Isidora Cekic-Laskovic
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Machine learning of free energies in chemical compound space using ensemble representations: Reaching experimental uncertainty for solvation

Auteurs: Jan Weinreich, Nicholas J. Browning, O. Anatole von Lilienfeld
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The effect of doping process route on LiNiO2 cathode material properties

Auteurs: S.L. Dreyer, P. Kurzhals, S.B. Seiffert, P. Müller, A. Kondrakov, T. Brezesinski, J. Janek
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Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forces

Auteurs: Jonas Busk, Mikkel N. Schmidt, Ole Winther, Tejs Vegge, Peter Bjørn Jørgensen
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Uncertainty-aware and explainable machine learning for early prediction of battery degradation trajectory

Auteurs: Laura Hannemose Rieger; Eibar Flores; Kristian Frellesen Nielsen; Poul Norby; Elixabete Ayerbe; Ole Winther; Tejs Vegge; Arghya Bhowmik
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Éditeur: Royal Society of Chemistry
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Understanding the patterns that neural networks learn from chemical spectra

Auteurs: Laura Hannemose Rieger, Max Wilson, Tejs Vegge, Eibar Flores
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Lithium ion battery electrode manufacturing model accounting for 3D realistic shapes of active material particles

Auteurs: Jiahui Xu; Alain C. Ngandjong; Chaoyue Liu; Franco M. Zanotto; Oier Arcelus; Arnaud Demortière; Alejandro A. Franco
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Elucidating an Atmospheric Brown Carbon Species-Toward Supplanting Chemical Intuition with Exhaustive Enumeration and Machine Learning

Auteurs: Enrico Tapavicza; Guido Falk von Rudorff; David O. De Haan; Mario Contin; Christian George; Matthieu Riva; O. Anatole von Lilienfeld
Publié dans: Environmental Science & Technology, 2021, ISSN 0013-936X
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A Solution‐Mediated Pathway for the Growth of the Solid Electrolyte Interphase in Lithium‐Ion Batteries

Auteurs: Meysam Esmaeilpour; Saibal Jana; Hongjiao Li; Mohammad Soleymanibrojeni; Wolfgang Wenzel
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Alchemical geometry relaxation

Auteurs: Domenichini, Giorgio; von Lilienfeld, O. Anatole
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Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT

Auteurs: Surajit Nandi, Jonas Busk, Peter Bjørn Jørgensen, Tejs Vegge, Arghya Bhowmik
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2023 Roadmap on molecular modelling of electrochemical energy materials

Auteurs: Zhang, Chao; Cheng, Jun; Chen, Yiming; Chan, Maria K.Y.; Cai, Qiong; Carvalho, Rodrigo P.; Marchiori, Cleber F.N.; Brandell, D.; Araujo, C. Moyses; Chen, Ming; Ji, Xiangyu; Feng, Guang; Goloviznina, Kateryna; Serva, Alessandra; Salanne, Mathieu; Mandai, Toshihiko; Hosaka, Tomooki; Alhanash, Mirna; Johansson, Patrik; Qiu, Yun Ze; Xiao, Hai; Eikerling, Michael; Jinnouchi, Ryosuke; Melander, Marko M.
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Autonomous Visual Detection of Defects from Battery Electrode Manufacturing

Auteurs: Nirmal Choudhary; Henning Clever; Robert Ludwigs; Michael Rath; Aymen Gannouni; Arno Schmetz; Tom Hülsmann; Julia Sawodny; Leon Fischer; Achim Kampker; Juergen Fleischer; Helge Sören Stein
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Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Auteurs: Miki Bonacci, Junfeng Qiao, Nicola Spallanzani, Antimo Marrazzo, Giovanni Pizzi, Elisa Molinari, Daniele Varsano, Andrea Ferretti, Deborah Prezzi
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Towards a 3D-resolved model of Si/Graphite composite electrodes from manufacturing simulations

Auteurs: Chaoyue Liu, Oier Arcelus, Teo Lombardo, Hassan Oularbi, Alejandro A. Franco
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Virtual Computational Chemistry Teaching Laboratories—Hands-On at a Distance

Auteurs: Rika Kobayashi, Theodorus P. M. Gouman, N. Ole Carstensen, Thomas M. Soini, Nicola Marzari, Iurii Timrov, Samuel Poncé, Edward B. Linscott, Christopher J. Sewell, Giovanni Pizzi, Francisco Ramirez, Marnik Bercx, Sebastiaan Huber, Carl Simon Adorf, and Leopold Talirz
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Conductivity experiments for electrolyte formulations and their automated analysis

Auteurs: Fuzhan Rahmanian; Monika Vogler; Christian Wölke; Peng Yan; Stefan Fuchs; Martin Winter; Isidora Cekic-Laskovic; Helge Sören Stein
Publié dans: Scientific data, Numéro 10, 2023, Page(s) 43, ISSN 2052-4463
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Surface analysis insight note: Accounting for X-ray beam damage effects in positive electrode-electrolyte interphase investigations

Auteurs: Roberto Fantin, Ambroise Van Roekeghem, Jean-Pascal Rueff, Anass Benayad
Publié dans: Surface and interface analysis, 2024, ISSN 0142-2421
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DEST: A Simplified Model and Automated Tool for Loss of Lithium Inventory and Loss of Active Material Estimation in Li-ion Batteries

Auteurs: Francisco J. Méndez-Corbacho, David Nieto-Castro, Iñaki Moreno-Artabe, Diego del Olmo, Giorgio Baraldi, Elixabete Ayerbe
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An active learning approach to model solid-electrolyte interphase formation in Li-ion batteries

Auteurs: M. Soleymanibrojeni, C. R. Caldeira Rego, M. Esmaeilpour, W. Wenzel
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PRISMA: A robust and intuitive tool for high-throughput processing of chemical spectra

Auteurs: Eibar Flores; Nataliia Mozhzhukhina; Xinyu Li; Poul Norby; Aleksandar Matic; Tejs Vegge
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Workflow Engineering in Materials Design within the BATTERY 2030 + Project

Auteurs: Joerg Schaarschmidt; Jie Yuan; Timo Strunk; Ivan Kondov; Sebastiaan P. Huber; Giovanni Pizzi; Leonid Kahle; Felix T. Bölle; Ivano E. Castelli; Tejs Vegge; Felix Hanke; Tilmann Hickel; Jörg Neugebauer; Celso R. C. Rêgo; Wolfgang Wenzel
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One-Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity

Auteurs: Fuzhan Rahmanian, Monika Vogler, Christian Wölke, Peng Yan, Martin Winter, Isidora Cekic-Laskovic, Helge S. Stein
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Accelerating Battery Characterization Using Neutron and Synchrotron Techniques: Toward a Multi-Modal and Multi-Scale Standardized Experimental Workflow

Auteurs: Duncan Atkins; Ennio Capria; Kristina Edström; Theodosios Famprikis; Alexis Grimaud; Quentin Jacquet; Mark Johnson; Aleksandar Matic; Poul Norby; Harald Reichert; Jean‐Pascal Rueff; Claire Villevieille; Marnix Wagemaker; Sandrine Lyonnard
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Rechargeable Batteries of the Future—The State of the Art from a BATTERY 2030+ Perspective

Auteurs: Maximilian Fichtner; Kristina Edström; Elixabete Ayerbe; Maitane Berecibar; Arghya Bhowmik; Ivano E. Castelli; Simon Clark; Robert Dominko; Merve Erakca; Alejandro A. Franco; Alexis Grimaud; Birger Horstmann; Arnulf Latz; Henning Lorrmann; Marcel Meeus; Rekha Narayan; Frank Pammer; Janna Ruhland; Helge Stein; Tejs Vegge; Marcel Weil
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Towards a unified description of battery data

Auteurs: Simon Clark, Jesper Friis, Francesca Lønstad Bleken, Casper Andersen, Eibar Flores, Martin Uhrin, Simon Stier, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, Rosa Palacin
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MultiXC-QM9: Large dataset of molecular and reaction energies from multi-level quantum chemical methods

Auteurs: Surajit Nandi, Tejs Vegge & Arghya Bhowmik
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Accelerating the Adoption of Research Data Management Strategies

Auteurs: Medina, Johanne; Ziaullah, Abdul Wahab; Heesoo Park; Castelli, Ivano E.; Shaon, Arif; Bensmail, Halima; Fedwa El-Mellouhi
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Greener, Safer and Better Performing Aqueous Binder for Positive Electrode Manufacturing of Sodium Ion Batteries

Auteurs: Ruochen Xu, Venkat Pamidi, Yushu Tang, Stefan Fuchs, Helge S. Stein, Bosubabu Dasari, Zhirong Zhao-Karger, Santosh Behara, Yang Hu, Shivam Trivedi, M. Anji Reddy, Prabeer Barpanda, Maximilian Fichtner
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Digitalization of Battery Manufacturing: Current Status, Challenges, and Opportunities

Auteurs: Elixabete Ayerbe; Maitane Berecibar; Simon Clark; Alejandro A. Franco; Janna Ruhland
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On-the-fly assessment of diffusion barriers of disordered transition metal oxyfluorides using local descriptors

Auteurs: Jin Hyun Chang, Peter Bjørn Jørgensen, Simon Loftager, Arghya Bhowmik, Juan María García Lastra, Tejs Vegge
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Electrochemistry Visualization Tool to Support the Electrochemical Analysis of Batteries

Auteurs: M.L. de Souza, M. Duquesnoy, M. Morcrette, A.A. Franco
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Perspectives on manufacturing simulations of Li-S battery cathodes

Auteurs: Oier Arcelus; Alejandro A Franco
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wfl Python toolkit for creating machine learning interatomic potentials and related atomistic simulation workflows

Auteurs: Elena Gelžinytė, Simon Wengert, Tamás K. Stenczel, Hendrik H. Heenen, Karsten Reuter, Gábor Csányi, Noam Bernstein
Publié dans: The Journal of Chemical Physics, Numéro 159, 2023, Page(s) 124801, ISSN 0021-9606
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Toward Operando Characterization of Interphases in Batteries

Auteurs: Maibach, Julia; Rizell, Josef; Matic, Aleksandar; Mozhzhukhina, Nataliia
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Toward the design of chemical reactions: Machine learning barriers of competing mechanisms in reactant space.

Auteurs: Stefan Heinen; Stefan Heinen; Guido Falk von Rudorff; Guido Falk von Rudorff; O. Anatole von Lilienfeld; O. Anatole von Lilienfeld
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How beam damage can skew synchrotron operando studies of batteries

Auteurs: T. Jousseaume, J.-F. Colin, M. Chandesris, S. Lyonnard, S. Tardif
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Computationally Efficient Quasi-3D Model of a Secondary Electrode Particle for Enhanced Prediction Capability of the Porous Electrode Model

Auteurs: Klemen Zelič; Tomaž Katrašnik
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Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials

Auteurs: Siwoo Lee, Stefan Heinen, Danish Khan, O Anatole von Lilienfeld
Publié dans: Machine Learning: Science and Technology, Numéro 5, 2024, Page(s) 015052, ISSN 2632-2153
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Mechanistic understanding of the correlation between structure and dynamics of liquid carbonate electrolytes: Impact of polarization

Auteurs: M. Maiti, A. N. Krishnamoorthy, Y. Mabrouk, N. Mozhzhukhina, A. Matic, D. Diddens and A. Heuer
Publié dans: Phys. Chem. Chem. Phys., 2023, ISSN 1463-9076
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Jahn–Teller Distortions and Phase Transitions in LiNiO2: Insights from Ab Initio Molecular Dynamics and Variable-Temperature X-ray Diffraction

Auteurs: Annalena R. Genreith-Schriever, Alexandra Alexiu, George S. Phillips, Chloe S. Coates, Liam A. V. Nagle-Cocco, Joshua D. Bocarsly, Farheen N. Sayed, Siân E. Dutton, and Clare P. Grey
Publié dans: Chem. Mater., 2024, ISSN 0897-4756
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Machine learning based energy-free structure predictions of molecules (closed and open-shell), transition states, and solids

Auteurs: Lemm, Dominik; von Rudorff, Guido Falk; von Lilienfeld, O. Anatole
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Resolving the Role of Configurational Entropy in Improving Cycling Performance of Multicomponent Hexacyanoferrate Cathodes for Sodium-Ion Batteries

Auteurs: Yanjiao Ma, Yang Hu,Yohanes Pramudya, Thomas Diemant, Qingsong Wang, Damian Goonetilleke, Yushu Tang, Bei Zhou, Horst Hahn, Wolfgang Wenzel, Maximilian Fichtner, Yuan Ma, Ben Breitung, Torsten Brezesinski
Publié dans: Advanced Functional Materials, Numéro 32, 2022, Page(s) 2202372, ISSN 1616-301X
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