Battery Interface Genome - Materials Acceleration Platform | BIG-MAP | Project | Results | H2020 | CORDIS

Risultati finali

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

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

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.

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.

Pubblicazioni

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

Autori: Bhowmik, Berecibar, Casas-Cabanas, Csanyi, Dominko, Hermansson, Palacin, Stein, Vegge
Pubblicato in: Advanced Energy Materials, 2021, ISSN 1614-6840
Editore: Wiley
DOI: 10.1002/aenm.202102698

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

Autori: Eibar Flores, Christian Wölke, Peng Yan, Martin Winter, Tejs Vegge, Isidora Cekic-Laskovic and Arghya Bhowmik
Pubblicato in: Digital Discovery, Numero 1, 2022, Pagina/e 440-447, ISSN 2635-098X
Editore: Royal Society of Chemistry
DOI: 10.1039/d2dd00027j

An orbital-based representation for accurate quantum machine learning

Autori: Konstantin Karandashev, O. Anatole von Lilienfeld
Pubblicato in: J. Chem. Phys., Numero 156, 2022, Pagina/e 114101, ISSN 0021-9606
Editore: American Institute of Physics
DOI: 10.1063/5.0083301

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

Autori: 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
Pubblicato in: Advanced Energy Materials, 2021, ISSN 1614-6840
Editore: Wiley
DOI: 10.1002/aenm.202102678

Accelerated Workflow for Antiperovskite‐based Solid State Electrolytes

Autori: Benjamin H. Sjølin; Peter B. Jørgensen; Andrea Fedrigucci; Tejs Vegge; Arghya Bhowmik; Ivano E. Castelli
Pubblicato in: Batteries and Supercaps, Numero 6 (6), 2023, Pagina/e e202300041, ISSN 2566-6223
Editore: 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)

Autori: Dirk Bakowies, O. Anatole von Lilienfeld
Pubblicato in: Journal of Chemical Theory and Computation, Numero 17/8, 2021, Pagina/e 4872-4890, ISSN 1549-9618
Editore: 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

Autori: V. Meunier, F. Capone, R. Dedryvère, A. Grimaud
Pubblicato in: J. Electrochem. Soc., Numero 170, 2023, Pagina/e 060551, ISSN 1945-7111
Editore: The Electrochemical Society
DOI: 10.1149/1945-7111/ace031

Leveraging Composition-Based Material Descriptors for Machine Learning Optimization

Autori: Trezza, Giovanni; Chiavazzo, Eliodoro
Pubblicato in: Materials Today Communications, Numero 36, 2023, Pagina/e 106579, ISSN 2352-4928
Editore: Elsevier BV
DOI: 10.1016/j.mtcomm.2023.106579

NeuralNEB—neural networks can find reaction paths fast

Autori: Mathias Schreiner; Arghya Bhowmik; Tejs Vegge; Peter Bjørn Jørgensen; Ole Winther
Pubblicato in: Machine Learning: Science and Technology, Numero 3, 2022, Pagina/e 045022, ISSN 2632-2153
Editore: IOP Publishing
DOI: 10.1088/2632-2153/aca23e

Ab Initio Machine Learning in Chemical Compound Space

Autori: Bing Huang, O. Anatole von Lilienfeld
Pubblicato in: Chemical Reviews, Numero 121/16, 2021, Pagina/e 10001-10036, ISSN 0009-2665
Editore: American Chemical Society
DOI: 10.1021/acs.chemrev.0c01303

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

Autori: Max Wilson, Saverio Moroni, Markus Holzmann, Nicholas Gao, Filip Wudarski, Tejs Vegge, Arghya Bhowmik
Pubblicato in: Phys. Rev. B, Numero 107, 2023, Pagina/e 235139, ISSN 2469-9950
Editore: American Physical Society
DOI: 10.1103/physrevb.107.235139

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

Autori: D. Du, T. J. Baird, S. Bonella, G. Pizzi
Pubblicato in: Computer Physics Communications, Numero 282, 2023, Pagina/e 108546, ISSN 0010-4655
Editore: Elsevier BV
DOI: 10.1016/j.cpc.2022.108546

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

Autori: Joonyeob Jeon; Gil Ho Yoon; Tejs Vegge; Jin Hyun Chang
Pubblicato in: ACS Appl. Mater. Interfaces, 2022, ISSN 1944-8244
Editore: 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

Autori: Abbos Shodiev, Mehdi Chouchane, Miran Gaberscek, Oier Arcelus, Jiahui Xu, Hassan Oularbi, Jia Yu, Jianlin Li, Mathieu Morcrette, Alejandro A. Franco
Pubblicato in: Energy Storage Materials, Numero 47, 2022, Pagina/e 462-471, ISSN 2405-8289
Editore: Elsevier
DOI: 10.1016/j.ensm.2022.01.058

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

Autori: 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
Pubblicato in: Nature Communications, Numero 12, 2021, Pagina/e 6047, ISSN 2041-1723
Editore: Nature Publishing Group
DOI: 10.3204/pubdb-2021-02598

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

Autori: Valentin Meunier, Matheus Leal De Souza, Mathieu Morcrette, Alexis Grimaud
Pubblicato in: Joule, Numero 7, 2022, Pagina/e 42-56, ISSN 2542-4351
Editore: 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

Autori: Kristoffer Visti Graae; Xinyu Li; Daniel Risskov Sørensen; Elixabete Ayerbe; Iker Boyano; Denis Sheptyakov; Mads Ry Vogel Jørgensen; Poul Norby
Pubblicato in: Journal of Power Sources, Numero 570, 2023, Pagina/e 232993, ISSN 1873-2755
Editore: Elsevier
DOI: 10.1016/j.jpowsour.2023.232993

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

Autori: Jonas Busk; Peter Bjørn Jørgensen; Arghya Bhowmik; Mikkel N. Schmidt; Ole Winther; Tejs Vegge
Pubblicato in: Machine Learning: Science and Technology, Numero 3, 2022, Pagina/e 015012, ISSN 2632-2153
Editore: IOP
DOI: 10.1088/2632-2153/ac3eb3

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

Autori: David Kleiven; Jaakko Akola; Andrew A Peterson; Tejs Vegge; Jin Hyun Chang
Pubblicato in: JPhys Energy, Numero 3, 2021, Pagina/e 034012, ISSN 2515-7655
Editore: IOPscience
DOI: 10.1088/2515-7655/abf9ef

Transition1x - a dataset for building generalizable reactive machine learning potentials

Autori: Mathias Schreiner; Arghya Bhowmik; Tejs Vegge; Jonas Busk; Ole Winther
Pubblicato in: Scientific Data, Numero 9, 2022, ISSN 2052-4463
Editore: Springer Nature
DOI: 10.1038/s41597-022-01870-w

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

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

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

Autori: Tejs Vegge, Jean-Marie Tarascon and Kristina Edström
Pubblicato in: Adv. Energy Mater., Numero 11, 2021, Pagina/e 2100362, ISSN 1614-6840
Editore: Wiley-VCH GmbH
DOI: 10.1002/aenm.202100362

Advances in studying interfacial reactions in rechargeable batteries by photoelectron spectroscopy

Autori: Ida Källquist; Ronan Le Ruyet; Haidong Liu; Ronnie Mogensen; Ming-Tao Lee; Kristina Edström; Andrew J. Naylor
Pubblicato in: J. Mater. Chem. A, Numero 10, 2022, Pagina/e 19466-19505, ISSN 1364-5501
Editore: Royal Society of Chemistry
DOI: 10.1039/d2ta03242b

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

Autori: Raul Ortega Ochoa; Bardi Benediktsson; Renata Sechi; Peter Bjørn Jørgensen; Arghya Bhowmik
Pubblicato in: Journal of Materials Chemistry A, Numero 11, 2023, Pagina/e 26551, ISSN 2050-7496
Editore: The royal society of chemistry
DOI: 10.1039/d3ta05860c

Phase Separating Electrode Materials – Chemical Inductors?

Autori: Klemen Zelič; Igor Mele; Arghya Bhowmik; Tomaž Katrašnik
Pubblicato in: Energy storage materials, Numero 56, 2023, Pagina/e 489-494, ISSN 2405-8297
Editore: Elsevier
DOI: 10.1016/j.ensm.2023.01.008

Towards autonomous high-throughput multiscale modelling of battery interfaces

Autori: Zeyu Deng; Vipin Kumar; Felix T. Bölle; Fernando Caro; Alejandro A. Franco; Ivano E. Castelli; Pieremanuele Canepa; Zhi Wei Seh
Pubblicato in: Energy & Environmental Science, Numero 15, 2022, Pagina/e 579-594, ISSN 1754-5706
Editore: Royal Society of Chemistry
DOI: 10.1039/d1ee02324a

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

Autori: I.-B. Magdău, D.J. Arismendi-Arrieta, H.E. Smith, C.P. Grey, K. Hermansson, G Csányi
Pubblicato in: npj Computational Materials, Numero 9, 2023, Pagina/e 146, ISSN 2057-3960
Editore: Springer Nature
DOI: 10.1038/s41524-023-01100-w

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

Autori: Abbos Shodiev; Abbos Shodiev; Marc Duquesnoy; Marc Duquesnoy; Oier Arcelus; Oier Arcelus; Mehdi Chouchane; Mehdi Chouchane; Jianlin Li; Alejandro A. Franco
Pubblicato in: Journal of Power Sources, Numero 511, 2021, Pagina/e 230384, ISSN 0378-7753
Editore: Elsevier BV
DOI: 10.1016/j.jpowsour.2021.230384

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

Autori: 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
Pubblicato in: Batteries & Supercaps, 2021, ISSN 2566-6223
Editore: 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

Autori: Roberta Cappabianca; Paolo De Angelis; Matteo Fasano; Eliodoro Chiavazzo; Pietro Asinari
Pubblicato in: Energies, Numero 16 (13), 2023, Pagina/e 5003, ISSN 1996-1073
Editore: 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

Autori: Williams Agyei Appiah, Laura Hannemose Rieger, Eibar Flores, Tejs Vegge, Arghya Bhowmik
Pubblicato in: Journal of Energy Storage, Numero 84, 2024, Pagina/e 111000, ISSN 2352-1538
Editore: Elsevier
DOI: 10.1016/j.est.2024.111000

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

Autori: Paolo De Angelis, Roberta Cappabianca, Matteo Fasano, Pietro Asinari, Eliodoro Chiavazzo
Pubblicato in: Scientific Reports, Numero 14, 2024, Pagina/e 978, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-023-50978-5

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

Autori: Bernard Mazouin; Alexandre Alain Schöpfer; O. Anatole von Lilienfeld
Pubblicato in: Materials Advances, Numero 3, 2022, Pagina/e 8306-8316, ISSN 2633-5409
Editore: Royal society of chemistry
DOI: 10.1039/d2ma00742h

Sensitivity analysis methodology for battery degradation models

Autori: Williams Agyei Appiah, Jonas Busk, Tejs Vegge, Arghya Bhowmik
Pubblicato in: Electrochimica Acta, Numero Vol 439, 2023, Pagina/e 141430, ISSN 0013-4686
Editore: 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

Autori: Rasmus Andersson, Oleg Borodin, Patrik Johansson
Pubblicato in: Journal of The Electrochemical Society, Numero 169, 2022, Pagina/e 100540, ISSN 0013-4651
Editore: Electrochemical Society, Inc.
DOI: 10.1149/1945-7111/ac96af

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

Autori: Konstantin Karandashev, Jan Weinreich, Stefan Heinen, Daniel Jose Arismendi Arrieta, Guido Falk von Rudorff, Kersti Hermansson, and O. Anatole von Lilienfeld
Pubblicato in: J. Chem. Theory Comput., Numero 19 (23), 2023, Pagina/e 8861–8870, ISSN 1549-9626
Editore: American Chemical Society
DOI: 10.1021/acs.jctc.3c00822

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

Autori: D Diddens, WA Appiah, Y Mabrouk, A Heuer, T Vegge, A Bhowmik
Pubblicato in: Advanced Materials Interfaces, 2022, ISSN 2196-7350
Editore: Wiley
DOI: 10.1002/admi.202101734

Machine learning for optimal electrode wettability in lithium ion batteries

Autori: Amina El Malki, Mark Asch, Oier Arcelus, Abbos Shodiev, Jia Yu, Alejandro A. Franco
Pubblicato in: Journal of Power Sources Advances, Numero 20, 2023, Pagina/e 100114, ISSN 2666-2485
Editore: Elsevier
DOI: 10.1016/j.powera.2023.100114

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

Autori: 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
Pubblicato in: Advanced Energy Materials, 2021, Pagina/e 2102687, ISSN 1614-6840
Editore: Wiley-VCH GmbH
DOI: 10.1002/aenm.202102687

Brokering between tenants for demonstration of an international materials acceleration platform

Autori: 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
Pubblicato in: Matter, Numero 6 (9), 2023, Pagina/e 2647-2665, ISSN 2590-2385
Editore: Cellpress
DOI: 10.1016/j.matt.2023.07.016

Principles of the Battery Data Genome

Autori: 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
Pubblicato in: Joule, Numero 6, 2022, Pagina/e 2253-2271, ISSN 2542-4351
Editore: Cellpress
DOI: 10.1016/j.joule.2022.08.008

Artificial Intelligence Applied to Battery Research: Hype or Reality?

Autori: 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
Pubblicato in: Chemical Reviews, 2021, ISSN 0009-2665
Editore: American Chemical Society
DOI: 10.1021/acs.chemrev.1c00108

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

Autori: Luc Patiny; Hamed Musallam; Alejandro Bolaños; Michaël Zasso; Julien Wist; Metin Karayilan; Eva Ziegler; Johannes C Liermann; Nils E Schlörer
Pubblicato in: Beilstein J. Org. Chem., Numero 20, 2024, Pagina/e 25-31, ISSN 1860-5397
Editore: Beilstein-Institut
DOI: 10.3762/bjoc.20.4

Electrochemical Protocols to Assess the Effects of Dissolved Transition Metal in Graphite/LiNiO<sub>2</sub> Cells Performance

Autori: Valentin Meunier; Matheus Leal De Souza; Mathieu Morcrette; Alexis Grimaud
Pubblicato in: Journal of The Electrochemical Society, Numero 169, 2022, Pagina/e 070506, ISSN 0013-4651
Editore: Electrochemical Society, Inc.
DOI: 10.1149/1945-7111/ac7e7a

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

Autori: Abbos Shodiev; Franco M. Zanotto; Jia Yu; Mehdi Chouchane; Jianlin Li; Alejandro A. Franco
Pubblicato in: Energy Storage Materials, Numero 49, 2022, Pagina/e 268-277, ISSN 2405-8297
Editore: 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

Autori: Sven Daboss, Fuzhan Rahmanian, Helge Stein, Christine Kranz
Pubblicato in: Electrochemical Science Advances, 2021, ISSN 2698-5977
Editore: Wiley
DOI: 10.1002/elsa.202100122

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

Autori: Fuzhan Rahmanian, Jackson Flowers, Dan Guevarra, Matthias Richter, John M. Gregoire, Helge S. Stein
Pubblicato in: Advanced Materials interfaces, Numero 9, 2022, Pagina/e 2101987, ISSN 2196-7350
Editore: Wiley-VCH GmbH
DOI: 10.1002/admi.202101987

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

Autori: R. Moreno, A. Faina and K. Stoy
Pubblicato in: IEEE Sensors Journal, Numero vol. 22, no. 10, 2022, Pagina/e 9857-9867, ISSN 1530-437X
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jsen.2022.3164188

Robotic cell assembly to accelerate battery research

Autori: Bojing Zhang; Leon Merker; Alexey Sanin; Helge S. Stein
Pubblicato in: Digital Discovery, Numero 1, 2022, Pagina/e 733, ISSN 2635-098X
Editore: Royal Society of Chemistry
DOI: 10.1039/d2dd00046f

Blended-salt electrolyte design for advanced NMC811ǁGraphite cell performance

Autori: Peng Yan, Mykhailo Shevchuk, Christian Wölke, Felix Pfeiffer, Debbie Berghus, Masoud Baghernejad, Gerd-Volker Röschenthaler, Martin Winter, Isidora Cekic-Laskovic
Pubblicato in: Small Structures, Numero 2300425, 2023, ISSN 2688-4062
Editore: Wiley-VCH GmbH
DOI: 10.1002/sstr.202300425

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

Autori: 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
Pubblicato in: Journal of Materials Chemistry A, Numero 11, 2023, Pagina/e 13483-13492, ISSN 2050-7496
Editore: Royal Society of Chemistry
DOI: 10.1039/d3ta01217d

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

Autori: Victor Landgraf; Theodosios Famprikis; Joris de Leeuw; Lars Johannes Bannenberg; Swapna Ganapathy; Marnix Wagemaker
Pubblicato in: Applied Energy Materials, Numero 6, 2023, Pagina/e 1661−1672, ISSN 2574-0962
Editore: 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

Autori: Anand Narayanan Krishnamoorthy, Christian Wölke, Diddo Diddens, Moumita Maiti, Youssef Mabrouk, Peng Yan, Mariano Grünebaum, Martin Winter, Andreas Heuer, Isidora Cekic-Laskovic
Pubblicato in: Chemistry Methods, Numero 2, 2022, Pagina/e e20220000, ISSN 2628-9725
Editore: Wiley-VCH GmbH
DOI: 10.1002/cmtd.202200008

Machine learning of free energies in chemical compound space using ensemble representations: Reaching experimental uncertainty for solvation

Autori: Jan Weinreich, Nicholas J. Browning, O. Anatole von Lilienfeld
Pubblicato in: The Journal of Chemical Physics, Numero 154/13, 2021, Pagina/e 134113, ISSN 0021-9606
Editore: American Institute of Physics
DOI: 10.1063/5.0041548

The effect of doping process route on LiNiO2 cathode material properties

Autori: S.L. Dreyer, P. Kurzhals, S.B. Seiffert, P. Müller, A. Kondrakov, T. Brezesinski, J. Janek
Pubblicato in: J. Electrochem. Soc., Numero 170, 2023, Pagina/e 060530, ISSN 1945-7111
Editore: IOPScience
DOI: 10.1149/1945-7111/acdd21

Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forces

Autori: Jonas Busk, Mikkel N. Schmidt, Ole Winther, Tejs Vegge, Peter Bjørn Jørgensen
Pubblicato in: Phys. Chem. Chem. Phys., Numero 25, 2023, Pagina/e 25828-25837, ISSN 1463-9084
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Uncertainty-aware and explainable machine learning for early prediction of battery degradation trajectory

Autori: Laura Hannemose Rieger; Eibar Flores; Kristian Frellesen Nielsen; Poul Norby; Elixabete Ayerbe; Ole Winther; Tejs Vegge; Arghya Bhowmik
Pubblicato in: Digital Discovery, Numero 2, 2023, Pagina/e 112–122, ISSN 2635-098X
Editore: Royal Society of Chemistry
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Understanding the patterns that neural networks learn from chemical spectra

Autori: Laura Hannemose Rieger, Max Wilson, Tejs Vegge, Eibar Flores
Pubblicato in: Digital discovery, Numero 2, 2023, Pagina/e 1957-1968, ISSN 2635-098X
Editore: Royal Society of Chemistry
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Lithium ion battery electrode manufacturing model accounting for 3D realistic shapes of active material particles

Autori: Jiahui Xu; Alain C. Ngandjong; Chaoyue Liu; Franco M. Zanotto; Oier Arcelus; Arnaud Demortière; Alejandro A. Franco
Pubblicato in: Journal of Power Sources, Numero 554, 2023, Pagina/e 232294, ISSN 1873-2755
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Elucidating an Atmospheric Brown Carbon Species-Toward Supplanting Chemical Intuition with Exhaustive Enumeration and Machine Learning

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

Autori: Meysam Esmaeilpour; Saibal Jana; Hongjiao Li; Mohammad Soleymanibrojeni; Wolfgang Wenzel
Pubblicato in: Advanced Energy Materials, Numero 13, 2023, Pagina/e 2203966, ISSN 1614-6840
Editore: Wiley-VCH Gmbh
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Alchemical geometry relaxation

Autori: Domenichini, Giorgio; von Lilienfeld, O. Anatole
Pubblicato in: J. Chem. Phys., Numero 156, 2022, Pagina/e 184801, ISSN 1089-7690
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Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT

Autori: Surajit Nandi, Jonas Busk, Peter Bjørn Jørgensen, Tejs Vegge, Arghya Bhowmik
Pubblicato in: J. Chem. Inf. Model., Numero 62, 2022, Pagina/e 4727–4735, ISSN 1549-960X
Editore: American Chemical Society
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2023 Roadmap on molecular modelling of electrochemical energy materials

Autori: 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

Autori: 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
Pubblicato in: Advanced Intelligent Systems, 2022, Pagina/e 2200142, ISSN 2640-4567
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Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Autori: Miki Bonacci, Junfeng Qiao, Nicola Spallanzani, Antimo Marrazzo, Giovanni Pizzi, Elisa Molinari, Daniele Varsano, Andrea Ferretti, Deborah Prezzi
Pubblicato in: npj Computational Materials, Numero 9, 2023, Pagina/e 74, ISSN 2057-3960
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Towards a 3D-resolved model of Si/Graphite composite electrodes from manufacturing simulations

Autori: 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

Autori: 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

Autori: Fuzhan Rahmanian; Monika Vogler; Christian Wölke; Peng Yan; Stefan Fuchs; Martin Winter; Isidora Cekic-Laskovic; Helge Sören Stein
Pubblicato in: Scientific data, Numero 10, 2023, Pagina/e 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

Autori: Roberto Fantin, Ambroise Van Roekeghem, Jean-Pascal Rueff, Anass Benayad
Pubblicato in: Surface and interface analysis, 2024, ISSN 0142-2421
Editore: John Wiley & Sons Inc.
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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

Autori: Francisco J. Méndez-Corbacho, David Nieto-Castro, Iñaki Moreno-Artabe, Diego del Olmo, Giorgio Baraldi, Elixabete Ayerbe
Pubblicato in: ChemElectroChem, Numero 11, 2024, Pagina/e e2023008, ISSN 2196-0216
Editore: Chemistry Europe
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An active learning approach to model solid-electrolyte interphase formation in Li-ion batteries

Autori: M. Soleymanibrojeni, C. R. Caldeira Rego, M. Esmaeilpour, W. Wenzel
Pubblicato in: J. Mater. Chem. A, 2023, ISSN 2050-7488
Editore: Royal Society of Chemistry
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PRISMA: A robust and intuitive tool for high-throughput processing of chemical spectra

Autori: Eibar Flores; Nataliia Mozhzhukhina; Xinyu Li; Poul Norby; Aleksandar Matic; Tejs Vegge
Pubblicato in: Chemistry - Methods, 2022, Pagina/e e202100094, ISSN 2628-9725
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Workflow Engineering in Materials Design within the BATTERY 2030 + Project

Autori: 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
Pubblicato in: Advanced Energy Materials, 2021, Pagina/e 2102638, ISSN 1614-6840
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One-Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity

Autori: Fuzhan Rahmanian, Monika Vogler, Christian Wölke, Peng Yan, Martin Winter, Isidora Cekic-Laskovic, Helge S. Stein
Pubblicato in: Batteries and Supercaps, Numero 5, 2022, Pagina/e e20220022, ISSN 2566-6223
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Accelerating Battery Characterization Using Neutron and Synchrotron Techniques: Toward a Multi-Modal and Multi-Scale Standardized Experimental Workflow

Autori: 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

Autori: 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

Autori: 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

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

Autori: Medina, Johanne; Ziaullah, Abdul Wahab; Heesoo Park; Castelli, Ivano E.; Shaon, Arif; Bensmail, Halima; Fedwa El-Mellouhi
Pubblicato in: Matter, Numero 5 (11), 2022, Pagina/e 3614-3642, ISSN 2054-2550
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Greener, Safer and Better Performing Aqueous Binder for Positive Electrode Manufacturing of Sodium Ion Batteries

Autori: 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
Pubblicato in: ChemSusChem, 2024, ISSN 1864-5631
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Digitalization of Battery Manufacturing: Current Status, Challenges, and Opportunities

Autori: 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

Autori: Jin Hyun Chang, Peter Bjørn Jørgensen, Simon Loftager, Arghya Bhowmik, Juan María García Lastra, Tejs Vegge
Pubblicato in: Electrochimica Acta, Numero 388, 2021, Pagina/e 138551, ISSN 0013-4686
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Electrochemistry Visualization Tool to Support the Electrochemical Analysis of Batteries

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

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

Autori: Elena Gelžinytė, Simon Wengert, Tamás K. Stenczel, Hendrik H. Heenen, Karsten Reuter, Gábor Csányi, Noam Bernstein
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Toward Operando Characterization of Interphases in Batteries

Autori: 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.

Autori: 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

Autori: 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

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

Autori: Siwoo Lee, Stefan Heinen, Danish Khan, O Anatole von Lilienfeld
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Mechanistic understanding of the correlation between structure and dynamics of liquid carbonate electrolytes: Impact of polarization

Autori: M. Maiti, A. N. Krishnamoorthy, Y. Mabrouk, N. Mozhzhukhina, A. Matic, D. Diddens and A. Heuer
Pubblicato in: 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

Autori: 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
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Machine learning based energy-free structure predictions of molecules (closed and open-shell), transition states, and solids

Autori: 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

Autori: 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
Pubblicato in: Advanced Functional Materials, Numero 32, 2022, Pagina/e 2202372, ISSN 1616-301X
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