Autonomous Battery Optimization by Deploying Distributed Experiments and Simulations (Adv. Energy Mater. 46/2024)

Autonomous Battery Optimization Autonomous materials acceleration platform involving globally distributed experimental and computational tenants. All tenants are connected to the central fast intention-agnostic learning server that enforces structured communication, records requests, and results. Physical inputs and outputs may be manually transferred between the experimental setups to enable workflows with humans, robots, and artificial intelligence in the loop. More in article number 2403263, Arghya Bhowmik, Helge Sören Stein, and co-workers.

Authors

Institutions

Publication Details

Journal
Advanced Energy Materials
Published
2024-12-01
DOI
https://doi.org/10.1002/aenm.202470204
Citations
1
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Autonomous Battery Optimization by Deploying Distributed Experiments and Simulations (Adv. Energy Mater. 46/2024)

Johan M. Carlsson, Alexey O. Sanin, Giovanni Pizzi, Leon Merker et al.
1 citations
Advanced Energy Materials
Modular Robots and Swarm Intelligence
0.21
article

Autonomous Battery Optimization by Deploying Distributed Experiments and Simulations (Adv. Energy Mater. 46/2024)

Johan M. Carlsson, Alexey O. Sanin, Giovanni Pizzi, Leon Merker, Jonas Busk, Arghya Bhowmik, Laura Rieger, Monika Vogler, Stefan Fuchs, Felix Hanke, Simon Clark, Ivano E. Castelli, Bojing Zhang, Eibar Flores, Helge S. Stein, Hamidreza Hajiyani, Miran Gaberšček, Francisco F. Ramírez, Tejs Vegge, Simon Krarup Steensen, François Liot
article en
1 citations

Abstract

Autonomous Battery Optimization Autonomous materials acceleration platform involving globally distributed experimental and computational tenants. All tenants are connected to the central fast intention-agnostic learning server that enforces structured communication, records requests, and results. Physical inputs and outputs may be manually transferred between the experimental setups to enable workflows with humans, robots, and artificial intelligence in the loop. More in article number 2403263, Arghya Bhowmik, Helge Sören Stein, and co-workers.

Advanced Energy MaterialsVol. 14(46)
SINTEF (NO), Paul Scherrer Institute (CH), Dassault Systèmes (Germany) (DE), Helmholtz-Institute Ulm (DE), Max Planck Computing and Data Facility (DE), Dassault Systèmes (United Kingdom) (GB), National Institute of Chemistry (SI), SINTEF Industry (NO), École Polytechnique Fédérale de Lausanne (CH), Technical University of Munich (DE), Technical University of Denmark (DK)
Affordable and clean energy
Openalex Percentile: Top 49%
Modular Robots and Swarm Intelligence
0.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.