Quantifying Perovskite Solar Cell Degradation via Machine Learning from Spatially Resolved Multimodal Luminescence Time Series
This paper presents the novel LumPerNet protocol for perovskite solar cells degradation diagnostics.
Leveraging quantum computing for heat conduction analysis: A case study in thermal engineering
This work presents a case study on heat conduction as a paradigmatic test case to promote the exploration of quantum computing for thermal science.
Energy-GNoME: A Living Database of Selected Materials for Energy Applications
This paper presents the novel Energy-GNoME database and the related protocol.
Exploring machine learning models to predict atmospheric water harvesting with an ion deposition membrane
This paper presents a novel Ion Deposition Membrane-based approach to atmospheric water harvesting, leveraging machine learning to predict water yields under various environmental conditions.
Learning Effective Good Variables from Physical Data
This paper presents two novel approaches to the discovery of possible groups or combinations of primitive variables.
Thévenin’s Battery Model Parameter Estimation Based on Simulink
This paper proposes the estimation of the values of the parameters of the Thévenin equivalent circuit of a LIB commercial cell.