Publications related to Critical analysis of decision variables for high-throughput experimentation (HTE) with perovskite solar cells

Related publications (19)

Element recovery from end-of-life thin-film solar cells

The demand for resources is increasing with increasing world population and technological and industrial development. Therefore, the European Union has defined a list of "critical raw materials" (CRM), which are economically important and have a high suppl ...

EPFL2025

Comparative analysis of search approaches to discover donor molecules for organic solar cells

Mohammed Azzouzi

stk-search employs multiple search algorithms, including Bayesian optimization, to systematically navigate the chemical space of molecules constructed from modular building blocks. ...

Royal Society of Chemistry (RSC)2025

An accurate bifacial PV module energy performance model using a direct-diffuse power rating model

Antonin Faes

Predicting the energy output of a bifacial photovoltaic (PV) module is usually not as straightforward as for a monofacial module. The problem usually lies in the estimation of the back-side irradiance which strongly depends on the mounting conditions, trac ...

ELSEVIER SCI LTD2025

How data structures affect generalization in Kernel Methods and Deep Learning

Umberto Maria Tomasini

Artificial Intelligence has revolutionized numerous fields, driving advancements in healthcare, finance, and autonomous systems. At the core of this revolution lies Deep Learning---algorithms that learn representations from data through computational layer ...

EPFL2025

Adaptive energy reference for machine-learning models of the electronic density of states

Michele Ceriotti, Federico Grasselli, Kevin Kazuki Huguenin-Dumittan, Sanggyu Chong, Wei Bin How

The electronic density of states (DOS) provides information regarding the distribution of electronic energy levels in a material, and can be used to approximate its optical and electronic properties and therefore guide computational materials design. Given ...

2025

Joint Compression of Multi-model Systems for Edge Devices

Mathieu Salzmann, João Luís Prado Vieira

Deploying deep learning models for computer vision (CV) often requires a careful trade-off between performance, efficiency, and cost. In the context of edge inference of machine learning systems, this trade-off translates into a challenge, as computing and ...

Springer Science and Business Media Deutschland GmbH2025

On the Guarantees of Minimizing Regret in Receding Horizon

Giancarlo Ferrari Trecate, Luca Furieri, Andrea Martin

Toward bridging classical optimal control and online learning, regret minimization has recently been proposed as a control design criterion. This competitive paradigm penalizes the loss relative to the optimal control actions chosen by a clairvoyant policy ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

RAFT: Regularized Adversarial Fine-Tuning to Enhance Deep Reinforcement Learning for Self-Parking

Andrea Cavallaro

Deep reinforcement learning (DRL) is a powerful method for local motion planning in automated driving. However, training of DRL agents is difficult and subject to instability. We propose Regularized Adversarial Fine-Tuning (RAFT), an adversarial DRL traini ...

2025

Ultra-uniform perovskite crystals formed in the presence of tetrabutylammonium bistriflimide afford efficient and stable perovskite solar cells

Alwani Imanah Rafieh, Jaekeun Lim, Mohammad Khaja Nazeeruddin, Paul Joseph Dyson, Zhaofu Fei, Hiroyuki Kanda, Yong Ding, Jianxing Xia, Hobeom Kim

Compositional engineering of organic-inorganic metal halide perovskite allows for improved optoelectrical properties, however, phase segregation occurs during crystal nucleation and limits perovskite solar cell device performance. Herein, we show that by a ...

2024

Co-optimising Design and Operation of Energy Systems using Reinforcement Learning

Marine Dominique Cauz

The energy transition is ongoing, in Switzerland and abroad, leading to an ever-increasing development of renewable energy sources. These sources are decentralised, heterogeneous, come with a high dependance on weather conditions, and are therefore hard t ...

EPFL2024

Modeling, design and economics of PEC devices

Alexandre Dominique M. Cattry

Photo-electrochemical (PEC) devices allow for converting solar energy into chemical energy and for the production of energetically dense solar fuels. Light absorption, charge separation and transport, electrochemical reactions, and ionic transport are requ ...

EPFL2024

Low-Resource Speech Recognition and Understanding for Challenging Applications

Juan Pablo Zuluaga Gomez

Automatic speech recognition (ASR) and spoken language understanding (SLU) is the core component of current voice-powered AI assistants such as Siri and Alexa. It involves speech transcription with ASR and its comprehension with natural language understand ...

EPFL2024

FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning

Zhuan Shi, Gang Wang

Federated learning (FL) is a privacy-preserving collaboratively machine learning paradigm. Traditional FL requires all data owners (a.k.a. FL clients) to train the same local model. This design is not well-suited for scenarios involving data and/or system ...

IJCAI2024

Solar-driven hydrogen production using organic semiconductor nanoparticles

Connor Robert Firth

Photocatalytic solar water splitting is a promising technology for producing green hydrogen that has the potential to compete economically with other commercially utilized carbon-based fuels. While this field has existed for decades, there has yet to be a ...

EPFL2024

Radical polymeric p-doping and grain modulation for stable, efficient perovskite solar modules

Michael Graetzel, Shaik Mohammed Zakeeruddin, Felix Thomas Eickemeyer, Yuhang Liu, Brian Irving Carlsen

High-quality perovskite light harvesters and robust organic hole extraction layers are essential for achieving high-performing perovskite solar cells (PSCs). We introduce a phosphonic acid???functionalized fullerene derivative in mixed-cation perovskites a ...

American Association for the Advancement of Science2023

Device Performance of Emerging Photovoltaic Materials (Version 4)

Mohammad Khaja Nazeeruddin, Tor Jesper Jacobsson, Fei Guo

Following the 3rd release of the "Emerging PV reports", the best achievements in the performance of emerging photovoltaic (e-PV) devices in diverse e-PV research subjects are summarized, as reported in peer-reviewed articles in academic journals since Augu ...

Wiley-V C H Verlag Gmbh2023

Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice

Martin Josifoski

Meta-Learning aims to speed up the learning process on new tasks by acquiring useful inductive biases from datasets of related learning tasks. While, in practice, the number of related tasks available is often small, most of the existing approaches assume ...

2023

Computational Conceptual Design – Typological Exploration Of Spatial Truss Systems Through Optimization

Corentin Jean Dominique Fivet, Jonas Warmuth

Exploring a wide range of relevant design options from the outset is crucial for every sound conceptual design process. Optimization techniques are generally employed to generate well-performing structural design options. However, focusing only on performa ...

2023

Multi-agent Learning with Privacy Guarantees

Elsa Rizk

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

EPFL2023