Optimal process design for the polygeneration of SNG, power and heat by hydrothermal gasification of waste biomass: Process optimisation for selected substrates

Publications associées (29)

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Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

Jiancheng Yang, Li Zhang, Xinchao Wang, Hua Sun

Background: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor pathological invasiveness. However, preoperative solid component assessment still lacks a reference standard.Methods: In this retrospective study, an AI algorithm w ...

Elsevier Ireland Ltd2023

Decision support for the design of integrated biorefineries

Julia Granacher

A shift from fossil-based energy and products to more sustainable alternatives is essential to reduce greenhouse gas emissions and associated climate change impacts. Biomass represents a promising alternative for providing fuels and carbon-based products w ...

EPFL2023

Text Representation Learning for Low Cost Natural Language Understanding

Jan Frederik Jonas Florian Mai

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

EPFL2023

Nanocrystalline Flash Annealed Nickel Oxide for Large Area Perovskite Solar Cells

Michael Graetzel, Jovana Milic, Felix Thomas Eickemeyer

The industrialization of perovskite solar cells requires adequate materials and processes to make them economically viable and environmentally sustainable. Despite promising results in terms of power conversion efficiency and operational stability, several ...

WILEY2023

Comparative Exergy and Economic Assessment of Fossil and Biomass-Based Routes for Ammonia Production

François Maréchal, Daniel Alexander Florez Orrego

Due to the increasing concerns about the marked dependence on fossil resources and their intrinsic economic uncertainty, as well as motivated by more stringent environmental regulations, the pursuit of alternative energy resources for the synthetic fertili ...

Silesian University of Technology2023

Modeling and mitigating supply chain disruptions as a bilevel network flow problem

Ralf Seifert, Anna Timonina-Farkas, René Yves Glogg

Years of globalization, outsourcing and cost cutting have increased supply chain vulnerability calling for more effective risk mitigation strategies. In our research, we analyze supply chain disruptions in a production setting. Using a bilevel optimization ...

2022

Optimal Matching of Random Parts

Thomas Alois Weber

This paper examines the minimization of the cost for an expected random production output, given an assembly of finished goods from two random inputs, matched in two categories. We describe the optimal input portfolio, first using the standard normal appro ...

2022

Hole transport material, synthesis thereof, and solar cell

Michael Graetzel, Shaik Mohammed Zakeeruddin, Yuhang Liu, Michael Bauer

The organic small molecule 4,4',4",4"'-(5,5-dimethoxycyclopenta-1,3-diene-1,2,3,4-tetrayl)tetrakis(N,N-bis(4-methoxyhenyl)aniline (CPDA 1), shows electrochemical properties very close to spiro-OMeTAD indicating a high compatibility with PSC systems for its ...

2022

Memory of Motion for Initializing Optimization in Robotics

Teguh Santoso Lembono

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022

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Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

Jiancheng Yang, Li Zhang, Xinchao Wang, Hua Sun

Elsevier Ireland Ltd2023