Publications associées à Composition C-4

Impact of quantum-chemical metrics on the machine learning prediction of electron density

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Machine learning (ML) algorithms have undergone an explosive development impacting every aspect of computational chemistry. To obtain reliable predictions, one needs to maintain a proper balance between the black-box nature of ML frameworks and the physics ...

AMER INST PHYSICS2021

Fiber-Tip Polymer Microcantilever for Fast and Highly Sensitive Hydrogen Measurement

Giovanni Dietler, Sandor Kasas, Jiangtao Zhou, Leonardo Venturelli, Yiping Wang, Chaohui Li, Meng Zhu, Cong Xiong

Hydrogen as an antioxidant gas has been widely used in the medical and biological fields for preventing cancer or treating inflammation. However, controlling the hydrogen concentration is crucial for practical use due to its explosive property when its vol ...

AMER CHEMICAL SOC2020

Predictive Models for Thermal Stability and Explosive Properties of Chemicals from Molecular Structure

Nadia Baati

Industrial chemical processes may involve thermal risks as most of the reactions performed are exothermic, the chemicals used are often thermally unstable, and the operating conditions are set to induce high conversion and throughput. Besides the reactive ...

EPFL2016

Quantitative Structure-Property Relationships for Thermal Stability and Explosive Properties of Chemicals

Thierry Meyer, Francis Stoessel, Annik Nanchen, Nadia Baati

Handling and storing chemicals in the industrial world require a conscientious hazards assessment and the implementation of appropriate measures to ensure safety for the workers, the company, the environment and the society. Reliable evaluations and predic ...

2013