Publications related to Review on Uric Acid Recognition by MOFs with a Future in Machine Learning

Solution-based Cu+ transient species mediate the reconstruction of copper electrocatalysts for CO2 reduction

Raffaella Buonsanti, Anna Loiudice, Petru Pasquale Albertini, Jan Vávra, Gaétan Philippe Louis Ramona

Understanding metal surface reconstruction is of the utmost importance in electrocatalysis, as this phenomenon directly affects the nature of available active sites. However, its dynamic nature renders surface reconstruction notoriously difficult to study. ...

Nature Portfolio2024

Rate-Determining Step for Electrochemical Reduction of Carbon Dioxide into Carbon Monoxide at Silver Electrodes

Sophia Haussener, Etienne Boutin

Silver is one of the most studied electrode materials for the electrochemical reduction of carbon dioxide into carbon monoxide, a product with many industrial applications. There is a growing number of reports in which silver is implemented in gas diffusio ...

2024

NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection

Lijing Xin, Yubo Zhao, Yan Lin, Wei Ye

Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. Here, we conduct NMR- and MS-based metabo ...

Nature Portfolio2024

Microstructure - Electrochemical Surface Reactivity Relationship of Electrochemically Grown Manganese Oxides Films

Roberto Cestaro

This Thesis provides a comprehensive and correlative investigation of the microstructure, chemical state, and electrochemical reactivity of manganese oxide (MnOx) films, aiming to gain a deeper understanding of the deposition and dissolution mechanism of M ...

EPFL2024

Tailoring nanocatalysts and reaction interfaces for water- and CO2-electrolysis

Thi Ha My Pham

Renewable energy sources offer a promising solution for mitigating sustainability and CO2 emissions-related issues due to their vast energy generation capacity. They enable hydrogen production via water electrolysis, as well as carbon capture and utilizati ...

EPFL2024

Dynamic Behavior of Spatially Confined Sn Clusters and Its Application in Highly Efficient Sodium Storage with High Initial Coulombic Efficiency

Kumar Varoon Agrawal, Lei Zhang, Kangning Zhao, Xu Xu

Advanced battery electrodes require a cautious design of microscale particles with built-in nanoscale features to exploit the advantages of both micro- and nano-particles relative to their performance attributes. Herein, the dynamic behavior of nanosized S ...

Wiley-V C H Verlag Gmbh2024

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning

Berend Smit, Xiaoqi Zhang, Sauradeep Majumdar, Hyunsoo Park

The combination of several interesting characteristics makes metal-organic frameworks (MOFs) a highly sought-after class of nanomaterials for a broad range of applications like gas storage and separation, catalysis, drug delivery, and so on. However, the e ...

Royal Soc Chemistry2024

Contrasting Views of the Electric Double Layer in Electrochemical CO2 Reduction: Continuum Models vs Molecular Dynamics

Sophia Haussener, Evan Fair Johnson

In the field of electrochemical CO2 reduction, both continuum models and molecular dynamics (MD) models have been used to understand the electric double layer (EDL). MD often focuses on the region within a few nm of the electrode, while continuum models ca ...

Amer Chemical Soc2024

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Mohammad Khaja Nazeeruddin

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Elsevier Science Sa2024

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024