Publication

Characterizing and Understanding Divalent Adsorbates on Carbon Nanotubes with Ab Initio and Classical Approaches: Size, Chirality, and Coverage Effects

Publications associées (30)

Mechanistic study on the evolution of vacancies in graphene by oxidation by scanning tunneling microscopy

Nanostructured graphitic materials, including graphene hosting Å to nanometer-sized pores, have attracted attention for various applications such as separations, sensors, and energy storage. Graphene with Å-scale pores is a promising next-generation materi ...

EPFL2023

In Situ Monitoring of the Surface Evolution of a Silver Electrode from Polycrystalline to Well-Defined Structures

Yunchang Liang

Capturing the surface-structural dynamics of metal electrocatalysts under certain electrochemical environments is intriguingly desired for understanding the behavior of various metal-based electrocatalysts. However, in situ monitoring of the evolution of a ...

AMER CHEMICAL SOC2022

Flowing Gas Experiments Reveal Mechanistic Details of Interfacial Reactions on a Molecular Level at Knudsen Flow Conditions

Michel Rossi, Christian Ludwig, Riccardo Iannarelli

Knudsen flow experiments and its interpretation in terms of adsorption/desorption kinetics as well as quantitative uptake on substrates of interest is presented together with the description of critical design parameters of the Knudsen Flow Reactor (KFR). ...

2022

Characterization of Chemisorbed Species and Active Adsorption Sites in Mg-Al Mixed Metal Oxides for High-Temperature CO2 Capture

Berend Smit, Christopher Patrick Ireland, Kevin Maik Jablonka, Susana Garcia Lopez

Mg-Al mixed metal oxides (MMOs), derived from the decomposition of layered double hydroxides (LDHs), have been purposed as adsorbents for CO2 capture of industrial plant emissions. To aid in the design and optimization of these materials for CO2 capture at ...

AMER CHEMICAL SOC2022

Oxygen Evolution at the BiVO4-Water Interface: Mechanism of the Water Dehydrogenation Reaction

Alfredo Pasquarello, Julia Anna Wiktor, Sai Lyu

We study the water dehydrogenation reaction at the BiVO4(010)-water interface by combining nudged-elastic-band calculations and electronic structure calculations at the hybrid functional level. We investigate the pathway and the kinetic barrier for the adi ...

AMER CHEMICAL SOC2022

Demonstrating and Unraveling a Controlled Nanometer-Scale Expansion of the Vacancy Defects in Graphene by CO2

Kumar Varoon Agrawal, Luis Francisco Villalobos Vazquez de la Parra, Kuang-Jung Hsu

A controlled manipulation of graphene edges and vacancies is desired for molecular separation, sensing and electronics applications. Unfortunately, available etching methods always lead to vacancy nucleation making it challenging to control etching. Herein ...

Wiley-VCH Verlag GmbH2022

Assessing the persistence of chalcogen bonds in solution with neural network potentials

Anne-Clémence Corminboeuf, Veronika Juraskova, Rubén Laplaza Solanas, Frédéric Célerse

Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry, and functional materials to name a few. Yet, their computational description generally neglects finite temperature and environme ...

2022

Adsorption Behavior of the Coenzyme NADH at the Carbon/ Electrolyte Interface Determined by Neutron Reflectometry

The adsorption behavior of beta-nicotinamide adenine dinucleotide (NADH) at the carbon/electrolyte interface has been studied using a combination of neutron reflectometry (NR) and solution depletion isotherms. Coupling the NR technique with an electrochemi ...

2022

Review-Origin and Promotional Effects of Plasmonics in Photocatalysis

Olivier Martin, Madasamy Thangamuthu

Plasmonic effects including near-field coupling, light scattering, guided mode through surface plasmon polaritons (SPPs), Forster resonant energy transfer (FRET), and thermoplasmonics are extensively used for harnessing inexhaustible solar energy for photo ...

ELECTROCHEMICAL SOC INC2022

Beyond potentials: Integrated machine learning models for materials

Michele Ceriotti

Over the past decade, interatomic potentials based on machine learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure calculations, they inherit ...

SPRINGER HEIDELBERG2022