Tim Möller

A hybrid machine learning-genetic algorithm (ML-GA) model to predict optimal process parameters of nanoporous Cu for CO2 reduction

Interface chemistry of conductive crystalline porous thin films

Water electrolysis: from textbook knowledge to the latest scientific strategies and industrial developments

What would it take for renewably powered electrosynthesis to displace petrochemical processes?

Growth mechanisms and anisotropic softness–dependent conductivity of orientation-controllable metal–organic framework nanofilms

Electrocatalytic CO₂ Reduction via a Permeable CNT Hollow-Fiber Electrode Incorporated with SnO₂ Nanoparticles

Evidence of Mars‐Van‐Krevelen Mechanism in the Electrochemical Oxygen Evolution on Ni‐Based Catalysts

In Situ/Operando Electrocatalyst Characterization by X-ray Absorption Spectroscopy

Loss of Life Transformer Prediction Based on Stacking Ensemble Improved by Genetic Algorithm By IJISRT

Multilayer Electrolyzer Stack Converts Carbon Dioxide to Gas Products at High Pressure with High Efficiency

The product selectivity zones in gas diffusion electrodes during the electrocatalytic reduction of CO₂

Efficient CO₂ to CO electrolysis on solid Ni–N–C catalysts at industrial current densities

Alloy Nanocatalysts for the Electrochemical Oxygen Reduction (ORR) and the Direct Electrochemical Carbon Dioxide Reduction Reaction (CO₂RR)

Electrocatalytic CO₂ Reduction on CuO_x Nanocubes: Tracking the Evolution of Chemical State, Geometric Structure, and Catalytic Selectivity using Operando Spectroscopy

Electrocatalytic CO₂ Reduction on CuO_x Nanocubes: Tracking the Evolution of Chemical State, Geometric Structure, and Catalytic Selectivity using Operando Spectroscopy