YoVDO

Challenges in Heterogeneous Catalyst Development - Advancements in High Throughput Simulation, Experiments, and Machine Learning

Offered By: ICTP Condensed Matter and Statistical Physics via YouTube

Tags

Computational Chemistry Courses Machine Learning Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the challenges and advancements in heterogeneous catalyst development through this webinar from the ICTP Condensed Matter and Statistical Physics Atomistic Simulation Seminar Series. Delve into the integration of Machine Learning-accelerated Quantum Mechanical modeling and high throughput experimental insights shaping industrial catalyst design. Learn about recent research topics such as carbon reutilization and bio-feedstock conversion, and gain a grounded understanding of practical applications in this multidisciplinary field. Presented by Sandip De, Global Scientific Discipline Lead for Inorganic Materials modelling QM at BASF, this 65-minute session offers valuable insights for young scientists interested in the crucial role of efficient catalysts in energy-efficient chemical transformations and environmental sustainability.

Syllabus

CMSP Webinar (Atomistic Simulation Seminar Series): Challenges in Heterogeneous Catalyst Development


Taught by

ICTP Condensed Matter and Statistical Physics

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity
Natural Language Processing
Columbia University via Coursera
Probabilistic Graphical Models 1: Representation
Stanford University via Coursera
Computer Vision: The Fundamentals
University of California, Berkeley via Coursera
Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent