
Revolutionizing catalysis through automated multiscale modeling and active exploration of chemical space, accelerating material discovery and optimizing processes from first principles to reactor scale.

Explore high-dimensional data extraction and encoding in complex chemical systems, focusing on exascale computing opportunities, multiscale correlations, and challenges in feature selection and interpretability.

Explore computational workflows for predicting complex materials properties, from phase diagrams to nanostructures, using density functional theory and machine learning potentials.

Exploring grafted nanoparticle melts for innovative gas separation techniques. Lecture delves into advanced materials science, focusing on nanoparticle applications in molecular filtration and separation processes.

Explore polymer material design for gas separations, focusing on advanced techniques and applications in membrane technology for efficient molecular separation processes.

Explore cyclic recursion in machine learning for drug discovery, featuring innovative approaches and industry applications in pharmaceutical research.

Groundbreaking analysis of collagen molecule behavior upon dehydration using collagen mimetic peptides. Reveals sequence-dependent elongation or contraction, crucial for understanding biological materials.

Explore methods for modeling collective dynamics, from microscopic to macroscopic scales. Learn techniques for analyzing complex systems in various scientific fields.

Explore a computational model of chemical bonding, examining bond formation probabilities and their impact on molecular structures.

Explore energies in spring-bonded atoms through computational problems, supplementing Matter and Interactions physics courses with hands-on coding exercises.

Explore quantum chemistry fundamentals and their applications in quantum information science with Prof. Anna Krylov in this comprehensive lecture from IPAM's Winter School.

Explore advanced quantum chemistry concepts and their applications in quantum information science, focusing on cutting-edge research and theoretical frameworks.

Explore innovative techniques for sampling conformational ensembles using latent space dynamics, enhancing our understanding of complex molecular systems and their behavior.

Explore nanoscale polymer structures using atomic-level simulations. Learn about crystal structures, polymer science paradigms, and use an interactive Polymer Modeler to understand polyacrylonitrile processing and crystallization.

Explore atomistic simulations using Amsterdam Modeling Suite. Learn about AMS driver, DFT engines, force fields, and PARAMS for novel molecular interactions. Gain insights through demos and practical applications.

Explore classical and quantum atomic modeling using MIT's toolkit. Perform molecular dynamics, Monte Carlo simulations, and quantum chemistry computations. Learn practical applications for various physics and chemistry courses.

Explore protein dynamics and spectroscopy with PigmentHunter, a user-friendly nanoHUB tool for simulating excitonic spectra of chlorophyll proteins. Learn its interface, workflow, and applications in molecular dynamics and spectral analysis.

Explore quantum computing algorithms for calculating scattering matrix elements in chemical reactions, focusing on the Møller operator formulation and its application to hydrogen exchange.

Explore electronic structure methods in chemistry using nanoHUB simulation tools. Learn to teach computational chemistry concepts and gain hands-on practice with Hartree-Fock and basis sets using ORCA.

Explore computational chemistry using NUITNS toolkit on nanoHUB. Learn to integrate simulations in undergraduate chemistry courses and analyze nanodiamonds through hands-on demonstrations and practical applications.

Explore nanoHUB tools for teaching chemistry, including DDSCAT, QC-Lab, and Nanosphere Optics Lab. Learn about applications in optics, spectroscopy, and molecular modeling from Prof. George Schatz.