2023
Michele Pavanello (Rutgers University), “DFT and DFT embedding: Ways to approach the mesoscopic world with ab-initio methods (without cutting corners)” and “Almost all-Python suite of software for ab-initio simulations and machine learning”
Jane Herriman (and Don Frederick) (LLNL), “Livermore Computing (LC) environment and leveraging LC resources - Part I. How to run and schedule jobs using SLURM on the LC Quartz cluster and Getting help with LC systems” and “Livermore Computing (LC) environment and leveraging LC resources - Part II. Getting started with Python on Quartz”
Erik Draeger (LLNL), “Supercomputing at the exascale and beyond: future trends and challenges”
Talat Rahman (University of Central Florida), “Catalytic conversion of CO2 and CO to value added products - guidelines from ab initio modeling & simulation” Parts I and II.
Jon Belof (LLNL), “Physical and Machine Learning Approaches toward the Control of Dynamic Material Response Far From Equilibrium”
Aurora Pribram-Jones (UC Merced), “Heating up Density Functional Theory” and “A Hot Mess? How Temperature, Interaction Strength, and Density Influence Electronic Structure”
Alexander Urban (Columbia), “Computational Materials and Process Development for a Clean-Energy Future”
Felipe Jornada (Stanford), “Introduction to Many-Body Perturbation Theory: Accurately Predicting Excited-State Properties of Materials from First Principles” and “Recent Developments and Applications of Many-Body Perturbation Theory Techniques to Study Excited-State Properties of Materials in Real Time”
William Schneider (Notre Dame), “Bridging First Principles Models to Zeolite Catalysis” and “The Catalytic Science of Making Up and Breaking Up Nitrogen”
Ravishankar Sundararaman (Rensselaer Polytechnic Institute), “Density-functional approximations: from electrons to classical fluids and Advancing solvation models from implicit to classical DFT methods”
2022
David Richards (LLNL), “High Performance Computing at LLNL. Past, Present, and Future”
Helgi Ingolfsson (LLNL), “MuMMI, a machine learning-driven modeling infrastructure for coupling different scales; showcased on a RAS-RAF biology application”
Jane Herriman and Don Frederick (LLNL), “Livermore Computing (LC) environment and leveraging LC resources”
Arthi Jayaraman (University of Delaware), “Theory, simulations, and machine learning for design and structural characterization of macromolecular materials”
Joshua Anderson (University of Michigan), “Predicting the complex structures that arise from simple building blocks”
Michael J. Janik (The Pennsylvania State University), “Combining experimental, density functional theory, and microkinetic modeling for catalytic mechanism determination” and “Development of electrocatalytic materials guided by computational chemistry: fuel cells and electrolysis”
Michele Pavanello (Rutgers University), “DFT and DFT embedding: Ways to approach the mesoscopic world with ab-initio methods (without cutting corners)” and “The (almost) all-Python DFTpy and QM-Learn suites of software”
Shyue Ping Ong (University of California, San Diego), “Mathematical Graphs as a Representation for Materials”
Miguel A. Morales Silva (Flatiron Institute), “Quantum Monte Carlo methods for Ab-Initio Electronic Structure”
Reid Van Lehn, (University of Wisconsin-Madison), “Classical Molecular Dynamics Simulations of Solvated Chemically Heterogeneous Interfaces” and “Combining Molecular Dynamics Simulations and Machine Learning to Screen Interfacial Properties”
2021
David Richards (LLNL), “High Performance Computing at LLNL. Past, Present, and Future”
Edwin Garcia (Purdue University), “Open Source Software for the Modeling and Simulation of Materials and Devices” and “Scaling, Coarse Graining, and Bottlenecks on the Microstructural Modeling of Lithium-Ion Batteries”
Eberhard K.U. Gross (The Hebrew University of Jerusalem), “First-principles simulation of matter far from equilibrium II: Non-adiabatic dynamics from the exact factorization” and “First-principles simulation of matter far from equilibrium I: Laser-driven charge and spin dynamics from real-time TDDFT”
Aurora Clark (Washington State University, Pacific Northwest National Laboratory), “Using Graphs and Topology to Identify Multidimensional Correlations in Complex Chemical Systems” and “The Mathematics of Graphs and Topology in Chemistry and Materials Science”
Roger Rousseau (Pacific Northwest National Laboratory), “Effect of Collective Dynamics and Anharmonicity on Entropy in Heterogenous Catalysis: Building the Case for Advanced Molecular Simulations” and “Understanding the role of solvent effects in the thermal and electrochemical hydrogenation of organics”
Michael Shirts (University of Colorado Boulder), “Materials that wiggle: thermodynamics of organic crystals and kinetics in nanostructured separation membranes” and “Computational Chemistry and Materials Science (CCMS) Summer Institute Lecture”
Paulette Clancy (Johns Hopkins University), “An introductory primer on Bayesian optimization for application to the chemical and materials sciences” and “A Bayesian Optimization Case study: Finding polymorphs in chemical systems and identifying stable versus metastable variants”
Nongnuch Artrith (Debye Institute for Nanomaterials Science), “Modelling of Complex Energy Materials with Machine Learning”
Kai Nordlund (University of Helsinki), “Applications of molecular dynamics to model the crystal direction dependence of sputtering, antiproton motion in solid films, and possible dark matter recoils in materials”
2020
Dave Richards (LLNL), “High Performance Computing at LLNL. Past, Present, and Future.”
A brief overview of the history and mission of High Performance Computing at LLNL. A discussion of how LLNL is adapting to the current shift to heterogeneous computing architectures and what that architectural change means to computational scientists.
Mikhail Dzugutov (KTH Royal Institute of Technology), “Particle simulations in statistical mechanics and condensed matter”
Laura Gagliardi (University of Minnesota), “Modeling catalysis and excited states with electronic structure theories”
Dion Vlachos (University of Delaware), Matteo Maestri (Politecnico di Milano), Michail Stamatakis (University College London), “Theory, Applications, and Tools for Multiscale Kinetic Modeling Workshop,” An online workshop on kinetic models and their integration with computational fluid dynamics (CFD).
Ellad Tadmor (University of Minnesota), “Predicting Behavior from the Ground Up: Molecular and Multiscale Simulations of Materials”
Danny Perez (Los Alamos National Laboratory), “Long-time simulations of materials with Accelerated Molecular Dynamics”
Yunzhi Wang (Ohio State University), “Phase Field Method for Simulating Complex Microstructural Evolution at Mesoscale”
2019
Dave Richards (LLNL), “High Performance Computing at LLNL. Past, Present, and Future.”
Wei Cai (Stanford), “Methods of atomistic simulations”
Alexander Stukowski (Technische Universität Darmstadt), “In-silico microscopy: Novel methods for analyzing large-scale atomistic materials simulation data”
Julia Ling (Citrine Informatics), “AI Algorithms in Materials Science” and “Sequential Learning Exercise in Python using Citrination”
Phil Stern (LLNL), “Electronic structure calculations”
Sebastien Hamel (LLNL), “Applications of electronic structure calculations”
Krishna Rajan (University at Buffalo), “Data Dimensionality in Materials Science” and “Chemical Design of Materials: Case studies”
Noa Marom (Carnegie Mellon University), “Structure prediction of molecular crystals from first principles” and “Computational discovery of singlet fission and up-conversion materials”
Becky Lindsey (LLNL), “Machine learning for interatomic potentials development I” and “Machine learning for interatomic potentials development II”
2018
Fred Streitz (LLNL), “Extreme Capability Computing at LLNL”
Christine Isborn (UC Merced), “Modeling Excited States of Molecules in Complex Environments with time- dependent density functional theory” and “Combining the Ensemble and Franck-Condon Approaches for Spectral Shapes of Molecules in Solution”
Anubhav Jain (LBNL), “High-throughput computation and machine learning applied to materials design” and “Methods, tools, and examples: High-throughput computation and machine learning applied to materials design”
Feliciano Giustino (University of Oxford), “Ab initio calculations of electron-phonon interactions: theory and applications”
Jaime Marian (UCLA), “The multiscale character of materials behavior: How to build viable models across multiple length and time scale” and “Selected examples of materials simulations across the scales: Alloy evolution under highly non-equilibrium conditions and its effect on mechanical properties”
Mark Tuckerman (NYU), “Molecular dynamics: ‘Ersatz’ chemistry in a virtual laboratory” and “Molecular dynamics based exploration and learning of free energy landscapes of molecular crystals and oligopeptides”
Brenda Rubenstein (Brown University), “Auxiliary Field Quantum Monte Carlo for Hot and Cold Electrons”
Nandini Ananth (Cornell University), “Quantum Dynamics from Classical Trajectories: Path Integral and Semiclassical Methods” and “Direct Dynamic Simulations of Charge and Energy Transfer”
Miles Stoudenmire (Flatiron Institute), “Introduction to Tensor Network Methods for Strongly Correlated Many-Body Systems” and “Applications of Tensor Networks: Quantum Chemistry and Machine Learning”
2017
Fred Streitz (LLNL), “Extreme Capability Computing at LLNL”
Kevin Leung (Sandia), Modeling Electrochemical Interfaces in Batteries” and “Battery Interfaces: Time, Electrostatics, and Voltages
Davide Donadio (UC Davis), “Molecular dynamics: from atoms trajectories to materials properties” and “Thermal transport at the nanoscale and heat dissipation in liquids during pumpprobe molecular spectroscopy”
Volker Blum (Duke University), “Computational Materials Science from Scratch: Density-Functional Theory, Many-Body Methods, & the Nuts and Bolts that Make Them Work” and “Functional Materials for Electronics and Light Harvesting - Understanding & Predictions from 1st Principles”
Andrew Peterson (Brown University), “Challenges and new methods in ab initio electrochemical reactions” and “Developing machine-learning approaches to accelerate ab initio calculations”
JR Schmidt (Wisconsin University), “Principles and practice of ab initio force field development: Applications to metal-organic frameworks and beyond” and “Computational heterogeneous catalysis and micro-kinetic modelling: Methods and applications”
Maria Chan (ANL), “Combining first principles modeling, experimental characterization, and machine learning to understand energy materials” and “Examples in energy storage, photovoltaics, and catalysis”
De-en Jiang (UC Riverside), “Multiscale methods in computational materials chemistry” and “Understanding capacitive energy storage from modeling”
Ming Tang (Rice University), “Phase-field modeling of materials microstructure evolution I & II”
2016
Eliot Kapit, Tulane, Quantum Computing with Superconducting Devices-- Part I: Qubit Design and Operation" and "Part II: Errors, Error Correction, and Applications
Fred Streitz, LLNL, Extreme Capability Computing at LLNL
Chris Van de Walle, UCSB, Impact of point defects on efficiency of devices" and "Designing point defects for quantum information science
Christopher Mundy, PNNL, The role of an accurate description of local structure to inform our understanding of nucleation and assembly
Francesco Paesani, UCSD, Feel the interactions: Achieving chemical accuracy through many-body representations
Francesco Paesani, UCSD, Vibrational spectroscopy from many-body molecular dynamics simulations
Andrew Taube, D.E. Shaw Research, Anton: a computational microscope for millisecond-scale biomolecular simulation
Andrew Taube, D.E. Shaw Research, Developing transferable force fields for specialized hardware
Martin Bazant, MIT, Nonequilibrium Chemical Thermodynamics" and "Phase Separation Dynamics in Li-ion Batteries
Malcolm Stocks, ORNL, Introduction to Multiple Scattering Theory based Korringa-Kohn- Rostoker (KKR) coherent-potential-approximation (CPA) methods for disordered systems with recent applications to High Entropy Alloys
Mal Kalos, LLNL, Quantum Monte Carlo and the Sign Problem
Eric Neuscamman, UC Berkeley, Variational Monte Carlo in Electronic Structure Theory
2015
Fred Streitz, LLNL, Extreme Capability Computing at LLNL
Sadasivan Shankar, Harvard, Multi-level Modeling in Materials and Materials Design
Ross Walker, UCSD, The Rise of the GPU: From Quake to Simulation Workhorse and Lights, Computer, Action: GPU Accelerated Molecular Dynamics, from Enzyme Activation to Membrane Dynamics
Roberto Car, Princeton, First principles molecular dynamics
David Trebotich, LBNL, High Resolution Simulation of Multiscale, Multiphysics Flows in Complex Geometries
Ying Chen, Resselaer Polytechnic Institute, Mesoscale Polycrystalline Science: From Microstructures to Properties and Monte Carlo Modeling at the Mesoscale
Yosuke Kanai, UNC Chapel Hill, First-Principles Modeling of Electron Dynamics, 1: Real-time TD-DFT and its application to Electronic Excitation Dynamica and 2: Surface Hopping and its application to Hot Electron Relaxation
Marcel Baer, PNNL, Ab initio DFT: Thermodynamic, rates and properties and Bulk and interfacial solvation of monatomic and polyatomic anions/acids using DFT
Jonathan Guyer, NIST, Computational Kinetics and Phase Field Modeling
Jianzhong Wu, UC Riverside, Structural Thermodynamics and Towards molecular and materials design from first principles
2014
Fred Streitz, LLNL, Extreme Capability Computing at LLNL
André Schleife, UIUC, Computational Methods for Atomistic Length and Time Scales and Quantum Interactions: Excited Electrons and Their Real-Time Dynamics
Daryl Chrzan, Berkeley, Application of Periodic Supercells to the Computation of Dislocations Core Structures and Dislocations in Two- and Three-Dimensional Materials
Todd Martinez, Stanford, Modeling Excited States and Nonadiabatic Dynamics and Machine Learning and Stream Processors for Ab Initio Molecular Dynamics
Vidvuds Ozolins, UCLA, First-Principles Methods for Modeling High Temperature Behavior of Materials
Shiwei Zhang, William & Mary, Accurate Ab Initio Computations in Materials
Tony Rollett, Carnegie Mellon, Image- and FFT-based Approach for Deformation Simulation and Potts Model for Microstructural Evolution
Max Berkowitz, UNC-Chapel Hill, Atomistic Modeling of Biological Membranes and Their Interactions with Proteins and Peptides
Francesco Pederiva, Trento, Italy, Using quantum mechanics to describe a classical diffusion process and Sampling rare events in classical systems by path-integrals
2013
Dr. Ulrike Meier Yang, LLNL, High Performance Computing
Dr. Fred Streitz, LLNL, Opening frontiers: Extreme capability computing at LLNL
Dr. Heather Kulik, Stanford/MIT, The practitioner's guide to density functional theory and Life, the universe, everything: Efficient and accurate quantum chemistry for biological systems
Dr. Evan Reed, Stanford, Electromechanical properties of nanoscale materials and Atomistic calculations of dynamic compression of materials
Dr. Katsuyo Thornton, University of Michigan, Computational kinetics: Fundamentals, phase field modeling, smoothed boundary method, and applications to energy materials
Dr. Vasily Bulatov, LLNL, Dislocation dynamics and multiscale materials strength
Dr. Stephen Garofalini, Rutgers, Simulations of Molecular Behavior at Interfaces: Applications in Conversion Materials for Advanced Batteries, Intergranular Films, Nanoconfined Water, and Proton Transport
Dr. Arthur Voter, LANL, Accelerating molecular dynamics methods
Dr. Boris Kozinsky, Bosch, Ab-initio materials design for commercial applications: High-energy batteries and Automated screening strategies and infrastructure for materials design
2012
Dr. Ulrike Meier Yang, LLNL, High Performance Computing
Dr. David Prendergast, Lawrence Berkeley National Lab, Simulating Core-Level Spectroscopy from First Principles I and Simulating Core-Level Spectroscopy from First Principles II
Prof. Eva Zurek, State University of New York at Buffalo, Locating the Global and Local Minima of Clusters and Solids and From Metallic Hydrogen to the Anti-AIDS Drug Ritonavir: The Need for Crystal Structure Prediction
Dr. Todd Weisgraber, LLNL, An Overview of the Lattice-Boltzmann Method for Fluid Dynamics
Dr. John Bell, Lawrence Berkeley National Lab, Finite-Volume Methods for Fluctuating Hydrodynamics
Prof. Kieron Burke, UC Irvine, The ABCs of DFT I and The ABCs of DFT II
Dr. Sadasivan Shankar, Intel Corp., Enabling Computational Materials and Chemistry Prototyping: Multi-Scale Modeling & Non-equilibrium systems I and Enabling Computational Materials and Chemistry Prototyping: Multi-Scale Modeling & Non-equilibrium systems II
Prof. Jorge Kohanoff, Queen's University Belfast, Ireland, Simplified methods for electronic structure calculations and A self-consistent tight-binding approach for the study of chemical reactions in heterogeneous environments
Prof. Peter Voorhees, Northwestern University, Computational Materials Science using Phase Field Methods I and Computational Materials Science using Phase Field Methods II
Dr. Celia Reina Romo, LLNL, Modeling and Simulation of Damage by Nucleation and Void Growth: a Multiscale Approach
2011
Professor Troy van Voorhis, MIT, What can simulations teach us about organic photovoltaics? and Improving density functional theory at long- and short-range
Professor Long-Qing Chen, Pennsylvania State University, Strain Contributions to Thermodynamics of Phase Transitions and Microstructure and Applications of Phase-field Method to Modeling Microstructure Evolution
Professor Mark Asta, University of California, Berkeley, Materials Interfaces Studied by Atomic-scale simulations I and Materials Interfaces Studied by Atomic-Scale Simulations II
Dr. Jeffrey Neaton, Lawrence Berkeley National Laboratory, Tailoring Nanoscale Interfaces for Renewable Energy Applications with Computation: DFT and Beyond
Professor Stephen Garofalini, Rutgers University, The Effect of the Water/Silica Interface on the Behavior of Nanoconfined Water and Proton Transport
Dr. Janathan Dubois, Lawrence Livermore National Laboratory, Solving Quantum Many Problems One Random Number at a Time
Dr. Randy Hood, Lawrence Livermore National Laboratory, Quantum Monte Carlo Studies of Electronic Structure
Professor Andrew Rappe, University of Pennsylvania, First-principles calculations as the cornerstone for multi-scale materials simulations and Using first-principles calculations to design new materials for solar energy harvesting
Professor Giulia Galli, University of California, Davis, Understanding and predicting materials for energy: Insight from quantum simulations I and Understanding and predicting materials for energy: Insight from quantum simulations II
Professor Ting Zhu, Georgia Institute of Technology, Revealing the Failure Mechanisms in Nanomaterial Electrodes for Lithium Ion Batteries and Nanomechanics of Ultra-strength Nanomaterials
Dr. Patrick Rinke, Towards a unified description of ground and excited state properties: the GW approach
2010
Prof. Jeffrey C. Grossman, MIT, Introduction to Electronic Structure Calculations in Materials Science: Density Functional Theory and Quantum Monte Carlo Methods and Applications of Electronic Structure Methods to Materials for Energy Conversion and Storage
Dr. Eric Schwegler, Lawrence Livermore National Laboratory, Materials Simulations for NIF
Prof. Alain Karma, Northeastern University, Phase-Field Modeling of Micro/Nano-structure Formation: From Turbine Blades to Nanowires I and Phase-Field Modeling of Micro/Nano-structure Formation: From Turbine Blades to Nanowires II
Prof. Kaushik Bhattacharya, California Institute of Technology, Phase transitions and microstructure in solids: General Principles and Phase transitions and microstructure in solids: Case Study of Liquid Crystal Elastomers
Prof. Wei Cai, Stanford University, Predicting Nucleation Rate by Computer Simulations I and Predicting Nucleation Rate by Computer Simulations II
Prof. Chris Wolverton, Northwestern University, Computational Discovery of Novel Hydrogen Storage Materials and Reactions and First-Principles Calculations and Virtual Aluminum Castings
Prof. Oleg Prezhdo, University of Rochester, Nonadiabatic Molecular Dynamics with Time-Domain Density Functional Theory and Time-domain ab initio studies of quantum dots and molecule-bulk interfaces for solar energy harvesting
Dr. Berni Alder, Lawrence Livermore National Laboratory, Historical Perspectives in Computational Physics