A5090295675- Material Dynamics and Properties
- Advanced Thermodynamics and Statistical Mechanics
- Mathematics Education and Programs
- Protein Structure and Dynamics
- Pickering emulsions and particle stabilization
- Innovative Teaching and Learning Methods
- Innovative Teaching Methods
- Micro and Nano Robotics
- Spectroscopy and Quantum Chemical Studies
- X-ray Spectroscopy and Fluorescence Analysis
- High-pressure geophysics and materials
- Force Microscopy Techniques and Applications
- Advanced X-ray Imaging Techniques
- stochastic dynamics and bifurcation
- Nanopore and Nanochannel Transport Studies
- Quantum Dots Synthesis And Properties
- Machine Learning in Materials Science
- nanoparticles nucleation surface interactions
- Mechanical and Optical Resonators
- Electrostatics and Colloid Interactions
- Neural dynamics and brain function
- Surfactants and Colloidal Systems
- Biocrusts and Microbial Ecology
- Field-Flow Fractionation Techniques
- Fault Detection and Control Systems
University of California, Berkeley
2019-2025
Institute for Atomic and Molecular Physics
2023-2025
Center for Theoretical Biological Physics
2023
Kavli Energy NanoScience Institute
2019
Lawrence Berkeley National Laboratory
2019
Colloidal nanocrystals of metals, semiconductors, and other functional materials can self-assemble into long-range ordered crystalline quasicrystalline phases, but insulating organic surface ligands prevent the development collective electronic states in nanocrystal assemblies. We reversibly self-assembled colloidal gold, platinum, nickel, lead sulfide, selenide with conductive inorganic supercrystals exhibiting optical properties consistent strong coupling between constituent nanocrystals....
Self-assembly of colloidal nanocrystals (NCs) into superlattices (SLs) is an appealing strategy to design hierarchically organized materials with promising functionalities. Mechanistic studies are still needed uncover the principles for SL self-assembly, but such have been difficult perform due fast time and short length scales NC systems. To address this challenge, we developed apparatus directly measure evolving phases in situ real electrostatically stabilized Au solution before, during,...
Active matter represents a broad class of systems that evolve far from equilibrium due to the local injection energy. Like their passive analogues, transformations between distinct metastable states in active proceed through rare fluctuations, however detailed balance violating dynamics renders these events difficult study. Here, we present simulation method for evaluating rate and mechanism generic nonequilibrium apply it study conformational changes solute an fluid. The employs variational...
We introduce a variational algorithm to estimate the likelihood of rare event within nonequilibrium molecular dynamics simulation through evaluation an optimal control force. Optimization force chosen basis is made possible by explicit forms for gradients cost function in terms susceptibility driven trajectories changes parameters. consider probabilities time-integrated dynamical observables as characterized their large deviation functions, and find that many cases quantitatively accurate....
We present a method to probe rare molecular dynamics trajectories directly using reinforcement learning. consider that are conditioned transition between regions of configuration space in finite time, such as those relevant the study reactive events, and exhibiting fluctuations time-integrated quantities long time limit, calculation large deviation functions. In both cases, learning techniques used optimize an added force minimizes Kullback–Leibler divergence trajectory ensemble driven one....
We use a nonequilibrium variational principle to optimize the steady-state, shear-induced interconversion of self-assembled nanoclusters DNA-coated colloids. Employing this within stochastic optimization algorithm allows us identify design strategies for functional materials. find that far-from-equilibrium shear flow can significantly enhance flux between specific colloidal states by decoupling trade-offs stability and reactivity required systems in equilibrium. For isolated nanoclusters, we...
This article reviews the concepts and methods of variational path sampling. These allow computational studies rare events in systems driven arbitrarily far from equilibrium. Based upon a statistical mechanics trajectory space leveraging theory large deviations, they provide perspective with which dynamical phenomena can be studied same types ensemble reweighting ideas that have been used for static equilibrium properties. Applications to chemical, material, biophysical are highlighted.
Using large deviation theory and principles of stochastic optimal control, we show that rare molecular dynamics trajectories conditioned on assembling a specific target structure encode set interactions external forces lead to enhanced stability structure. Such relationship can be formulated into variational principle, for which have developed an associated optimization algorithm used it determine targeted self-assembly within nonequilibrium steady-states. We illustrate this perspective...
Bottom-up assembly of nanocrystals (NCs) into ordered arrays, or superlattices (SLs), is a promising route to design materials with new functionalities, but the degree control over functional structures remains challenging. Using electrostatics, rather than density, tune interactions between semiconductor NCs, we watch self-assembly proceeding through metastable liquid phase. We systematically investigate phase behavior as function quench conditions in situ and real time using small angle...
Solution-phase bottom up self-assembly of nanocrystals into superstructures such as ordered superlattices is an attractive strategy to generate functional materials increasing complexity, including very recent advances that incorporate strong interparticle electronic coupling. While the kinetics in these systems have been elucidated and related product characteristics, weak bonding interactions suggest formed could continue order within solution long after primary nucleation growth occurred,...
A student-led mathematics bootcamp has been designed and implemented to help foster community building, improve confidence in mathematical skills, provide resources for incoming physical chemistry doctoral students. The is held immediately before the start of first semester graduate school uses an active learning approach review practice undergraduate-level problems over 5 days small student groups. This work includes development presentation a new, publicly available curriculum on select...
A student-led mathematics bootcamp has been designed and implemented to help foster community building, improve confidence in mathematical skills, provide resources for incoming physical chemistry doctoral students. The is held immediately before the start of first semester graduate school uses an active learning approach review practice undergraduate-level problems over five days small student groups. This work includes development presentation a new, publicly available curriculum on select...
Solution-phase bottom up self-assembly of nanocrystals into superstructures such as ordered superlattices is an attractive strategy to generate functional materials increasing complexity, including very recent advances that incorporate strong interparticle electronic coupling. While the kinetics in these systems have been elucidated and related product characteristics, weak bonding interactions suggest formed could continue order within solution long after primary nucleation growth occurred,...
Self-assembly of colloidal nanocrystals (NCs) into superlattices (SLs) is an appealing strategy to design hierarchically organized materials with new functionalities. Mechanistic studies are still needed uncover the principles for SL self-assembly, but such have been difficult perform due fast time- and short length scales NC systems. To address this challenge, we developed apparatus directly measure evolving phases \textit{in situ} in real time electrostatically stabilized Au solution...
We have designed and implemented a student-led mathematics bootcamp to improve mathematical skills confidence among incoming physical chemistry doctoral students. The is held immediately before the start of first semester graduate school uses an active learning approach review practice undergraduate problems over five days in small student groups. developed content, which now publicly available, for on select topics, including calculus, linear algebra, functions, differential equations,...