Statistical Thermodynamics & Molecular Simulations (STMS) Seminar Series
These seminar series are aimed at providing a virtual platform for sharing scientific research in the area of statistical mechanics, molecular simulations, and computational materials science. Since early 2020, the coronavirus pandemic has disrupted many large in-person scientific gatherings, including conferences and department seminars, and it is not clear that the situation will improve any time soon. STMS is aimed at filling this gap, and provide a venue for dissemination of research findings and exchange of ideas in the age of COVID. This model is being currently used by several other scientific communities, and can potentially continue even beyond the pandemic if successful.
Each seminar will be a 60-minute event and will comprise of a long-form (30-minute) talk by a principal investigator or a senior research scientists from academia or industry and a short-form (15-minute) presentation by a graduate student or a postdoc. The remainder of the event will be dedicated to Q&A (10 minutes for the PI, 5 minutes for the student/postdoc). Long-form speakers will be chosen by the STMS Organizing Committee, while we encourage suggestions from the community at large. Student and postdoctoral speakers can either be nominated by their advisors or can self-nominate themselves by sending a CV to the organizers. During 2022 we expect to hold two seminar per month, and the events will take place in the last two Fridays of each month, from 10:45 AM-12:00 PM Eastern Standard Time (EST):
This event's talks:
Revisiting Free-Energy methods to study transitions along complex order parameters: Application to Network Phases
Prof. Fernando Escobedo (Cornell University)
Abstract: In this presentation, I will first provide a brief tutorial about the computation of free-energy differences via perturbation (FEP) methods and thermodynamic integration (TI) and their suitability for different types of coupling parameters, categorized as being either Hamiltonian parameters (HPs) or Order parameters (OPs). This background allows to illustrate how new simple formulas to evaluate free-energy differences can be derived that combine the advantages of the strategies embodied by common FEP (i.e., overlap sampling) and TI (i.e., use of first-derivative data). I will next discuss the challenges associated with the calculation of disorder-to-order transition free-energy barriers of complex network phases such as the gyroid, diamond and other co- or bicontinuous phases encountered in block copolymers, patchy particles, and polyphillic building blocks like bolaamphiphiles. Such systems exemplify cases where the relevant OP that track the nucleation of order is a complex function of the system’s phase space which is very expensive to frequently compute in umbrella sampling simulations via molecular dynamics. It is shown how the dual-OP method that uses a blunter global OP for the umbrella bias while keeping record of configurations for analysis with a local OP, is more robust and computationally efficient than other popular methods, as it does not require the expensive local OP to be computed on-the-fly, and it can negotiate large barriers aided by the biased sampling.
I would also briefly highlight a mentorship initiative called “Scholarship-for-Fellowship” that we have deployed via the Diversity and Inclusion Program in our Department. This is a yearly forum to recognize the publication of peer-reviewed journal papers by students where they have the opportunity to share lessons that helped them grow as individuals and as researchers, focusing on the struggles and anecdotes that may illuminate what “made the difference” along the way.
Speaker Bio: Fernando Escobedo received a B.S. degree in Chemical Engineering from the University of San Agustin in Peru (1987) and upon working for 5 years as an R&D engineer in a Peruvian company he came to the U.S., getting his Ph.D. from the University of Wisconsin-Madison (1997) under the supervision of Prof. Juan de Pablo. Since joining the faculty of Cornell University in 1999 he has received the Camille & Henry Dreyfus Foundation new faculty award, the Career Award from NSF, the Alfred P. Sloan Foundation fellowship, and the AIChE CoMSEF Impact Award. He currently holds the Samuel and Diane Bodman Professorship in Engineering.
Revisiting Hagen-Poiseuille Law for Flow in Nanopores
Dr. Mohammad “Mosi” Heiranian (Yale University)
Abstract: High-performance transport in nanopores has drawn a great deal of attention in a variety of applications, such as water purification, resource recovery, power generation, and biosensing. Confined fluids in nanopores possess unique properties that differ substantially from those of bulk fluids. Here, molecular corrections are introduced into the classical Hagen-Poiseuille (HP) equation by considering the variation of key hydrodynamical properties with thickness and diameter of pores in ultrathin graphene and finite-length carbon nanotubes (CNTs) using Green–Kubo relations and molecular dynamics (MD) simulations. Large water flow rate enhancement factors in carbon-based nanopores have been reported over the classical HP equation which does not account for the interfacial physics of transport at molecular scale. The corrected HP (CHP) theory successfully predicts the flow rates from pressure-driven flows in simulations and experiments.
Speaker Bio: Mohammad “Mosi” Heiranian is a current postdoctoral associate under the supervision of Professor Menachem Elimelech in the Department of Chemical and Environmental Engineering at Yale University. He obtained his B.E in Mechanical Engineering from the University of Manitoba in 2012. He then received his M.S. and PhD under the direction of Professor Narayana Aluru in Theoretical and Applied Mechanics from the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign in 2016 and 2020, respectively. His expertise is in using modern theoretical and computational tools to study physical phenomena across different scales, from quantum to continuum. His research is focused on developing multiscale models for addressing different engineering problems and discovery of new advanced materials for a wide variety of engineering applications such as power generation, energy storage, resource recovery, water purification, and single biomolecule detection for diagnosis. For his outstanding research in Mechanical Engineering, he received the Michael Sutton Memorial Award in 2018.