# Greater Boston Area Theoretical Chemistry Lecture Series

## 2019-2020 Speaker Schedule

## New Strategies for Multireference Electronic Structure Problems

### 09/18/19 4:15pm

### MIT Building 4, Room 163

### Francesco Evangelista

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In order to make meaningful predictions about the electronic properties of molecules and materials, theoretical computations must satisfactorily converge electron correlation effects. By correlation, we refer to its normal decomposition into a static component, which is defined by the strong mixing of electronic configurations typically resultant from orbital degeneracies, and a dynamical component, which includes short-range Coulombic and long-range dispersion interactions. Dynamical correlation is the dominant effect in closed-shell molecules, while strong configuration mixing accompanies the more exciting world of bond-breaking processes, open-shell species with orbital degeneracies, electronically excited states, and complexes of transition metals with coupled localized spins. The success of many-body methods like coupled-cluster theory in applications to closed-shell species makes them a natural candidate for creating hierarchies of multireference approaches that are systematically improvable. However, efforts to develop general multireference coupled cluster methods have often resulted in schemes that suffer from numerical instabilities, or that can target only a limited number of near-degenerate configurations. To address these issues, we have recently developed a novel family of methods inspired by the similarity (or flow) renormalization group (SRG)—a many-body formalism to diagonalize many-body operators via a series of infinitesimal transformations.1,2 Because of its renormalization group structure, the SRG offers a solution to the problem of divergences that arise in multireference theories. Starting from the SRG, we have recently proposed a multireference driven SRG (MR-DSRG) scheme for Quantum Chemistry applications.3 5 The MR-DSRG provides a convenient framework to derive numerically-robust multireference theories with electron correlation treated perturbatively or at a level comparable to that of coupled-cluster methods. The first part of this talk will review fundamental aspects of electron correlation in molecules and introduce elements of the similarity renormalization group. The second part will give an overview of recent developments of the MR-DSRG, including novel schemes to treat excited states and conical intersections, combinations of the MR-DSRG with the adaptive configuration interaction for large-scale applications, and hybrid schemes that combine quantum algorithms with the MR-DSRG.

Suggested Reading:

[1] S.D. Głazek, K.G. Wilson, Phys. Rev. D 49, 4214 (1994).

[2] F. Wegner, Ann. Phys. Rev. 506, 77 (1994).

[3] F.A. Evangelista, J. Chem. Phys. 141, 054109 (2014).

[4] C. Li, F. A. Evangelista, J. Chem. Theory Comput. 11, 2097 (2015).

[5] C. Li, F.A. Evangelista, Annu. Rev. Phys. Chem. 70, 052416 (2019).

## Design principles for organization and self-assembly far from equilibrium

### 10/9/19 4:15pm

### MIT Building 4, Room 163

### Suriyanarayanan Vaikuntanathan

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Non-equilibrium thermodynamics provides a useful set of tools to analyze and constrain the behavior of far from equilibrium systems. However, these tools have not yet been broadly applied to aid in the control of many body systems and materials assembled far from equilibrium. In this talk, I will report an application of ideas from non-equilibrium thermodynamics to the problems related to morphological changes in membranes, non-equilibrium self-assembly and more broadly control of material properties far from equilibrium. In many of these contexts, I will show how the material properties can be substantially constrained (and even predicted) using tools from non-equilibrium thermodynamics.

## Probing many body correlations with entangled photons

### 10/16/19 4:15pm

### MIT Building 4, Room 163

### Eric Bittner

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## Efficient Discovery of Potent Enzyme Inhibitors

### 10/30/19 4:15pm

### MIT Building 4, Room 163

### Bill Jorgensen

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Drug discovery is being pursued through computer-aided design, synthesis, biological assaying, and crystallography. 1-4 Lead identification features de novo design with the ligand growing program BOMB or virtual screening. Emphasis is placed on optimization of the resultant hits to yield potent, drug-like inhibitors. Monte Carlo/free-energy perturbation (FEP) simulations are executed to identify the most promising choices for heterocycles, substituents on rings, and linking groups. The illustrated applications center on the design of inhibitors targeting HIV-1 reverse transcriptase, macrophage migration inhibitory factor (MIF), and JAK2 kinase. Micromolar leads have been rapidly advanced to low nanomolar inhibitors, and numerous crystal structures for protein-inhibitor complexes have been obtained. Development and use of fluorescence polarization (FP) assays provide direct binding data. Key computational issues are considered including force fields, computation of absolute free energies of binding, and unbinding pathways from metadynamics.

## Structure and Chemistry of TiO_{2} Surfaces and Aqueous Interfaces: Insights from Simulations

### 11/13/19 4:15pm

### MIT Building 4, Room 163

### Annabella Selloni

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Titanium dioxide (TiO_{2}) is a naturally abundant, chemically stable, and environmentally compatible metal oxide, and also one of the most widely used photocatalysts for scientific and technological applications. Of particular relevance is the anatase phase of TiO_{2}, which predominates at the nanoscale. Since TiO_{2} photocatalysis usually takes place in humid or aqueous environment, the interface of anatase TiO_{2} with water is of fundamental importance, e.g. for elucidating the not yet fully understood mechanisms of photochemical water splitting and UV-induced hydrophilicity. In this talk, I shall present recent applications of ab initio molecular dynamics (AIMD) to study the structure and chemistry of anatase surfaces and their interaction with water, with main focus on the structure and dynamics of interfacial water on the majority anatase (101) surface, for which a number of experimental results have recently become available. I shall also discuss large scale molecular dynamics simulations with a deep neural network interatomic potential trained on the AIMD results. These simulations show a dynamical equilibrium of molecular and dissociated water on the TiO_{2} surface, consistent with the dissociation free energy estimate obtained from enhanced sampling techniques.

## Diversity, evolution, and exaptation of CRISPR-Cas systems

### 2/5/20 4:00pm

### MIT Building 4, Room 237

### Eugene Koonin

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CRISPR is famous for its use in new, revolutionary methods of genome engineering. However, the natural history of CRISPR-Cas, an adaptive immunity mechnism of archaea andbacteria, is no less fascinating than its applications. After presenting a broad background on CRISPR biology, I will focus on the recently updated evolutionary classification of CRISPR-Cas systems and cas genes, with an emphasis on the major developments that occurred since the publication of the latest such classification in 2015. One of these developments is the ongoing discovery of novel Class 2 CRISPR-Cas systems that now include 3 types and 17 subtypes compared to 2 types and 4 subtypes in 2015. These findings elucidate the multiple, independent origins of Class 2 CRISPR-Cas systems from mobile genetic elements. In addition, 2 new subtypes of type III and 2 of type IV are introduced, bringing the total numberof subtypes to 33. The second major novelty is the discovery of numerous derived CRISPR-Cas variants, often associated with mobile elements, that lack the nucleases required for interference. Some of these variants are involved in RNA-guided transposition whereas othersare predicted to perform still obscure functions distinct from adaptive immunity. The third highlight is the discovery of numerous families of ancillary CRISPR-linked genes, often implicated in signal transduction. Finally, many bacterial and archaeal viruses were shown to carry CRISPR mini-arrays that are employed in intervirus conflicts. Together, these findings substantially expand the functional diversity of CRISPR-Cas systems and clarify their evolutionary history, in particular, the multi-faceted connections with mobile genetic elements.

## Multi-scale Modeling of Genome Organization

### 2/12/20 4:00pm

### MIT Building 4, Room 237

### Bin Zhang

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Three-dimensional genome organization plays essential roles for all DNA-templated processes, including gene transcription, gene regulation, DNA replication, etc. Computer simulation can be an effective way of building genome structural models and improving our understanding of these molecular processes. It faces significant challenges, however. First, the human genome consists of over 6 billion base pairs, a system size that exceeds the capacity of traditional simulation approaches, even with the most powerful super-computer. Second, the set of molecular interactions that folds the genome is complex, with a wide array of protein molecules mediating the contacts between DNA segments. This complexity places a high demand on the chemical accuracy of force fields. Finally, the genome is inherently a non-equilibrium system, and one must go beyond conventional sampling techniques to account for the impact ATP-driven molecular motors on its organization. We tackle these challenges by bringing together statistical mechanics, computational modeling, and bioinformatics analysis to invent new methodologies that can accurately model the genome at different lengthscales. In this talk, I shall present our recent progress on bottom-up modeling of chromatin folding at a near-atomistic resolution and top-down simulations that aim to elucidate the principles of whole genome organization.

## Plasmonic lattices

### 2/26/20 4:00pm

### MIT Building 4, Room 237

### George Schatz

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This talk will overview the interplay between optics, plasmonics, and excitonics for systems that
consist of arrays of gold, silver or aluminum nanoparticles in 1D, 2D and 3D. I begin with
developing theory (electrodynamics) that describes the interaction of light with arrays of
plasmonic particles, including the special properties of plasmonic surface lattice resonances
(PSLR) for 1D and 2D lattices in which photonic resonances get hybridizes with plasmons to
generate high Q optical modes. The theory then evolves to considering the interaction of the
lattices with emitters, varying from a single emitter plus a lattice, where a generalized Fano-
Anderson model can be developed, and evolving to high concentrations of emitters where strong
coupling is found, and effective medium approximations are useful.
As application of these theories, I describe the unusual extinction and scattering properties of
PSLRs, including quadrupole resonance effects for aluminum lattices, and lattice plasmon lasers
in which laser dyes, quantum dots or upconversion nanoparticles are added to the nanoparticle
lattices and where the theory needs to combine electrodynamics with a quantum description of
the emitter. I also describe 3D lattices consisting of DNA—linked nanoparticle structures which
also give rise to resonance modes, but where nonresonant interference can lead to unusual
results.

## Determining rates and mechanisms of complex reactions

### 3/18/20 4:00pm

### MIT Building 4, Room 237

### Aaron Dinner

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Accurate quantitative predictions concerning reactions (rearrangements of atoms) in molecular and materials systems are fundamental to chemistry and are of practical importance for designing the next generations of catalysts, materials for sustainable energy, therapeutics, and molecular sensors, to name just a few examples. However, traditional kinetic theories are unable to treat many reactions of pressing interest for two reasons: (i) While traditional theories assume a well-defined activated complex (transition state) and a simple form for the underlying (free) energy landscape governing the dynamics, reactions in complex systems typically involve many intermediates and competing pathways. (ii) Traditional theories assume thermal statistics, but many reactions are subject to additional driving forces (e.g., electromotive forces in a battery). New computational methods for describing complex dynamics are needed.

In the first part of my talk, I will use biomolecular systems to illustrate these issues and then review two lines of research within the chemistry and applied mathematics communities: Transition Path Theory (TPT) and Markov State Models (MSMs). The essential idea in TPT is to express chemical kinetic quantities like rates in terms of sums over all contributing paths, rather than in terms of barrier crossings. MSMs are a means of aggregating information about these paths by dividing the configuration space into a set of states and constructing a state-to-state transition matrix.

In the second part of my talk, I will describe a recent framework that we have implemented that builds on TPT and MSMs to obtain estimates of chemical kinetic quantities from molecular dynamics data. The essential idea is to cast the chemical kinetic quantities as solutions to operator equations that can be solved by linear combinations of basis functions, and I will discuss the choice of basis functions with the aid of paradigmatic molecular and materials systems. Finally, I will explain how we can go beyond the Markov assumption and describe an algorithm that provides unbiased estimates of rates and other dynamical statistics for both reversible and irreversible stochastic processes.

**Postponed due to COVID-19**

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### 3/25/20 4:00pm

### MIT Building 4, Room 237

### Andrew Ferguson

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**Postponed due to COVID-19**

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### 4/8/20 4:00pm

### MIT Building 4, Room 237

### Anna Krylov

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**Postponed due to COVID-19**

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### 4/15/20 4:00pm

### MIT Building 4, Room 237

### Ilpo Vattulainen

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**Postponed due to COVID-19**

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### 4/29/20 4:00pm

### MIT Building 4, Room 237

### Dan Tawfik

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**Postponed due to COVID-19**