171. Connecting the dots for fundamental understanding of structure-photophysics-property relationships of

        COFs, MOFs, and perovskites using a multiparticle Holstein formalism.

        R. Ghosh, F. Paesani. Chem. Sci. 14, 1040 (2023). [link]

Elucidating structure-photophysics-property relationships in functional materials is nontrivial and requires

a fundamental understanding of the intricate interplay among excitons, polarons, bipolarons, phonons,

inter-layer stacking interactions, and different forms of structural and conformational defects. Here, we describe

a unified theoretical framework in which the electronic coupling as well as the local coupling between

the electronic and nuclear degrees of freedom can be efficiently described for a wide range of quasiparticles

with similarly structured Holstein-style Hamiltonians. We then discuss excitonic and polaronic photophysical

signatures in polymers, COFs, MOFs, and perovskites, and bridge the gap between different research fields

using a Multiparticle Holstein Formalism. We envision that the synergistic integration of state-of-the-art

computational approaches with the Multiparticle Holstein Formalism will help establish new design strategies

for the development of next-generation materials optimized for a broad range of energy-related applications.

© Paesani Research Group. All rights reserved.

170. Data-driven many-body potential energy functions for generic molecules: Linear alkanes as a proof-of-

        concept application. E.F. Bull-Vulpe, M. Riera, S.L. Bore, F. Paesani. J. Chem. Theory Comput. In press. [link]

We present a generalization of the many-body energy (MB-nrg) theoretical/computational framework that

enables the development of data-driven potential energy functions (PEFs) for generic covalently bonded

molecules, with arbitrary quantum mechanical accuracy. Exploiting the "nearsightedness" of electronic matter,

the energy of generic molecules is expressed as a sum of individual many-body energies of incrementally

larger subsystems which are represented by a combination of data-driven permutationally invariant polynomials

optimized to reproduce electronic structure data at an arbitrary level of theory and classical many-body

polarization. As a proof-of-concept application of the general MB-nrg framework, we present MB-nrg PEFs

that accurately reproduce reference energies, harmonic frequencies, and potential energy scans of alkanes,

independently of their length. Since, by construction, the MB-nrg framework can be applied to generic

covalently bonded molecules, we envision future computer simulations of complex molecular systems using

data-driven MB-nrg PEFs, with arbitrary quantum mechanical accuracy.

173. A highly sensitive fluorescent reporter for adenine base editing reveals DNA base editing by the wild-type

        tRNA adenosine deaminase enzyme TadA. B.L. Ranzau, K.L. Rallapalli, M. Evanoff, F. Paesani, A.C. Komor.

        Under review.

Adenine base editors (ABEs) convert A•T to G•C base pairs in DNA by utilizing an adenosine deaminase enzyme

to modify target adenosines to inosine intermediates. Due to the lack of a naturally occurring adenosine deaminase

that can modify DNA, ABEs were evolved from a tRNA-deaminating enzyme, TadA. Previous experiments utilizing

an ABE comprised of a wild-type (wt) TadA showed no detectable activity on DNA, and directed evolution was

therefore required to enable this enzyme to accept DNA as a substrate. Here we show that wtTadA can perform

base editing in DNA in both bacterial and mammalian cells, with a strict sequence motif requirement of TAC.

We leverage this discovery to optimize a reporter assay to detect base editing levels as low as 0.01%. Finally, we use

this assay along with molecular dynamics simulations of full ABE:DNA complexes to better understand how the

sequence recognition of mutant TadA variants change as they accumulate mutations to better edit DNA substrates. 

172. Data-driven many-body potentials from density functional theory for aqueous phase chemistry.

        E. Palos, S. Dasgupta, E. Lambros, F. Paesani. Chem. Phys. Rev. 4, 011301 (2023). [link]

The ubiquity of water in chemical and biological processes demands a unified understanding of its physics, from the

single-molecule to the thermodynamic limit and everything in between. Recent advances in the development of

data-driven and machine-learning potentials have accelerated simulation of water and aqueous systems with DFT

accuracy. However, the anomalous properties of water in the condensed phase, where a rigorous treatment of both

local and non-local many-body interactions is in order, is often unsatisfactory or partially missing in DFT models of water.

Here, we discuss the modeling of water and aqueous systems based on DFT, and provide a comprehensive description

of a general theoretical/computational framework, coined MB-DFT, for the development of data-driven many-body

potentials from DFT reference data. Theoretical considerations are emphasized, including the role that the delocalization

error plays in MB-DFT potentials of water, and the possibility to elevate DFT and MB-DFT to near-chemical-accuracy

through a density-corrected formalism. Finally, we identify open challenges and discuss future directions for MB-DFT

simulations in condensed phases.

175. A “short blanket” dilemma for a state-of-the-art neural network potential for water: Reproducing experimental

        properties or the physics of the underlying physics? Y. Zhai, A. Caruso, S.L. Bore, Z. Luo, F. Paesani.

        J. Chem. Phys. 158, 084111 (2023). [link]

We explore the possibility of combining the computational efficiency of DeePMD and the demonstrated accuracy

of the MB-pol data-driven many-body potential to train a DNN potential for large-scale simulations of water across

its phase diagram. We find that the DNN potential is able to reliably reproduce the MB-pol results for liquid water

but provides a less accurate description of the vapor-liquid equilibrium properties. This shortcoming is traced

back to the inability of the DNN potential to correctly represent many-body interactions. An attempt to explicitly

include information about many-body effects results in a new DNN potential that exhibits opposite performance,

being able to correctly reproduce the MB-pol vapor-liquid equilibrium but losing accuracy in the description of the

liquid properties. These results suggest that DeePMD DNN potentials are not able to correctly “learn” and,

consequently, represent many-body interactions. The computational efficiency of DeePMD can still be exploited

to train DNN potentials on data-driven many-body potentials to enable large-scale, chemically accurate simulations.

174. Structure and thermodynamics of water adsorption in NU-1500-Cr. C.-H. Ho, M.L. Valentine, Z. Chen, H. Xie,

        O.K. Farha, W. Xiong, F. Paesani. Under review. [link]

The mechanism of water adsorption in NU-1500-Cr is investigated using a combination of molecular dynamics

simulations and infrared spectroscopy. Calculations of thermodynamic and dynamical properties of water as a function

of relative humidity allow for following the adsorption process from the initial hydration stage to complete filling of the

MOF pores. Initial hydration begins at the water molecules that saturate the open Cr3+ sites of the framework, which is

then followed by the formation of water chains that extend along the channels connecting the hexagonal pores of the

framework. Water present in these channels gradually coalesces and fills the hexagonal pores sequentially after the

channels are completely hydrated. The development of hydrogen-bond networks inside the MOF pores as a function of

relative humidity is characterized at the molecular level using experimental and computational infrared spectroscopy.

A detailed analysis of the OH-stretch vibrational band indicates that the low-frequency tail, which is common in the

experimental infrared spectra of water in MOFs, stems from strongly polarized hydrogen-bonded water molecules,

suggesting the presence of some structural dis- order in the experimental samples.

176. Quantum phase diagram of water. S.L. Bore, F. Paesani. Under review. [link]

Since the experimental characterization of the low-pressure region of the phase diagram of

water in the early 1900s, scientists have been on a quest to understand the thermodynamic

stability of ice polymorphs on the molecular level. In this study, we demonstrate that combining the MB-pol data-driven many-body potential for water, which was rigorously derived from “first principles” and exhibits chemical accuracy, with advanced

enhanced-sampling algorithms, which correctly describe the quantum nature of molecular

motion and thermodynamic equilibria, enables computer simulations of the phase diagram of

water with an unprecedented level of realism. Besides providing unique insights into how

enthalpic, entropic, and nuclear quantum effects shape the free-energy landscape of water,

we demonstrate that recent progress in data-driven many-body potentials and simulation

algorithms has effectively opened the door to realistic computational studies of complex

molecular systems, thus bridging the gap between experiments and simulations.

177. Unveiling unexpected modulator-CO2 dynamics within a zirconium metal-organic framework. T.M. Rayder,

        F. Formalik, S.M. Vornholt, H. Frank, S. Lee, M. Alzayer, Z. Chen, T. Islamoglu, F. Paesani, K.W. Chapman,

        R.Q. Snurr, O.K. Farha. Under review.

Carbon capture, storage, and utilization (CCSU) represents an opportunity to mitigate carbon emissions that

drive global anthropogenic climate change. Promising materials for CCSU through gas adsorption have been

developed by leveraging the porosity, stability, and tunability of extended crystalline coordination polymers

called metal-organic frameworks (MOFs). Herein, we report a multifaceted in situ analysis following the

adsorption of CO2 in MOF-808 variants with different capping agents (formate, acetate, and trifluoroacetate

– FA, AA, and TFA, respectively). In situ DRIFTS analysis paired with in situ powder X-ray diffraction revealed

unexpected CO2 interactions at the node associated with dynamic behavior of node-capping modulators in

the pores of MOF-808, which had previously been assumed to be static. MOF-808-TFA displays two binding

modes for CO2, resulting in higher binding affinity and gas uptake of CO2. Computational analyses further

support these dynamic observations.

178. Engineering flat and dispersive bands in 2D layered COFs via interlayer stacking and donor-acceptor strategy.

        Y. Pan, C.H. Ho, F. Paesani, R. Ghosh. Under review. [link]

Covalent organic frameworks (COFs) are an emergent class of two-dimensional (2D) crystalline organic materials that exhibit unique electronic, optical, and transport prop- erties. In this study, we employ density functional theory (DFT) and the multiparticle Holstein

formalism (MHF) to investigate the electronic structure and two-dimensional coherence of polarons in

donor-acceptor COFs as a function of interlayer stacking arrangement. We show that simple modifications in

the interlayer stacking arrangement have a profound impact on the transport properties, which can range from

metallic behavior with vanishing band gap to highly localized states having completely flat bands. The extent of

charge delocalization is found to be sensitive to the type of stacking arrangement and the precise arrangement

of the donor and acceptor fragments within the COF structure. The results from the DFT calculations are

consistent with MHF-based simulations, demonstrating that stacking-induced interlayer interactions facilitate

better in-plane charge delocalization. As a consequence, we find that interlayer interactions help circumvent

defect-induced trap states to enhance overall charge delocalization.

179. Towards data-driven many-body simulations of biomolecules in solution: N-methyl acetamide as a proxy for

        the protein backbone. R. Zhou, M. Riera, F. Paesani. Under review. [link]

The development of molecular models with quantum-mechanical accuracy for predictive simulations of biomolecular systems

has been a long standing goal in the field of computational biophysics and biochemistry. As a first step towards a transferable

force field for biomolecules entirely derived from “first principles”, we introduce a data-driven many-body energy (MB-nrg)

potential energy function (PEF) for N-methyl acetamide (NMA), a peptide bond capped by two methyl groups that is commonly

used as a proxy for the protein backbone. The MB- nrg PEF is shown to accurately describe the energetics and structural

properties of an isolated NMA molecule, including the normal modes of both cis and trans isomers and the energies along the

isomerization path, as well as the multidimensional potential energy landscape of the NMA–H2O dimer in the gas phase.

Importantly, we show that the MB-nrg PEF is fully transferable, enabling molecular dynamics simulations of NMA in solution

with chemical accuracy. Comparisons with results obtained with a popular pairwise-additive force field for biomolecules and a

classical polarizable PEF demonstrate the ability of the MB-nrg PEF to accurately represent many-body effects in NMA–H2O

interactions at both short and long distances, which is key to guaranteeing full transferability from the gas to the liquid phase.

180. MB-pol(2023): Sub-chemical accuracy for water simulations from the gas to the liquid phase. X. Zhu, M. Riera,

        E.F. Bull-Vulpe, F. Paesani. Under review. [link]

We use the MB-pol theoretical/computational framework to introduce a new family of data-driven many-body

potential energy functions (PEFs) for water, named MB-pol(2023). By employing larger 2-body and 3-body

training sets, including an explicit machine-learned representation of 4-body energies, and adopting more

sophisticated machine-learned representations of 2-body and 3-body energies, we demonstrate that the

MB-pol(2023) PEFs achieve sub-chemical accuracy in modeling the energetics of the hexamer isomers,

outperforming both the original MB-pol and q-AQUA PEFs, which currently provide the most accurate description

of water clusters in the gas phase. Importantly, the MB-pol(2023) PEFs provide remarkable agreement with

the experimental results for various properties of liquid water, improving upon the original MB-pol PEF and

effectively closing the gap with experimental measurements. We also demonstratte that our MB-pol(2023) PEFs

can be trivially improved, without changing the underlying functional form, by training the current 2-body,

3-body, and 4-body terms on more “complete” datasets and/or adding explicit n-body terms with n > 4.