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).
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. 19, 4494 (2023).
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,
ChemBioChem e202200788 (2023).
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).
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).
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, Commun. Chem. 6, 70 (2023).
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. Realistic phase diagram of water from "first principles" data-driven quantum simulations. S.L. Bore, F. Paesani,
Nat. Commun. 14, 3349 (2023).
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. 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 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, J. Am. Chem. Soc. 145, 11195 (2023).
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, Chem. Mater. 16, 6235 (2023).
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, J. Chem. Theory Comput. 19, 4308 (2023).
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, J. Chem. Theory Comput. 19, 3551 (2023).
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.
181. Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix.
Y. Zhou, S.L. Bore, A.R. Tao, F. Paesani, G. Arya. Under review.
In this study, we develop a many- body potential for describing the effective interactions between spherical
polymer-grafted NPs in a polymer matrix through a machine learning (ML) approach. The approach involves using
permutationally invariant polynomials to fit two- and three-body interactions derived from potential of mean force
(PMF) calculations. This potential developed here reduces the computational cost by several orders of magnitude,
thereby allowing us to explore assembly behavior over large length and time scales. We show that the potential not
only reproduces previously known assembled phases, such as 1D strings and 2D hexagonal sheets, which cannot
be achieved using two-body potentials, but can also help discover interesting new phases, such as networks,
clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition
between two- and three-body interactions. Our approach for deriving many- body effective potentials can be
readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior
and dissect the role of individual interaction energy terms in the overall potential in the observed behavior.
182. Computational insights into the interaction of water with the UiO-66 metal-organic framework and its
functionalized derivatives. J. Zhang, F. Paesani, M. Lessio, J. Mater. Chem. C 11, 10247 (2023).
We provide computational insights into the adsorption of water in UiO-66 and its functionalized derivatives
to reveal the role played by different adsorption sites and functional groups in the adsorption mechanism.
To this end, we developed molecular models for UiO-66, UiO-66-NH2, UiO-66-OH, and UiO-66-(OH)2
compatible with the MB-pol data-driven many-body potential of water, which were used to perform MD
simulations and calculate radial distribution functions, IR spectra, and two-dimensional density distributions
of water in the the various MOFs. Our results consistently show that the μ3-OH sites are the preferential
interaction sites for water in UiO-66 and all its variants, and the formation of localized water clusters inside
the octahedral pores is responsible for the abrupt step in the experimental adsorption isotherms.
Furthermore, the presence of different functional groups allows water to cluster in the octahedral pores at
lower RH, thus making UiO-66 a more efficient water harvester. Our study provides molecular-level
insights into the pore filling process, which are key to the design of more efficient water harvesting MOFs.
183. MBX: A many-body energy and force calculator for data-driven many-body simulations. M. Riera, C. Knight,
E.F. Bull-Vulpe, X. Zhu, H. Agnew, D.G.A. Smith, A.C. Simmonett, F. Paesani, J. Chem. Phys. 159, 054802 (2023).
MBX is a C++ library that implements many-body potential energy functions (PEFs) within the “many-body energy”
(MB-nrg) formalism. MB-nrg PEFs integrate an underlying polarizable model with explicit machine-learned
representations of many-body interactions to achieve chemical accuracy from the gas to the condensed phases.
MBX can be employed either as a stand-alone package or as an energy/force engine that can be integrated
with generic software for molecular dynamics and Monte Carlo simulations. MBX is parallelized internally using
OpenMP, and can utilize MPI when available in interfaced molecular simulation software. MBX enables classical
and quantum molecular simulations with MB-nrg PEFs, as well as hybrid simulations that combine conventional
force fields and MB-nrg PEFs, for diverse systems ranging from small gas-phase clusters to aqueous solutions
and molecular fluids to biomolecular systems and metal-organic frameworks.
184. Elucidating the competitive adsorption of H2O and CO2 in CALF-20: New insights for enhanced carbon
capture metal-organic frameworks. C.-H. Ho, F. Paesani, ACS Appl. Mater. Interfaces 15, 49287 (2023).
In this study, we investigates the simultaneous adsorption of water (H2O) and carbon dioxide (CO2) as a function of RH
in CALF-20. Advanced computer simulations reveal that, due to their similar interactions with the framework, H2O and
CO2 molecules compete for the same binding sites, occupying similar void regions within the CALF-20 pores. This
competition results in distinct thermodynamic and dynamical behavior of H2O and CO2 molecules, depending on whether
one or both guest species are present. Notably, the presence of CO2 molecules forces the H2O molecules to form more
connected hydrogen-bond networks within smaller regions, slowing water reorientation dynamics and decreasing water
entropy. Conversely, the presence of water speeds up the reorientation of CO2 molecules, decreases CO2 entropy, and
increases the propensity for CO2 to be adsorbed within the framework due to stronger water-mediated interactions. Due
to the competition for the same void spaces, both H2O and CO2 molecules exhibit slower diffusion when molecules of the
other guest species are present. These findings offer valuable strategies and insights to enhance the differential
affinity of H2O and CO2 for MOFs specifically designed for carbon capture applications.
187. Consistent density functional theory-based description of ion hydration through density-corrected many-body
representations. E. Palos, A. Caruso, F. Paesani. In review.
Delocalization error constrains the accuracy of density functional theory (DFT) in describing molecular interactions in
ion–water systems. Using Na+ and Cl− in water as model systems, we calculate the effects of delocalization error in
the SCAN functional for describing ion–water and water–water interactions in hydrated ions, and demonstrate that
density-corrected SCAN (DC-SCAN) predicts n-body and interaction energies with an accuracy approaching coupled
cluster theory. The performance of DC-SCAN is size-consistent, maintaining an accurate description of molecular
in- teractions well beyond the first solvation shell. Molecular dynamics simulations at ambient conditions with
MB-SCAN(DC) potentials, derived from the many-body expansion, predict the solvation structure of Na+ and Cl−
in quantitative agreement with reference data, while simultaneously reproducing the structure of liquid water.
Beyond rationalizing the accuracy of density-corrected models of ion hydration, our findings suggest that our unified
density-corrected many-body formalism holds great promise for efficient DFT-based simulations of condensed-phase
systems with chemical accuracy.
186. Balance between physical interpretability and energetic predictability in widely used dispersion-corrected
density functionals. S. Dasgupta, E. Palos, Y. Pan, F. Paesani. In review.
We assess the performance of different dispersion models for several popular density functionals across a diverse
set of non-covalent systems, ranging from the benzene dimer to molecular crystals. By analyzing the interaction
energies and their individual components, we demonstrate that there exists variability across different systems for
empirical dispersion models that are calibrated for reproducing the interaction energies of specific systems. Thus,
parameter fitting may undermine the underlying physics, as dispersion models rely on error compensation among
the different components of the interaction energy. Energy decomposition analyses reveal that, the accuracy of
several dispersion-corrected functionals originates from significant compensation between dispersion and charge
transfer energies. These results highlight the propensity for unpredictable behavior in various dispersion-corrected
density functionals across a wide range of molecular systems, akin to the behavior of force fields. Future development
of dispersion models should prioritize the faithful description of the dispersion energy, a shift that promises greater
accuracy in capturing the underlying physics across diverse molecular and extended systems.
185. Humidity-responsive polymorphism in CALF-20: A resilient MOF physisorbent for CO2 capture.
Z. Chen, C.-H. Ho, X. Wang, S.M. Vornholt, T.M. Rayder, T. Islamoglu, O.K. Farha, F. Paesani, K.W. Chapman,
ACS Materials Lett. 5, 2942 (2023).
We find that the originally reported CALF-20 phase (now denoted α-CALF-20) undergoes a structure
transformation following exposure to humid environments to generate a new polymorph, β-CALF-20,
identified here through combined synchrotron powder X-ray diffraction and pair distribution function (PDF)
analysis. This α-to-β transformation is fully reversible with α-CALF-20 being regenerated by treating
β-CALF-20 under dry air or vacuum. The rapid reversion of β- to α-CALF-20 under conditions relevant to
measuring the gas adsorption isotherm required the CO2 adsorption properties for β-CALF-20 to be
evaluated computationally. Experimental evaluation of the adsorption behavior of β-CALF-20 is not
practical. These analyses suggest that β-CALF-20 has a higher CO2 heat of adsorption than α-CALF-20,
which may be advantageous to CO2 sorption selectivity at low partial pressures.