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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Understanding flavin electronic structure and spectra

Abstract Flavins have emerged as central to electron bifurcation, signaling, and countless enzymatic reactions. In bifurcation, two electrons acquired as a pair are separated in coupled transfers wherein the energy of both is concentrated on one of the two. This enables organisms to drive demanding reactions based on abundant low‐grade chemical fuel. To enable incorporation of this and other flavin capabilities into designed materials and devices, it is essential to understand fundamental principles of flavin electronic structure that make flavins so reactive and tunable by interactions with protein. Emerging computational tools can now replicate spectra of flavins and are gaining capacity to explain reactivity at atomistic resolution, based on electronic structures. Such fundamental understanding can moreover be transferrable to other chemical systems. A variety of computational innovations have been critical in reproducing experimental properties of flavins including their electronic spectra, vibrational signatures, and nuclear magnetic resonance (NMR) chemical shifts. A computational toolbox for understanding flavin reactivity moreover must be able to treat all five oxidation and protonation states, in addition to excited states that participate in flavoprotein's light‐driven reactions. Therefore, we compare emerging hybrid strategies and their successes in replicating effects of hydrogen bonding, the surrounding dielectric, and local electrostatics. These contribute to the protein's ability to modulate flavin reactivity, so we conclude with a survey of methods for incorporating the effects of the protein residues explicitly, as well as local dynamics. Computation is poised to elucidate the factors that affect a bound flavin's ability to mediate stunningly diverse reactions, and make life possible. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Electronic Structure Theory > Combined QM/MM Methods Theoretical and Physical Chemistry > Spectroscopy

59 BASIC BIOLOGICAL SCIENCES↗

QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations

Combined quantum mechanical and molecular mechanical (QM/MM) methods play an important role in multiscale modeling and simulations. QMMM 2023 is a general-purpose program for single-point calculations, geometry optimizations, transition-state optimizations, and molecular dynamics (MD) at the QM/MM level. It calls a QM package and an MM package to perform the required single-level calculations and combines them into a QM/MM energy by a variety of schemes. QMMM 2023 supports GAMESS-US, Gaussian, and ORCA as QM packages and Tinker as the MM package. Four types of treatments are available for embedding the QM subsystem in the MM environment: mechanical embedding with gas-phase calculations of the QM region, electronic embedding that allows polarization of the QM region by the MM environment, polarizable embedding for mutual polarization of the QM and MM regions, and flexible embedding for both mutual polarization and partial charge transfer between the QM and MM regions. Boundaries between QM and MM regions that pass through covalent bonds can be treated by several methods, including the redistributed charge (RC) scheme, redistributed charge and dipole (RCD) scheme, balanced-RC scheme, balanced-RCD scheme, screened charge scheme that takes account of charge penetration effects, and smeared charge scheme that delocalizes the MM charges near the QM–MM boundary. Geometry optimization can be done using the optimizer implemented in QMMM 2023 or the Berny optimizer in Gaussian through external calls to Gaussian. Molecular dynamics simulations can be performed at the pure-MM level, pure-QM level, fixed-partitioning QM/MM level, and adaptive-partitioning QM/MM level. As a result, the adaptive-partitioning treatments permit on-the-fly relocation of the QM–MM boundary by dynamically reclassifying atoms or groups into the QM or MM subsystems.

97 MATHEMATICS AND COMPUTING↗

Origins of Acid-Gas Stability Behavior in Zeolitic Imidazolate Frameworks: The Unique High Stability of ZIF-71

Zeolitic imidazolate frameworks (ZIFs) are promising materials for industrial process separations, but recent literature reports have highlighted their vulnerability to acid gases (e.g., SO 2 , CO 2 , NO 2 , H 2 S), often present in practical applications. While previous work has documented the widely varying stability behavior of many ZIFs under varying (humid and dry) acid gas environments, efforts to explain or correlate these experimental observations via empirical descriptors have not succeeded. A key observation is that ZIF-71 (RHO topology) is an extraordinarily stable ZIF material, retaining both structure and porosity under prolonged humid SO 2 exposure whereas many other well-known ZIFs with different linkers and topologies (such as ZIF-8) were shown to degrade. Through a combination of hybrid quantum mechanics/molecular mechanics (QM/MM) based methods and statistical mechanical models, we successfully explain this important experimental observation via atomistic investigations of the reaction mechanism. Our holistic approach reveals an ~9 times lower average defect formation rate in ZIF-71 RHO compared to ZIF-8 SOD, leading to the conclusion that the observed experimental stability of this material rises from kinetic effects. Moreover, our analysis reveals that differing stability of the two materials is determined by the distributions of acid gas molecules, which is difficult to capture using empirical descriptors. Furthermore, our results suggest wider applicability of the present approach, toward identifying tuned functional groups and topologies that move the acid gas distributions away from more reactive sites and thus allow enhanced kinetic stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards the Accurate Thermodynamic Characterization of Enzyme Reaction Mechanisms

We employed QM/MM molecular dynamics (MD) simulations to characterize the rate-limiting step of the glycosylation reaction of pancreatic α-amylase with combined DFT/molecular dynamics methods (PBE/def2-SVP : AMBER). Upon careful choice of four starting active site conformations based on thorough reactivity criteria, Gibbs energy profiles were calculated with umbrella sampling simulations within a statistical convergence of 1 -2 kcal · mol -1 . Nevertheless, Gibbs activation barriers and reaction energies still varied from 11.0 to 16.8 kcal · mol -1 and -6.3 to +3.8 kcal · mol -1 depending on the starting conformations, showing that despite significant state-of-the-art QM/MM MD sampling (0.5 ns/profile) the result still depends on the starting structure. In conclusion, the results supported the one step dissociative mechanism of Asp197 glycosylation preceded by an acid-base reaction by the Glu233, which are qualitatively similar to those from multi-PES QM/MM studies, and thus support the use of the latter to determine enzyme reaction mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical Reactivity Through Adaptive Quantum Mechanics/Many-Body Representations: Theoretical Development, Software Implementation, and Applications (Final Report)

The main objective of this research project was the development and application of a new theoretical/computational framework to model chemical transformations and electronic excitations in fluid mixtures across different phases. Our theoretical/computational framework combines our data-driven many-body (DD-MB) potentials representing molecular interactions with adaptive schemes for modeling chemical reactions in solution. The combination of these two components resulted in an adaptive quantum mechanics/many-body (adQM/MB) method that largely suppresses discontinuities between QM and MM regions, which affect existing QM/MM methods, and thus provides an accurate representation of both quantum mechanical and environmental effects through a rigorous description of mutual polarization between QM and MM regions. The implementation of our DD-MB potentials and adQM/MB method in popular software enabled computer simulations of solvation phenomena, reactive processes, and electronic excitations in fluid mixtures with chemical and spectroscopic accuracy, representing a major step toward realistic computer simulations of a wide range of molecular systems relevant to the DOE mission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational quantum chemistry of metal–organic frameworks

Metal–organic frameworks (MOFs) have premium exceptional properties for a variety of functions, such as gas separation and storage and catalysis. The large variety of possible inorganometallic nodes and organic linkers provide an almost unlimited number of combinations for assembling MOFs, which makes the experimental characterization and examination of all potentially useful combinations practically impossible. Furthermore, experimental studies of MOFs typically fall short in uncovering crucial details regarding their mechanisms of action or the molecular details responsible for their functional properties, such as the nature of adsorbate binding or the structures of transition states. Computational modeling has, therefore, become an efficient and important tool for strategizing the functionalization of MOFs and explicating the mechanisms of their functions. Furthermore, we review the computational methodologies used for computational studies of MOFs, especially Kohn–Sham density functional theory and combined quantum mechanical and molecular mechanical methods for calculating their structural, electronic, and magnetic properties, as well as for understanding the mechanisms of MOFs' applications to magetic devices, thermal conduction, gas adsorption, separation, storage, and sensing, thermal catalysis, photocatalysis, and electrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Building Toward the Future in Chemical and Materials Simulation with Accessible and Intelligently Designed Web Applications

Over the last few decades, significant progress has been made in the development and use of electronic structure and other molecular simulation methods. As these methods become more mature and are able to simulate larger and more complex chemical simulations, the need for improvement in scientific visualization, molecular builders, simplified input to simulation methods, and the development of new approaches and languages to describe simulations, along with workflows to carry them out, becomes more apparent. In this chapter, we describe our recent efforts in developing a prototype open-source computational tool called Arrows that combines NWChem, SQL and NoSQL databases, email, web APIs, and web applications in a way that make molecular and materials modeling accessible to all scientists and engineers. At the same time, because of its simplified input, it provides a framework for expert users to carry out large numbers of calculations and run complex workflows.