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At least 91 records · Page 5

Proton Dissociation and Delocalization under Stepwise Hydration of Zeolite HZSM-5

The protonation behavior of zeolite Brønsted acid sites (BAS) in the presence of water is important for the performance of these widely used catalysts. Despite extensive study, the number of water molecules necessary for deprotonation is not well understood, in large part because experiments have been unable to access this information. In this work, we report experimental evidence for full deprotonation of the BAS in the presence of two or more water molecules, with a deprotonation energy of 1.6 kcal/mol. Linear IR absorption and 2D IR spectra were measured over a wide range of controlled hydration levels from 0.5 to 8.0 equivalents of H 2 O/Al at a constant temperature. Distinct spectral signatures of the protonated BAS and excess proton are identified, and their hydration dependence is analyzed quantitatively. Using the experiment as a benchmark, ab initio molecular dynamics simulations are reported that reproduce the experimental trends in the protonation state and IR spectra. The proton charge position and delocalization are quantified in clusters of 1–8 H 2 O molecules using the recently developed rCEC method. This analysis provides insight into the proton structure in confined water clusters, showing that the excess charge remains relatively localized between two oxygen atoms across the hydration range.

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Enabling Efficient and Accurate Computational Studies of MOF Reactivity via QM/MM and QM/QM Methods

Electronic structure calculations can provide unique insight into metal–organic framework (MOF) reactivity and defect formation. Such calculations can be broadly categorized as utilizing either periodic or cluster models, each with their respective advantages and disadvantages. In the present study, we demonstrate how multiscale methods can leverage the advantages of both approaches to enable high levels of accuracy and computational efficiency in studies of MOF reactivity. Using defect formation in a zeolitic imidazolate framework (ZIF) as a prototypical example, we benchmark a quantum mechanics/molecular mechanics (QM/MM) scheme that enables highly efficient cluster-based calculations on MOFs. We demonstrate the importance of correctly accounting for the influence of both dative bond cleavage in the QM cluster and long-range mechanical coupling to the bulk to achieving accurate QM/MM studies of MOFs. We subsequently leverage these cluster models in a QM/QM scheme that goes beyond standard DFT to yield “gold-standard” correlated wave function results on MOFs at modest computational cost. Crucially, we find several cases in which the incorporation of these correlated corrections yields qualitatively important corrections over conventional DFT values.

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Efficient Parameterization of Density Functional Tight-Binding for 5 f -Elements: A Th–O Case Study

Density functional tight binding (DFTB) models for f-element species are challenging to parametrize owing to the large number of adjustable parameters. The explicit optimization of the terms entering the semiempirical DFTB Hamiltonian related to f orbitals is crucial to generating a reliable parametrization for f-block elements, because they play import roles in bonding interactions. However, since the number of parameters grows quadratically with the number of orbitals, the computational cost for parameter optimization is much more expensive for the f-elements than for the main group elements. In this work we present a set of efficient approaches for mitigating the hurdle imposed by the large size of the parameter space. A novel group-by-orbital correction functions for two-center bond integrals was developed. With this approach the number of parameters is reduced, and it grows linearly with the number of elements, maintaining the accuracy and the number of parameters, in the case of f elements, by more than 40%. The parameter optimization step was accelerated by means of the mini-batch BFGS method. This method allows parameter optimizations with much larger training sets than other single batch methods. A stochastic optimizer was employed that helped overcome shallow local minima in the objective function. The proposed algorithm was used to parametrize the DFTB Hamiltonian for the Th–O system, which was subsequently applied to the study of ThO 2 nanoparticles. The training set consisted of 6322 unique structures, which is barely feasible with conventional optimization methods. The optimized parameter set, LANL-ThO, displays good agreement with DFT-calculated properties such as energies, forces, and structures for both clusters and bulk ThO 2 . Benefiting from the fewer number of parameters and lower computational costs for objective function evaluations, this new approach shows its potential applications in DFTB parametrization for elements with high angular momentum, which present a challenge to conventional methods.

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Data-Driven Many-Body Models for Molecular Fluids: CO 2 /H 2 O Mixtures as a Case Study

In this study, we extend the scope of the many-body TTM-nrg and MB-nrg potential energy functions (PEFs), originally introduced for halide ion–water and alkali-metal ion–water interactions, to the modeling of carbon dioxide (CO2) and water (H2O) mixtures as prototypical examples of molecular fluids. Both TTM-nrg and MB-nrg PEFs are derived entirely from electronic structure data obtained at the coupled cluster level of theory and are, by construction, compatible with MB-pol, a many-body PEF that has been shown to accurately reproduce the properties of water. Although both TTM-nrg and MB-nrg PEFs adopt the same functional forms for describing permanent electrostatics, polarization, and dispersion, they differ in the representation of short-range contributions, with the TTM-nrg PEFs relying on conventional Born–Mayer expressions and the MB-nrg PEFs employing multidimensional permutationally invariant polynomials. By providing a physically correct description of many-body effects at both short and long ranges, the MB-nrg PEFs are shown to quantitatively represent the global potential energy surfaces of the CO 2 –CO 2 and CO 2 –H 2 O dimers and the energetics of small clusters, as well as to correctly reproduce various properties in both gas and liquid phases. Furthermore, building upon previous studies of aqueous systems, our analysis provides further evidence for the accuracy and efficiency of the MB-nrg framework in representing molecular interactions in fluid mixtures at different temperature and pressure conditions.

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Sulfur-Ligated [2Fe-2C] Clusters as Synthetic Model Systems for Nitrogenase

Metal clusters featuring carbon and sulfur donors have coordination environments comparable to the active site of nitrogenase enzymes. Here, we report a series of di-iron clusters supported by the dianionic yldiide ligands, in which the Fe sites are bridged by two μ 2 -C atoms and four pendant S donors. The [L 2 Fe 2 ] (L = {[Ph 2 P(S)] 2 C} 2– ) cluster is isolable in two oxidation levels, all-ferrous Fe 2 II and mixed-valence Fe II Fe III . The mixed-valence cluster displays two peaks in the Mössbauer spectra, indicating slow electron transfer between the two sites. The addition of the Lewis base 4-dimethylaminopyridine to the Fe2 II cluster results in coordination with only one of the two Fe sites, even in the presence of an excess base. Conversely, the cluster reacts with 8 equiv of isocyanide t BuNC to give a monometallic complex featuring a new C–C bond between the ligand backbone and the isocyanide. The electronic structure descriptions of these complexes are further supported by X-ray absorption and resonant X-ray emission spectroscopies.

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Precision Loading and Delivery of Molecular Cargo by Size-Controlled Coacervation of Gold Nanoparticles Functionalized with Elastin-like Peptides

Thermoresponsive elastin-like peptides (ELPs) have been extensively investigated in biotechnology and medicine, but little attention has been paid to the process by which coacervation causes ELP-decorated particles to aggregate. Here, using gold nanoparticles (AuNPs) functionalized with a cysteine-terminated 96-repeat of the VPGVG sequence (V96-Cys), we show that the size of the clusters that reversibly form above the ELP transition temperature can be finely controlled in the 250 to 930 nm range by specifying the concentration of free V96-Cys in solution and using AuNPs of different sizes. We further find that the localized surface plasmon resonance peak of the embedded AuNPs progressively red-shifts with cluster size, likely due to an increase in particle–particle contacts. We exploit this fine control over size to homogeneously load precise amounts of the dye Nile Red and the antibiotic Tetracycline into clusters of different hydrodynamic diameters and deliver cargos near-quantitatively by deconstructing the aggregates below the ELP transition temperature. Beyond establishing a key role for free ELPs in the agglomeration of ELP-functionalized particles, our results provide a path for the thermally controlled delivery of precise quantities of molecular cargo. This capability might prove useful in combination photothermal therapies and theranostic applications, and to trigger spatially and temporally uniform responses from biological, electronic, or optical systems.

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Neural Network for Principle of Least Action

The principle of least action is the cornerstone of classical mechanics, theory of relativity, quantum mechanics, and thermodynamics. Here, we describe how a neural network (NN) learns to find the trajectory for a Lennard-Jones (LJ) system that maintains balance in minimizing the Onsager–Machlup (OM) action and maintaining the energy conservation. The phase-space trajectory thus calculated is in excellent agreement with the corresponding results from the “ground-truth” molecular dynamics (MD) simulation. Furthermore, we show that the NN can easily find structural transformation pathways for LJ clusters, for example, the basin-hopping transformation of an LJ 38 from an incomplete Mackay icosahedron to a truncated face-centered cubic octahedron. Unlike MD, the NN computes atomic trajectories over the entire temporal domain in one fell swoop, and the NN time step is a factor of 20 larger than the MD time step. The NN approach to OM action is quite general and can be adapted to model morphometrics in a variety of applications.

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Critical Role of the Interfacial Layer in Associating Polymers with Microphase Separation

Polymers with dynamic (transient) bonds, often called associating polymers, have been attracting significant attention in recent years due to their unique viscoelastic properties, self-healing ability, and recyclability. Nevertheless, understanding the mechanisms and the factors controlling their macroscopic properties remains limited due to the higher complexity introduced by the dynamic bonds. Here in this study, small-angle X-ray scattering (SAXS), broadband dielectric spectroscopy (BDS), and rheology were applied to unravel the structure and dynamics of telechelic associating polymers with different molecular weights. SAXS measurements revealed phase separation of the functional end groups with an average cluster size of ~2–3 nm and the distance between clusters controlled by the chain length. Borrowing the interfacial layer model analysis of BDS data from the polymer nanocomposite field, we demonstrated the presence of an interfacial polymer layer with a thickness of ~0.7–0.9 nm surrounding these clusters. Rheological measurements showed quantitatively that the presence of the interfacial layer significantly alters the viscoelastic behavior of these materials, indicating the crucial role of the interfacial layer in defining the macroscopic mechanical properties of the studied telechelic materials. The presented results emphasize that phase separation of the functional groups in associating polymers leads to very significant changes of the viscoelastic properties, opening a promising avenue in the design of novel functional materials.

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Morphology–Diffusivity Relationships in Fluorine-Free Random Terpolymers for Proton-Exchange Membranes

Here, using atomistic molecular dynamics simulations, we investigate the morphology and transport properties of a new family of fluorine-free terpolymers designed as proton-exchange membranes. Simulated random terpolymers consist of three monomers with a 5-carbon backbone with a phenylsulfonate, phenyl, or no pendant group and have ion exchange capacities (IECs) ranging from 1.06–4.14 mmol/g. At a hydration level of 9, cluster analysis reveals macrophase separation between water and terpolymers with IEC < 2.1 mmol/g and continuous, percolated hydrophilic and hydrophobic nanoscale domains at higher IECs. Channel width distribution analysis of the percolated morphologies revealed that more hydrophobic units produce less uniform channels. Decreasing the surface area per sulfonate group and increasing the fractal dimension of the hydrophilic domains correlate with increased water diffusivity, due to a more acidic interface and more isotropic water channels. Relative to the previously studied phenylsulfonate homopolymer, these terpolymers with lower IECs have only modestly lower water diffusion, and we anticipate other advantages related to processability.

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Understanding Metal–Organic Framework Nucleation from a Solution with Evolving Graphs

A mechanistic understanding of metal–organic framework (MOF) synthesis and scale-up remains underexplored due to the complex nature of the interactions of their building blocks. In this work, we investigate the collective assembly of building units at the early stages of MOF nucleation, using MIL-101(Cr) as a prototypical example. Using large-scale molecular dynamics simulations, we observe that the choice of solvent (water and N,N-dimethylformamide), the introduction of ions (Na+ and F–) and the relative populations of MIL-101(Cr) half-secondary building unit (half-SBU) isomers have a strong influence on the cluster formation process. Additionally, the shape, size, nucleation and growth rates, crystallinity, and short and long-range order largely vary depending on the synthesis conditions. We evaluate these properties as they naturally emerge when interpreting the self-assembly of MOF nuclei as the time evolution of an undirected graph. Solution-induced conformational complexity and ionic concentration have a dramatic effect on the morphology of clusters emerging during assembly. While pure solvents lead to the rapid formation of a small number of large clusters, the presence of ions in aqueous solutions results in smaller clusters and slower nucleation. This diversity is captured by the key features of the graph representation. Principle component analysis on graph properties reveals that only a small number of molecular descriptors is needed to deconvolute MOF self-assembly. Furthermore, descriptors such as the average coordination number between half-SBUs and fractal dimension are of particular interest as they can be can be followed experimentally by techniques like by time-resolved spectroscopy. Ultimately, graph theory emerges as an approach that can be used to understand complex processes revealing molecular descriptors accessible by both simulation and experiment.

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Vibrational signatures of HNO 3 acidity when complexed with microhydrated alkali metal ions, M + ∙(HNO 3 )(H 2 O) n =5 (M = Li, K, Na, Rb, Cs), at 20 K

The speciation of strong acids like HNO 3 under conditions of restricted hydration is an important factor in the rates of chemical reactions at the air-water interface. Here we explore the trade-offs in play when HNO 3 is attached to alkali ions (Li + -Cs + ) with four water molecules in their primary hydration shells. This is achieved by analyzing the vibrational spectra of the M + ∙(HNO 3 )(H 2 O) 5 clusters cooled to about 20 K in a cryogenic photofragmentation mass spectrometer. The local acidity of the acidic OH group is estimated by the extent of the red shift in its stretching frequency when attached to a single water molecule. Here, the persistence of this local structural motif (HNO 3 -H 2 O) in all of these alkali metal clusters enables us to determine the competition between the effect of the direct complexation of the acid with the cation, which acts to enhance acidity, and the role of the water network in the first hydration shell around the ions, which acts to counter (screen) the intrinsic effect of the ion. Analysis of the vibrational features associated with the acid molecule as well as those of the water network reveal how cooperative interactions in the micro hydration regime conspire to effectively offset the intrinsic enhancement of HNO 3 acidity afforded by attachment to the smaller cations.

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Reactivity, Mechanism, and Assembly of the Alternative Nitrogenases

Biological nitrogen fixation is catalyzed by the enzyme nitrogenase, which facilitates the cleavage of the relatively inert triple bond of N 2 . Nitrogenase is most commonly associated with the molybdenum–iron cofactor called FeMoco or the M-cluster, and it has been the subject of extensive structural and spectroscopic characterization over the past 60 years. In the late 1980s and early 1990s, two “alternative nitrogenase” systems were discovered, isolated, and found to incorporate V or Fe in place of Mo. These systems are regulated by separate gene clusters; however, there is a high degree of structural and functional similarity between each nitrogenase. Limited studies with the V- and Fe-nitrogenases initially demonstrated that these enzymes were analogously active as the Mo-nitrogenase, but more recent investigations have found capabilities that are unique to the alternative systems. In this review, we will discuss the reactivity, biosynthetic, and mechanistic proposals for the alternative nitrogenases as well as their electronic and structural properties in comparison to the well-characterized Mo-dependent system. Studies over the past 10 years have been particularly fruitful, though key aspects about V- and Fe-nitrogenases remain unexplored.

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Ultra-fast Proton Conduction and Photocatalytic Water Splitting in a Pillared Metal–Organic Framework

Proton-exchange membrane fuel cells enable the portable utilization of hydrogen (H 2 ) as an energy resource. Current electrolytic materials have limitation, and there is an urgent need to develop new materials showing especially high proton conductivity. Here, we report the ultra-fast proton conduction in a novel metal–organic framework, MFM-808, which adopts an unprecedented topology and a unique structure consisting of two-dimensional layers of {Zr 6 }-clusters. By replacing the bridging formate with sulfate ligands within {Zr 6 }-layers, the modified MFM-808-SO 4 exhibits an exceptional proton conductivity of 0.21 S·cm –1 at 85 °C and 99% relative humidity. Modeling by molecular dynamics confirms that proton transfer is promoted by an efficient two-dimensional conducting network assembled by sulfate–{Zr 6 }-layers. MFM-808-SO 4 also possesses excellent photocatalytic activity for water splitting to produce H 2 , paving a new pathway to achieve a renewable hydrogen-energy cycle.

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Folding Coarse-Grained Oligomer Models with PyRosetta

Non-biological foldamers are a promising class of macromolecules that share similarities to classical biopolymers such as proteins and nucleic acids. Currently, designing novel foldamers is a non-trivial process, often involving many iterations of trial synthesis and characterization until folded structures are observed. In this work, we aim to tackle these foldamer design challenges using computational modeling techniques. We developed CG PyRosetta, an extension to the popular protein folding python package, PyRosetta, which introduces coarse-grained (CG) residues into PyRosetta, enabling the folding of toy CG foldamer models. Although these models are simplified, they can help explore overarching physical hypotheses about how oligomers can form. Through systematic variation of CG parameters in these models, we can investigate various folding hypotheses at the CG scale to inform the design process of new foldamer chemistries. In this study, we demonstrate CG PyRosetta’s ability to identify minimum energy structures with a diverse structural search over a range of simple models, as well as two hypothesis-driven parameter scans investigating the effects of side-chain size and internal backbone angle on secondary structures. We are able to identify several types of secondary structures from single- and double-helices to sheet-like and knot-like structures. Here, we show how side-chain size and backbone bond angle both play an important role in the structure and energetics of these toy models. Optimal side-chain sizes promote favorable packing of side chains, while specific backbone bond angles influence the specific helix type found in folded structures.

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High-Resolution XFEL Structure of the Soluble Methane Monooxygenase Hydroxylase Complex with its Regulatory Component at Ambient Temperature in Two Oxidation States

Soluble methane monooxygenase (sMMO) is a multicomponent metalloenzyme that catalyzes the conversion of methane to methanol at ambient temperature using a nonheme, oxygen-bridged dinuclear iron cluster in the active site. Structural changes in the hydroxylase component (sMMOH) containing the diiron cluster caused by complex formation with a regulatory component (MMOB) and by iron reduction are important for the regulation of O 2 activation and substrate hydroxylation. Structural studies of metalloenzymes using traditional synchrotron-based X-ray crystallography are often complicated by partial X-ray-induced photoreduction of the metal center, thereby obviating determination of the structure of the enzyme in pure oxidation states. Here, microcrystals of the sMMOH:MMOB complex from Methylosinus trichosporium OB3b were serially exposed to X-ray free electron laser (XFEL) pulses, where the ≤35 fs duration of exposure of an individual crystal yields diffraction data before photoreduction-induced structural changes can manifest. Merging diffraction patterns obtained from thousands of crystals generates radiation damage-free, 1.95 Å resolution crystal structures for the fully oxidized and fully reduced states of the sMMOH:MMOB complex for the first time. The results provide new insight into the manner by which the diiron cluster and the active site environment are reorganized by the regulatory protein component in order to enhance the steps of oxygen activation and methane oxidation. Furthermore, this study also emphasizes the value of XFEL and serial femtosecond crystallography (SFX) methods for investigating the structures of metalloenzymes with radiation sensitive metal active sites.

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Unveiling the Role of Surface Ir-Oxo Species in O 2 Evolution at IrO 2 Electrocatalysts via Embedded Cluster Multireference Calculations

Understanding the mechanisms driving the oxygen evolution reaction (OER) on iridium oxide (IrO 2 )-based catalysts is essential to improving their performance and enabling an actual scale-up of water-splitting photoelectrochemical cells. The mechanistic pathways at IrO 2 interfaces have been extensively investigated computationally using density functional theory (DFT), which predicts a high-energy barrier for the last step of the OER of molecular oxygen detachment and release from the catalyst surface. Nevertheless, surface O 2 over- and under-binding results by standard generalized gradient approximation and hybrid density functionals, respectively, call for further analysis of this crucial step via multireference methods. Aiming at unveiling the nature of such a barrier, we hereby address the formation of O 2 from the most-stable IrO 2 (110) surface with both periodic DFT and an electrostatic embedded cluster approach at the n-electron valence-state perturbation theory. With this multireference approach, we find a value for the aforementioned energy barrier that is much closer to experimental indications than DFT ones. Here, an in-depth analysis of the involved molecular orbitals suggests that the origin of this barrier is related to the breaking of a π interaction between O 2 and Ir surface atom and to a significant additional O 2 interaction with adjacent electrophilic Ir-oxo species, which is present under experimental operating conditions. Besides shedding light on the mechanism of the OER on IrO 2 , these findings point out the importance of multireference methods for dissecting complex reactions at electrocatalytic interfaces and pave the route for further investigations with effective embedding approaches.

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Mixed Valence {Ni 2+ Ni 1+ } Clusters as Models of Acetyl Coenzyme A Synthase Intermediates

Acetyl coenzyme A synthase (ACS) catalyzes the formation and deconstruction of the key biological metabolite, acetyl coenzyme A (acetyl-CoA). The active site of ACS features a {NiNi} cluster bridged to a [Fe4S4] n+ cubane known as the A-cluster. The mechanism by which the A-cluster functions is debated, with few model complexes able to replicate the oxidation states, coordination features, or reactivity proposed in the catalytic cycle. In this work, we isolate the first bimetallic models of two hypothesized intermediates on the paramagnetic pathway of the ACS function. The heteroligated {Ni 2+ Ni 1+ } cluster, [K(12-crown-4) 2 ][1], effectively replicates the coordination number and oxidation state of the proposed “A red ” state of the A-cluster. Addition of carbon monoxide to [1] - allows for isolation of a dinuclear {Ni 2+ Ni 1+ (CO)} complex, [K(12-crown-2) n ][2] (n = 1–2), which bears similarity to the “A NiFeC ” enzyme intermediate. Structural and electronic properties of each cluster are elucidated by X-ray diffraction, nuclear magnetic resonance, cyclic voltammetry, and UV/vis and electron paramagnetic resonance spectroscopies, which are supplemented by density functional theory (DFT) calculations. Calculations indicate that the pseudo-T-shaped geometry of the three-coordinate nickel in [1] – is more stable than the Y-conformation by 22 kcal mol –1 , and that binding of CO to Ni 1+ is barrierless and exergonic by 6 kcal mol –1 . UV/vis absorption spectroscopy on [2] - in conjunction with time-dependent DFT calculations indicates that the square-planar nickel site is involved in electron transfer to the CO π*-orbital. Further, we demonstrate that [2] - promotes thioester synthesis in a reaction analogous to the production of acetyl coenzyme A by ACS.

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Gating Single Molecules with Counterions

We report atomic-scale gating and visualization of local charge distribution within individual rare-earth-based molecular complexes on a metallic surface. The complexes are formed by a positively charged lanthanum ion coordinated to a (pcam)3 molecule and a negatively charged counterion trapped underneath via electrostatic interactions on a Au(111) surface. Local gating is performed by adding an additional negatively charged counterion to one side of the complex, which results in the redistribution of charges within the complex and a positive shift of the frontier orbitals. This is caused by the internal Stark effect induced by the added counterion. This effect is directly captured using tunneling spectroscopy and spectroscopic mapping at 5 K substrate temperature. The polarizability of the complex is corroborated by density functional theory and analytical calculations based on experimental findings. Furthermore, the influence of charge polarization on nearby complexes is investigated in a cluster purposely assembled using three complexes, which reveals maintaining the charge states as in single complexes. These findings will enable the design of robust charged rare-earth complexes to be tailored for potential solid-state applications.

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