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At least 523 records · Page 29

CO 2 Capture Characteristics of Hyperbranched Poly(alkylene imine): A Molecular Dynamics Simulation Approach

This study explores the CO 2 capture characteristics of hyperbranched poly(ethylenimine) (HB-PEI) and poly- (propyleneimine) (HB-PPI) through molecular dynamics simulations using density functional theory-calibrated force fields. Key features such as density, free volume, glass transition temperature, CO 2 /H 2 O distribution, and molecular diffusion are systematically investigated to elucidate structure−function relationships under dry and hydrated conditions. HB-PEI demonstrates a slightly higher density and lower free volume compared to HB-PPI yet shows superior CO 2 capture due to the high amine concentration. Glass transition analysis indicates a higher thermal mobility in HBPEI, enhancing the CO 2 diffusivity. Pair correlation and coordination analyses confirm a stronger affinity of CO 2 with primary and secondary amines, particularly in hydrated environments where water competes with CO 2 for binding sites. Despite its more compact structure, HB-PEI outperformed HB-PPI in CO 2 and H 2 O transport, as confirmed by higher diffusion coefficients across all hydration levels. These findings highlight a critical balance among polymer architecture, amine accessibility, and hydration in designing next-generation solid amine sorbents for efficient direct air capture applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-thermal structural transformation of diamond driven by x-rays

Intense x-ray pulses can cause the non-thermal structural transformation of diamond. At the SACLA XFEL facility, pump x-ray pulses triggered this phase transition, and probe x-ray pulses produced diffraction patterns. Time delays were observed from 0 to 250 fs, and the x-ray dose varied from 0.9 to 8.0 eV/atom. The intensity of the (111), (220), and (311) diffraction peaks decreased with time, indicating a disordering of the crystal lattice. From a Debye–Waller analysis, the rms atomic displacements perpendicular to the (111) planes were observed to be significantly larger than those perpendicular to the (220) or (311) planes. At a long time delay of 33 ms, graphite (002) diffraction indicates that graphitization did occur above a threshold dose of 1.2 eV/atom. These experimental results are in qualitative agreement with XTANT+ simulations using a hybrid model based on density-functional tight-binding molecular dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Catalytic Triad-Inspired Nanozyme Catalysts for Ester Hydrolysis in Organic Solvent Mixtures

We synthesized a series of molecular nanozyme catalysts containing functional groups (imidazole, carboxylic acid, and hydroxyl groups) inspired by the catalytic triad found in natural serine hydrolases. Different structural features were incorporated using two distinct synthesis routes to investigate the influence of interactions beyond the active site on catalytic activity in designing molecular nanozymes. Molecular dynamics simulations suggest that nanozyme activity is affected by structural features that influence nanozyme hydrophilicity and the organization of the local solvent environment. The most active nanozyme showed activity comparable to the enzyme α-chymotrypsin for the hydrolysis of a model ester (4-nitrophenyl 4- hydroxybenzoate) in a 95:5 (v/v%) water/acetonitrile mixture at ambient temperature. Increasing the temperature and organic solvent content decreases the activity of α-chymotrypsin while enhancing the activity of the nanozymes. The nanozymes can be immobilized on supported metal nanoparticles using a dithiol self-assembled monolayer, which facilitates their removal from the postreaction solution. These results demonstrate the potential in creating solvent-tolerant bioinspired catalysts, thereby combining the advantages of biocatalysts and chemical catalysts as next-generation industrial catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First-principles study of an S = 1 quasi one-dimensional quantum molecular magnetic material

We use density functional theory to study the structural, magnetic, and electronic structures of the organometallic quantum magnet NiCl 2-4 SC (NH 2 ) 2 (DTN). Recent work has demonstrated the quasi one-dimensional nature of the molecular crystal and studied its quantum phase transitions at low temperatures. The system includes a magnetoelectric (ME) coupling and, when doped with Br, the presence of an exotic Bose-glass state. Using the generalized gradient approximation with inclusion of a van der Waals term to account for weak intermolecular forces and by introducing a Hubbard U term to the total energy, we systematically show that our calculations reproduce the magnetic anisotropy, the intermolecular exchange coupling strength, and the magnetoelectric effect in DTN, which have been observed in previous experiments. Further analysis of the electronic structure gives insight into the underlying magnetic interactions, including what mechanisms may be causing the ME effect. Using this computationally efficient model, we predict what effect applying an electric field might have on the magnetic properties of this quantum magnet.

1-dimensional spin chains↗

General contraction of Gaussian basis sets. II - Atomic natural orbitals and the calculation of atomic and molecular properties

A recently proposed scheme for using natural orbitals from atomic configuration interaction wave functions as a basis set for linear combination of atomic orbitals (LCAO) calculations is extended for the calculation of molecular properties. For one-electron properties like multipole moments, which are determined largely by the outermost regions of the molecular wave function, it is necessary to increase the flexibility of the basis in these regions. This is most easily done by uncontracting the outermost Gaussian primitives, and/or by adding diffuse primitives. A similar approach can be employed for the calculation of polarizabilities. Properties which are not dominated by the long-range part of the wave function, such as spectroscopic constants or electric field gradients at the nucleus, can generally be treated satisfactorily with the original atomic natural orbital sets.

Almlof, Jan↗

Crystal structures of an E1–E2–ubiquitin thioester mimetic reveal molecular mechanisms of transthioesterification

E1 enzymes function as gatekeepers of ubiquitin (Ub) signaling by catalyzing activation and transfer of Ub to tens of cognate E2 conjugating enzymes in a process called E1–E2 transthioesterification. The molecular mechanisms of transthioesterification and the overall architecture of the E1–E2–Ub complex during catalysis are unknown. Here, we determine the structure of a covalently trapped E1–E2–ubiquitin thioester mimetic. Two distinct architectures of the complex are observed, one in which the Ub thioester (Ub(t)) contacts E1 in an open conformation and another in which Ub(t) instead contacts E2 in a drastically different, closed conformation. Altogether our structural and biochemical data suggest that these two conformational states represent snapshots of the E1–E2–Ub complex pre- and post-thioester transfer, and are consistent with a model in which catalysis is enhanced by a Ub(t)-mediated affinity switch that drives the reaction forward by promoting productive complex formation or product release depending on the conformational state.

59 BASIC BIOLOGICAL SCIENCES↗

Functionalizing aromatic compounds with optical cycling centres

Molecular design principles provide guidelines for augmenting a molecule with a smaller group of atoms to realize a desired property or function. Here, we demonstrate that these concepts can be used to create an optical cycling centre, the Ca(I)–O unit, that can be attached to a number of aromatic ligands, enabling the scattering of many photons from the resulting molecules without changing the molecular vibrational state. Such capability plays a central role in quantum state preparation and measurement, as well as laser cooling and trapping, and is therefore a prerequisite for many quantum science and technology applications. We provide further molecular design principles that indicate the ability to optimize and expand this work to an even broader class of molecules. This represents a great step towards a quantum functional group, which may serve as a generic qubit moiety that can be attached to a wide range of molecular structures and surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Proteins associated with the Arabidopsis thaliana plastid rhomboid-like protein RBL10

Rhomboid-like proteins are intramembrane proteases with a variety of regulatory roles in cells. Though many rhomboid-like proteins are predicted in plants, their detailed molecular mechanisms or cellular functions are not yet known. Of the 13 predicted rhomboids in Arabidopsis thaliana, one, RBL10, affects lipid metabolism in the chloroplast, because in the respective rbl10 mutant the transfer of phosphatidic acid through the inner envelope membrane is disrupted. Here we show that RBL10 is part of a high-molecular-weight complex of 250 kDa or greater in size. Nine likely components of this complex are identified by two independent methods and include Acyl Carrier Protein 4 (ACP4) and Carboxyltransferase Interactor1 (CTI1), which have known roles in chloroplast lipid metabolism. The acp4 mutant has decreased C16:3 fatty acid content of monogalactosyldiacylglycerol, similar to the rbl10 mutant, prompting us to offer a mechanistic model of how an interaction between ACP4 and RBL10 might affect chloroplast lipid assembly. We also demonstrate the presence of a seventh transmembrane domain in RBL10, refining the currently accepted topology of this protein. Taken together, the identity of possible RBL10 complex components as well as insights into RBL10 topology and distribution in the membrane provide a stepping-stone towards a deeper understanding of RBL10 function in Arabidopsis lipid metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

A partially disordered region connects gene repression and activation functions of EZH2

Enhancer of Zeste Homolog 2 (EZH2) is the catalytic subunit of Polycomb Repressive Complex 2 (PRC2), which minimally requires two other subunits, EED and SUZ12, for enzymatic activity. EZH2 has been traditionally known to mediate histone H3K27 trimethylation, a hallmark of silent chromatin. Emerging evidence indicates that EZH2 also activates gene expression in cancer cells in a context distinct from canonical PRC2. The molecular mechanism underlying the functional conversion of EZH2 from a gene repressor to an activator is unclear. In this work, we show that EZH2 harbors a hidden, partially disordered transactivation domain (TAD) capable of interacting with components of active transcription machinery, mimicking archetypal acidic activators. The EZH2 TAD comprises the SRM (Stimulation-Responsive Motif) and SANT1 (SWI3, ADA2, N-CoR, and TFIIIB 1) regions that are normally involved in H3K27 methylation. The crystal structure of an EZH2–EED binary complex indicates that the EZH2 TAD mediates protein oligomerization in a noncanonical PRC2 context and is entirely sequestered. The EZH2 TAD can be unlocked by cancer-specific EZH2 phosphorylation events to undergo structural transitions that may enable subsequent transcriptional coactivator binding. The EZH2 TAD directly interacts with the transcriptional coactivator and histone acetyltransferase p300 and activates gene expression in a p300-dependent manner in cells. The corresponding TAD may also account for the gene activation function of EZH1, the paralog of EZH2. Distinct kinase signaling pathways that are known to abnormally convert EZH2 into a gene activator in cancer cells can now be understood in a common structural context of the EZH2 TAD.

59 BASIC BIOLOGICAL SCIENCES↗

Exact constraints and appropriate norms in machine-learned exchange-correlation functionals

Machine learning techniques have received growing attention as an alternative strategy for developing general-purpose density functional approximations, augmenting the historically successful approach of human-designed functionals derived to obey mathematical constraints known for the exact exchange-correlation functional. More recently, efforts have been made to reconcile the two techniques, integrating machine learning and exact-constraint satisfaction. We continue this integrated approach, designing a deep neural network that exploits the exact constraint and appropriate norm philosophy to de-orbitalize the strongly constrained and appropriately normed (SCAN) functional. The deep neural network is trained to replicate the SCAN functional from only electron density and local derivative information, avoiding the use of the orbital-dependent kinetic energy density. The performance and transferability of the machine-learned functional are demonstrated for molecular and periodic systems.

Artificial neural networks↗

High temperature stability and transport characteristics of hydrogen in alumina via multiscale computation

Here, the impact of hydrogen charge states on the stability and transport characteristics of hydrogen interstitials in alumina polymorphs is evaluated by multiscale computational methods including density functional theory (DFT), ab initio molecular dynamics (AIMD) and machine learned force fields. Thermodynamic calculations show that the protonic H i +1 interstitial is the most stable defect species for most values of the electronic bandgap in both and amorphous alumina (Al 2 O 3 ). Further, active learned Gaussian approximation potentials (GAP) were developed using AIMD data to study temperature dependent long time proton diffusion in alumina. Diffusivity calculations from GAP-MD simulations are found to be comparable with of the AIMD data, while being ~340 times faster and scalable to larger systems. Comparisons with diffusivity values for other interstitial charge states (H i 0 and H i -1 ) and published experimental literature indicate that H i +1 diffusion is the likely mechanism of hydrogen transport. A good agreement is obtained between H i +1 diffusivity calculated in α-Al 2 O 3 from DFT: 5.05 10 -3 exp(-0.81 eV/k B /T) cm 2 /s and reported experiment: 9.7X10 -4 exp(-0.83 eV/k B /T) cm 2 /s. Computationally and experimentally calculated energy barriers (0.81 and 0.83 eV respectively) only differ by 2.5%. Similarly, the pre-exponential diffusion coefficients only differ by 0.5 orders of magnitude. Moreover, the diffusivity of H i +1 in amorphous Al 2 O 3 in the 1000–2000 K range is calculated to be 2.53X10 -2 exp(-0.89 eV/k B /T), just one order of magnitude higher than the corresponding value in α-Al 2 O 3 . This suggests that local structural disorder does not significantly affect the energy landscape and diffusion behavior of H i +1 in Al 2 O 3 . Overall, these results show promise for the application of alumina polymorphs as hydrogen permeation barriers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Energy conversion and transport in molecular-scale junctions

Molecular-scale junctions (MSJs) have been considered the ideal testbed for probing physical and chemical processes at the molecular scale. Due to nanometric confinement, charge and energy transport in MSJs are governed by quantum mechanically dictated energy profiles, which can be tuned chemically or physically with atomic precision, offering rich possibilities beyond conventional semiconductor devices. While charge transport in MSJs has been extensively studied over the past two decades, understanding energy conversion and transport in MSJs has only become experimentally attainable in recent years. As demonstrated recently, by tuning the quantum interplay between the electrodes, the molecular core, and the contact interfaces, energy processes can be manipulated to achieve desired functionalities, opening new avenues for molecular electronics, energy harvesting, and sensing applications. This Review provides a comprehensive overview and critical analysis of various forms of energy conversion and transport processes in MSJs and their associated applications. We elaborate on energy-related processes mediated by the interaction between the core molecular structure in MSJs and different external stimuli, such as light, heat, electric field, magnetic field, force, and other environmental cues. Key topics covered include photovoltaics, electroluminescence, thermoelectricity, heat conduction, catalysis, spin-mediated phenomena, and vibrational effects. Furthermore, the review concludes with a discussion of existing challenges and future opportunities, aiming to facilitate in-depth future investigation of promising experimental platforms, molecular design principles, control strategies, and new application scenarios.

Charge transport↗

Antimony stable isotope fractionation during adsorption onto birnessite: A molecular perspective from X-ray absorption spectroscopy and density functional theory

Sorption of antimony (Sb) onto birnessite significantly influences the fate of Sb in oceanic and terrestrial environments and fractionates Sb isotopes. Nevertheless, little is known about Sb isotopic fractionation during its adsorption on birnessite. Here, in this study, we show the value of Δ 123 Sb adsorbed-aqueous increases from −0.398 to −0.332 ‰ in 1 h and then decreases and stabilizes at −0.384 ‰ in 72 h. The enrichment of the light Sb isotope is predominantly due to the distortion of the octahedral symmetry. X-ray absorption spectroscopy results indicate Sb first forms a double-corner-sharing complex on birnessite and then transforms to a double-edge-sharing complex during adsorption. The optimized bond distances for double-corner-sharing (3.37 Å) and double-edge-sharing (2.90 Å) complexes calculated using density functional theory (DFT) fits well with the structure (3.41 and 3.00 Å) revealed by X-ray absorption spectroscopy, respectively. The fractionation derived from reduced partition function ratios calculated using DFT aligns well with the experimental results. Therefore, the variation in Sb isotopic fractionation during adsorption is attributed to the evolving structure of Sb complexes on birnessite. Our results demonstrate the isotopic fractionation of Sb during adsorption on birnessite and provide a molecular-scale understanding of Sb behavior, contributing to the correct reconstruction of the Sb isotope composition of ancient seawater using ferromanganese crusts and nodules, and efforts to trace Sb migration in epigenetic mining environments.

Adsorption↗

Computational insights into the interaction of water with the UiO-66 metal–organic framework and its functionalized derivatives

The UiO-66 metal–organic framework (MOF) has been identified as a promising hydrophilic material for water harvesting. Recent studies show that its water uptake ability at low relative humidity (RH) can be improved by incorporating hydrophilic functional groups into the framework. In this work, 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. We started by developing molecular models for UiO-66, UiO-66-NH 2 , UiO-66-OH, and UiO-66-(OH) 2 compatible with the MB-pol data-driven many-body potential of water. We then benchmarked these models against ab initio data. Here we used these models to perform molecular dynamics simulations and calculate radial distribution functions, IR spectra, and two-dimensional density distribution maps for water in the MOFs. These results consistently show that the μ 3 -OH sites are the preferential interaction sites for water in UiO-66 and all its variants, and the formation of localised water clusters inside the octahedral pores is responsible for the abrupt step in the experimental adsorption isotherms. Furthermore, the presence of functional groups in the framework allows water to cluster in the octahedral pores at lower RH, thus making the MOF a more efficient water harvester. Overall, this study provides molecular-level insights into the pore filling process of UiO-66 and its functionalized derivatives, which are needed for the design of efficient water harvesting materials based on MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BETO 2021 Peer Review - Inverse Bioproduct Design Through Machine Learning and Molecular Simulation

This work aims to identify performance advantaged bioproducts (PABPs) through property prediction, which will guide experimental synthesis. The impact of this work will be faster market adoption of bioproducts with greater performance relative to incumbent products. We have identified >106 bioproduct candidates, but only some will have superior performance to create a market pull. High-throughput property prediction, enabled by machine learning, and elucidation of structure-function relationships, enabled by molecular simulation, provide a hypothesis driven approach for down selection of candidate biomolecules to pursue experimentally. To enable machine learning and molecular simulation for bioproduct discovery, automated structure generation and embedding must capture relevant features for prediction, databases must cover domains applicable to biobased products, and best practices for simulation of polymer systems must be developed. To address these challenges, we have established bioproduct relevant datasets, developed high-throughput polymer structure generation, and built end-to-end neural networks that have predicted 8 properties for >1.4 x 106 biopolymers. A molecular simulation pipeline for building, running, and analyzing polymers and polymer additives is being used to predict performance and develop design principles of biobased products. In collaboration with the PABP synthesis project, these computational tools are guiding synthesis and informing design of PABPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Molecular Recognition at Mineral Interfaces: Implications for the Beneficiation of Rare Earth Ores

Ce-bastnäsite is the single largest mineral source for light rare-earth elements. In view of the growing industrial importance of rare-earth minerals, it is critical to develop more efficient methods for separating the valuable rare-earth-containing minerals from the surrounding gangue. In this work, we employ a combination of periodic density functional theory (DFT) and molecular mechanics (MM) calculations together with the de novo molecular design program HostDesigner to identify bis-phosphinate ligands that preferentially bind to the (100) Ce-bastnäsite surface rather than the (104) calcite surface. DFT calculations for a simple phosphinate ligand were employed to qualitatively understand key behaviors involved in ligand–metal, ligand–solvent, and solvent–metal interactions. These insights were then used to guide the search for flexible, rigid, and semirigid hydrocarbon linkers to identify candidate bis-phosphinate ligands with the potential to bind preferentially to Ce-bastnäsite. Among the five most promising bis-phosphinate ligands suggested by theoretical studies, three ligands were synthesized and their adsorption characteristics to bastnäsite (100) interfaces were characterized using vibrational sum-frequency (vSFG) spectroscopy, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, and isothermal titration calorimetry (ITC). The efficacy of the selective interfacial molecular binding was demonstrated by identifying a bis-phosphinate ligand capable of providing an overall higher surface coverage of alkyl groups relative to a monophosphinate ligand. The results highlight the interplay between adsorption binding strength and maximum surface coverage in determining ligand efficiency to render the mineral surface hydrophobic. DFT calculations further indicate that all tested ligands have higher affinity for Ce-bastnäsite than for calcite. Finally, this is consistent with the ITC data showing stronger adsorption enthalpy to bastnäsite than to calcite, making these ligands promising candidates for selective flotation of Ce-bastnäsite.

58 GEOSCIENCES↗

Atomistic insights into the synergistic effects of tensile strain and hydroxyl group on increasing the thermal conductivity of monohydric alcohols as latent heat storage materials

The low thermal conductivity of linear monohydric alcohols significantly limits their performance when used as latent heat storage materials. It was found that imposing certain mechanical strains on nanomaterials with highly ordered structures can lead to appreciable thermal conductivity enhancement. To explore the potential of enhancing the intrinsic thermal conductivity of monohydric alcohols, a simplified ideal crystal model was employed for molecular arrangement in this work. The variation of atomistic heat transfer as a function of tensile strains was exploited by non-equilibrium molecular dynamics simulations. Furthermore, the influence of stretching on the vibration density of states and the corresponding molecular morphology were revealed. The results suggested that the thermal conductivity of monohydric alcohols with such simplified ideal crystalline structures can increase by about 170 % at the strain of 0.1. The distance between neighboring interfaces was found to determine the energy of inter-molecular interactions at the crystal grain boundaries. The hydrogen bonds energy has not reached the critical value when increasing tensile strains from 0 to 0.1. In contrast, the strongest van der Walls interactions for alkanes were obtained at the strain of 0.06 where the interfacial distances of alkanes have achieved their equilibrium distances. In addition, the interfacial heat transfer coefficient of ideal crystal monohydric alcohols at hydroxyl interfaces was found to be threefold than that between methyl interfaces, in consistent with the strength of inter-molecular interactions between functional groups at the interfaces.

36 MATERIALS SCIENCE↗

Decomposition decreases molecular diversity and ecosystem similarity of soil organic matter

Soil organic matter (SOM) is comprised of a diverse array of reactive carbon molecules, including hydrophilic and hydrophobic compounds, that impact rates of SOM formation and persistence. Despite clear importance to ecosystem science, little is known about broad-scale controls on SOM diversity and variability in soil. Here, we show that microbial decomposition drives significant variability in the molecular richness and diversity of SOM between soil horizons and across a continental-scale gradient in climate and ecosystem type (arid shrubs, coniferous, deciduous, and mixed forests, grasslands, and tundra sedges). The molecular dissimilarity of SOM was strongly influenced by ecosystem type (hydrophilic compounds: 17%, P < 0.001; hydrophobic compounds: 10% P < 0.001) and soil horizon (hydrophilic compounds: 17%, P < 0.001; hydrophobic compounds: 21%, P < 0.001), as assessed using metabolomic analysis of hydrophilic and hydrophobic metabolites. While the proportion of shared molecular features was significantly higher in the litter layer than subsoil C horizons across ecosystems (12 times and 4 times higher for hydrophilic and hydrophobic compounds, respectively), the proportion of site-specific molecular features nearly doubled from the litter layer to the subsoil horizon, suggesting greater differentiation of compounds after microbial decomposition within each ecosystem. Together, these results suggest that microbial decomposition of plant litter leads to a decrease in SOM α-molecular diversity, yet an increase in β-molecular diversity across ecosystems. The degree of microbial degradation, determined by the position in the soil profile, exerts a greater control on SOM molecular diversity than environmental factors, such as soil texture, moisture, and ecosystem type.

59 BASIC BIOLOGICAL SCIENCES↗