Quantum Mechanical Calculations Research Articles

Subnanoscale Ion Beam Modification-Assisted Smoothing of Heterostructure Surfaces.

Glass ceramic (GC) is the most promising material for objective lenses for extreme ultraviolet lithography that must meet the subnanometer precision, which is characterized by low values of high spatial frequency surface roughness (HSFR). However, the HSFR of GC is typically degraded during ion beam figuring (IBF). Herein, a developed method for constructing molecular dynamics (MD) models of GC was presented, and the formation mechanisms of surface morphologies were investigated. The results indicated that the generation of the dot-like microstructure was the result of the difference in the erosion rate caused by the difference in the intrinsic properties between ceramic phases (CPs) and glass phases (GPs). Further, the difference in the microstructure of the IBF surface under different beam angles was mainly caused by the difference in the two types of sputtering. Quantum mechanical calculations showed that the presence of interstitial atoms would result in electron rearrangement and that the electron localization can lead to a reduction in CP stability. To obtain a homogeneous surface, the effects of beam parameters on the heterogeneous surface were systematically investigated based on the proposed MD model. Then, a novel ion beam modification (IBM) method was proposed and demonstrated by TEM and GIXRD. The range of ion beam smoothing parameters that could effectively converge the HSFR of the modified surface was determined through numerous experiments. Using the optimized beam parameters, an ultrathin homogeneous modified surface within 3 nm was obtained. The HSFR of GC smoothed by ion beam modification-assisted smoothing (IBMS) dropped from 0.348 to 0.090 nm, a 74% reduction. These research results offer a deeper understanding of the morphology formation mechanisms of the GC surfaces involved in ion beam processing and may point to a new approach for achieving ultrasmooth heterostructure surfaces down to the subnanometer scale.

Coupling molecular density functional theory with converged selected configuration interaction methods to study excited states in aqueous solution.

This paper presents the first implementation of a coupling between advanced wavefunction theories and molecular density functional theory (MDFT). This method enables the modeling of solvent effect into quantum mechanical (QM) calculations by incorporating an electrostatic potential generated by solvent charges into the electronic Hamiltonian. Solvent charges are deduced from the spatially and angularly dependent solvent particle density. Such a density is obtained through the minimization of the functional associated with the molecular mechanics (MM) Hamiltonian describing the interaction between the fluid particles. The introduced QM/MDFT framework belongs to QM/MM family of methods, but its originality lies in the use of MDFT as the MM solver, offering two main advantages. First, its functional formulation makes it competitive with respect to sampling-based molecular mechanics. Second, it preserves a molecular-level description lost in macroscopic continuum approaches. The excited state properties of water and formaldehyde molecules solvated into water have been computed at the selected configuration interaction (SCI) level. The excitation energies and dipole moments have been compared with experimental data and previous theoretical work. A key finding is that using the Hartree-Fock method to describe the solute allows for predicting the solvent charge around the ground state with sufficient precision for the subsequent SCI calculations of excited states. This significantly reduces the computational cost of the described procedure, paving the way for the study of more complex molecules.

Experimental and theoretical investigation on refining mechanism of Mg2Si by Y addition in the Mg-Al-Si alloys

Aiming at development of new lightweight and high-strength magnesium alloys, a combined experimental and theoretical study on refining mechanism of Mg2Si by Y addition in the Mg-Al-Si alloys was performed. Two alloys, Mg63.32Al22.83Si13.85 and Mg62.56Al22.55Si14.36Y0.52 (wt.%), were prepared and investigated by combining experimental characterization with quantum-mechanical and CALPHAD calculations. The experimental results indicated that Y can refine the Mg2Si phase in Mg-Al-Si alloys but it is rather sensitive to the preparation procedure of the alloys. It was observed that Al4MgY is surrounded by Mg2Si in the as-cast alloys with Y, but it undergoes separation after homogenization annealing. First-principles calculations revealed that the mechanism of Y refining the Mg2Si phase is direct adsorption on the Mg2Si surface rather than indirect adsorption in the form of the elements atomic substitution or entering the center interstitial sites of Mg2Si. The significant refinement of the Mg2Si phase after annealing is attributed to recrystallization within the grains, eliminating the original grain boundaries, and the surface activity is reduced with Y adsorption, resulting in the formation of new and smaller Mg2Si phases. The mechanism behind the Al4MgY phase being surrounded by Mg2Si in the as-cast state but subsequent separation after homogenization annealing is not heterogeneous nucleation, but maybe due to liquid entrapment.

An eco friendly approach for the development of a dipeptide based anti-TB drug nanocomposites: A greener approach in drug delivery system for pulmonary delivery

The conventional anti tubercular (anti-TB) treatment strategies constitute challenges in terms of patient compliance and treatment outcomes. Nano-therapeutics is an emerging field with increasing demand for the therapeutic management of tuberculosis (TB) and the challenges over acquired drug toxicity and poor availability. Nevertheless, studies based on nanopeptide drug carrier for the delivery of anti-TB drugs are scanty. The present work emphasizes on the development of a nanocarrier system through hydrothermal process for encapsulating anti-TB drugs (rifampicin, isoniazid, pyrazinamide, ethambutol) using carnosine dipeptide for the potential therapeutic application. Here, carnosine was synthesized by treating native carnosine and anti-TB drugs at an equal ratio (1:1) incubated at 65°C for 30 min (pH 5.3). The hybrid clusters were freeze dried and used further for characterization (physiochemical, biological, morphology and in silico methods). The structural and functional annotations of carnosine and anti-TB drug nanocomposites are confirmed from its terminal amine absorption stretching’s and its amino group fingerprinting regions. The homogenous nature of carnosine-anti-TB drug complexes in solutions was demonstrated with the particle size (>1 μm), that is suitable for macrophage uptake. SEM analysis demonstrated the interactions and functional group orientation between carnosine and anti-TB drugs during the self-assembling process. The drug release profile indicated that the carnosine-drug conjugation promoted the sustained release compared to free drugs. The quantum mechanical calculations define the structural modelling of drugs with carnosine to obtain a stable energy-minimized conformation. As a result, the developed carnosine- anti-TB drug nanoclusters with stable and uniformity in size makes them suitable for macrophage uptake and targeted delivery approaches during TB treatment.

Growing Glycans in Rosetta: Accurate de novo glycan modeling, density fitting, and rational sequon design.

Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult. Computational approaches can aid in carbohydrate structure prediction, structure determination, and design. In this work, we developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. GlycanTreeModeler was benchmarked on a test set of glycan structures of varying lengths, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. We employed these tools to design de novo glycan trees into a protein nanoparticle vaccine to shield regions of the scaffold from antibody recognition, and experimentally verified shielding. This work will inform glycoprotein model prediction, glycan masking, and further aid computational methods in experimental structure determination and refinement.

Molecular Dynamics Simulation of Silicone Oil Polymerization from Combined QM/MM Modeling.

We outline a molecular simulation protocol for elucidating the formation of silicone oil from trimethlyl- and dimethlysilanediole precursor mixtures. While the fundamental condensation reactions are effectively described by quantum mechanical calculations, this is combined with molecular mechanics models in order to assess the extended relaxation processes. Within a small series of different precursor mixtures used as starting points, we demonstrate the evolution of the curing degree and heat formation in the course of polymer chain growth. Despite the increasing complexity of the amorphous agglomerate of polymer chains, our approach shows an appealing performance for tackling both elastic and viscous relaxation. Indeed, the finally obtained polymer systems feature 99% curing and thus offer realistic insights into the growth mechanisms of coexisting/competing polymer strands.

Unraveling the Role of Boron Dimers in the Electrical Anisotropy and Superconductivity in Boron-doped diamond

We use quantum mechanics (QM) to determine the states formed by B dopants in diamond. We find that isolated B sites prefer to form BB dimers and that the dimers pair up to form tetramers (BBCBB) that prefer to aggregate parallel to the (111) surface in the <110> direction, one double layer below the H-terminated surface double layer. These tetramers lead to metallic character (Mott metal Insulator Transition) with holes in the valence band near the Γ point and electrons in the BBCBB tetramer promoted band along the X direction. Our experiments find very significant anisotropy in the superconductivity for boron-doped diamond thin films prepared with Microwave Plasma Assisted Chemical Vapor Deposition using deuterium-rich plasma. This leads to much higher conductivity in the X direction than the Y direction, as predicted by the QM. This phase transition to the anomalous phase is linked with the emergence of boson quantum entanglement states behaving as a bosonic insulating state. These anisotropic superconducting properties of the diamond film might enable applications such as single-photon detectors. We expect that this formation of a dirty superconductivity state is related to the BBCBB tetramers found in our QM calculations.

Exploratory data science on supercomputers for quantum mechanical calculations

Literate programming—the bringing together of program code and natural language narratives—has become a ubiquitous approach in the realm of data science. This methodology is appealing as well for the domain of Density Functional Theory (DFT) calculations, particularly for interactively developing new methodologies and workflows. However, effective use of literate programming is hampered by old programming paradigms and the difficulties associated with using high performance computing (HPC) resources. Here we present two Python libraries that aim to remove these hurdles. First, we describe the PyBigDFT library, which can be used to setup materials or molecular systems and provides high-level access to the wavelet based BigDFT code. We then present the related remotemanager library, which is able to serialize and execute arbitrary Python functions on remote supercomputers. We show how together these libraries enable transparent access to HPC based DFT calculations and can serve as building blocks for rapid prototyping and data exploration.

Toward Accurate Quantum Mechanical Thermochemistry: (1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions.

Obtaining accurate enthalpies of formation of chemical species, ΔHf, often requires empirical corrections that connect the results of quantum mechanical (QM) calculations with the experimental enthalpies of elements in their standard state. One approach is to use atomization energy corrections followed by bond additivity corrections (BACs), such as those defined by Petersson et al. or Anantharaman and Melius. Another approach is to utilize isodesmic reactions (IDRs) as shown by Buerger et al. We implement both approaches in Arkane, an open-source software that can calculate species thermochemistry using results from various QM software packages. In this work, we collect 421 reference species from the literature to derive ΔHf corrections and fit atomization energy corrections and BACs for 15 commonly used model chemistries. We find that both types of BACs yield similar accuracy, although Anantharaman- and Melius-type BACs appear to generalize better. Furthermore, BACs tend to achieve better accuracy than IDRs for commonly used model chemistries, and IDRs can be less robust because of the sensitivity to the chosen reference species and reactions. Overall, Anantharaman- and Melius-type BACs are our recommended approach for achieving accurate QM corrections for enthalpies.

Synergistic Machine Learning Accelerated Discovery of Nanoporous Inorganic Crystals as Non-Absorbable Oral Drugs.

Machine learning (ML) has taken drug discovery to new heights, where effective ML training requires vast quantities of high-quality experimental data as input. Non-absorbable oral drugs (NODs) have unique safety advantage for chronic diseases due to their zero systemic exposure, but their empirical discovery is still time-consuming and costly. Here, a synergistic ML method, integrating small data-driven multi-layer unsupervised learning, in silico quantum-mechanical computations, and minimal wet-lab experiments was devised to identify the finest NODs from massive inorganic materials to achieve multi-objective function (high selectivity, large capacity and stability). Based on this method, a NH4-form nanoporous zeolite with MER framework (NH4-MER) was discovered for the treatment of hyperkalemia. In 3 different animal models, NH4-MER showed a superior safety and efficacy profile in reducing blood K+ without Na+ release, which is an unmet clinical need in chronic kidney disease and Gordon's syndrome. Our work provides a synergistic ML method to accelerate the discovery of NODs and other shape-selective materials. This article is protected by copyright. All rights reserved.

Crystal violet degradation by visible light-driven AgNP/TiO2 hybrid photocatalyst tracked by SERRS spectroscopy

Dyes are important concerns regarding aquatic environmental contamination given their extensive industrial use and the occurrence of highly toxic and carcinogenic effects on the biota. In this work, photodegradation processes of the organic dye crystal violet (CV) by a hybrid plasmonic photocatalyst involving titanium dioxide (TiO2) and silver nanoparticles (AgNP), through irradiation with low-power visible light were studied, and the experiments were tracked by ultraviolet-visible absorption (UV–VIS) and surface-enhanced resonance Raman scattering (SERRS) spectroscopies. Enhanced photocatalytic activity was observed, reaching about 71, 80 and 87 % of CV removal with only 100 minutes of irradiation, depending on the Ag loading used. The high photocatalytic efficiency is further highlighted by the low energy consumption in the process, requiring only ca. 1.46 kW h L-1 in the best reaction condition. Quantum-mechanical calculations were used to the assignment of electronic spectra, as well as to the prediction of frontier molecular orbitals and atomic charges, aiming to propose mechanisms for radical attacks. Such results allow suggesting degradation processes involved mainly N-demethylation and bond breaking of central carbon. The presence of CV protonated species was also supported through Density Functional Theory (DFT) investigation. The integration of theoretical and experimental results allows proposing the formation of pararosaniline, phenol and benzophenone derivatives, which may have highest ecotoxicity than the original contaminant, outstanding the remarkable relevance of SERRS spectroscopy in monitoring such recalcitrant substances.

17-β-Estradiol—β-Cyclodextrin complex as an aqueous solution: Structural and physicochemical characterization supported by MM and QM calculations

17-β-estradiol (EST) is an Active Pharmaceutical Ingredient characterized by a low water solubility. Complexation with β-cyclodextrin (βCD) enhances its bioavailability, hence such complex is an interesting research object from pharmaceutical point of view. However, basic facts like description of complex's structure and definition of its molar ratio, were debatable already for decades. This work for the first time justifies the EST:βCD molar ratio as 1:2 using the HRMS (high-resolution mass spectrometry) and phase solubility studies. The latter are used to define complex stability constant, as well. The structure and stability is analyzed using a variety of computational approaches: Quantum Mechanics (QM) based methods (DFT, semiempirical approaches) and MD/MMGBSA approach. In case of the QM, for the first time in the computational analysis of cyclodextrin complexes, a thorough benchmarking test is presented. Different computational parameters (solvent model, presence/absence of dispersion correction etc.) are used. Obtained results are compared with the experimental data.

A Combined Experimental, DFT and Molecular Dynamics Simulation Study of Binary Mixture of Ethylbenzene and Aniline

AbstractDensity and viscosity values of the binary mixture of ethylbenzene and aniline have been experimentally measured in different mole fractions at temperatures of 293.15 to 313.15 K and at an absolute pressure of 86.7 kPa. Based on the obtained experimental data, the excess molar volume and viscosity deviations have been reported, which can interpret the interactions in this mixture. The obtained data were fitted with the Redlich‐Kister equation. In addition, the viscosity results are discussed using the equation proposed by Gruenberg‐Nissan. After experimental studies, in order to investigate the interactions of these two components and their mixture, quantum mechanical calculations and molecular dynamics simulation have been used. In this way, the structures of the desired molecules have been optimized. Then Atoms in Molecules (AIM) and frontier molecular orbital (FMO) techniques have been used for a more detailed investigation. Finally, by plotting radial distribution functions (RDFs) obtained from molecular dynamics, these interactions have been investigated in a more comprehensive way. In addition, the simulated densities at 298.15 K have been reported. At the end, clear pictures of the interactions of molecules in mixtures were obtained by comparing the achievements of experimental measurements, quantum chemical and calculations MD simulation.

In situ crystallization of methanesulfonic acid, CH3SO3H, and serendipitous single crystal formation of its anhydride, (CH3)2S2O5

Methanesulfonic acid, CH3SO3H, has been crystallized using an in situ technique on a single crystal diffractometer. The crystal structure is monoclinic (P21/c, Z = 4, a = 842.07(4) pm, b = 582.20(3) pm, c = 820.38(4) pm, β = 106.459(2)°) and stamped by the presence of strong hydrogen bonds. Single crystals of the anhydride of methanesulfonic acid, (CH3)2S2O5, formed as a side product in the reaction of bis‐trimethylsilyl‐sulfate, [(CH3)3SiO]2SO2 with SO3 in a sealed glass ampoule. The monoclinic crystal structure (P21/n, Z = 12, a = 1794.5(2) pm, b = 831.75(7) pm, 1383.4(1) pm, β = 110.630(4)°) shows three crystallographically different (CH3)2S2O5 molecules in the unit cell. According to the orientation of the CH3 groups with respect to each other the (CH3)2S2O5 molecule appears as the so‐called trans‐conformer. The structure of both molecules is corroborated by quantum mechanical DFT calculations.

Reaction mechanisms for methyl isocyanate (CH3NCO) gas-phase degradation

Methyl isocyanate (MIC) is a toxic chemical found in many commercial, industrial, and agricultural processes, and was the primary chemical involved in the Bhopal, India disaster of 1984. The atmospheric environmental chemical reactivity of MIC is relatively unknown with only proposed reaction channels, mainly involving OH-initiated reactions. The gas-phase degradation reaction pathways of MIC and its primary product, formyl isocyanate (FIC), were investigated with quantum mechanical (QM) calculations to assess the fate of the toxic chemical and its primary transformation products. Transition state energy barriers and reaction energetics were evaluated for thermolysis/pyrolysis-like reactions and bimolecular reactions initiated by relevant radicals (•OH and Cl•) to evaluate the potential energy surfaces and identify the primary reaction pathways and products. Thermolysis/pyrolysis of MIC requires high energy to initiate N-CH3 and C-H bond dissociation and is unlikely to dissociate except under extreme conditions. Bimolecular radical addition and H-abstraction reaction pathways are deemed the most kinetically and thermodynamically favorable mechanisms. The primary transformation products of MIC were identified as FIC, methylcarbamic acid, isocyanic acid (isocyanate radical), and carbon dioxide. The results of this work inform the gas-phase reaction channels of MIC and FIC reactivity and identify transformation products under various reaction conditions.

Rhodium(I)-Catalyzed Annulation of Bicyclo[1.1.0]butyl-Substituted Dihydroquinolines and Dihydropyridines.

Bicyclo[1.1.0]butane-containing compounds feature a unique chemical reactivity, trigger "strain-release" reaction cascades, and provide novel scaffolds with considerable utility in the drug discovery field. We report the synthesis of new bicyclo[1.1.0]butane-linked heterocycles by a nucleophilic addition of bicyclo[1.1.0]butyl anions to 8-isocyanatoquinoline, or, alternatively, iminium cations derived from quinolines and pyridines. The resulting bicyclo[1.1.0]butanes are converted with high regioselectivity to unprecedented bridged heterocycles in a rhodium(I)-catalyzed annulative rearrangement. The addition/rearrangement process tolerates a surprisingly large range of functional groups. Subsequent chemo- and stereoselective synthetic transformations of urea, alkene, cyclopropane, and aniline moieties of the 1-methylene-5-azacyclopropa[cd]indene scaffolds provide several additional new heterocyclic building blocks. X-ray structure-validated quantum mechanical DFT calculations of the reaction pathway indicate the intermediacy of rhodium carbenoid and metallocyclobutane species.

Mechanistic insights into the role of cyclodextrin in the regioselective radical CH trifluoromethylation of aromatic compounds.

The regioselective radical CH trifluoromethylation of aromatic compounds have been shown to proceed in good yield and high regioselectivity when cyclodextrin (CD) is present. Yet, the reaction mechanism and the role of CD during the reaction have remained obscure. To this end, here we performed density functional theory (DFT) calculations to the conformations obtained by semiempirical quantum mechanical molecular dynamics calculations to reveal the reaction mechanism and the role of CD in controlling regioselectivity. The results show that metal salt increases the yield but do not affect the regioselectivity, which we further confirmed by an experiment. In contrast, multiple CD-substrate complex conformations and reaction pathways were obtained, and CD was shown to contribute to improving the regioselectivity by stabilizing the intermediate state via encapsulation. The present study indicates that CDs can increase the regioselectivity by stabilizing the intermediate and product states while only marginally affecting the transition state.

Computational Modeling Oriented Substructure Splicing Application in the Identification of Thiazolidine Derivatives as Potential Low Honeybee Toxic Neonicotinoids.

With the aim of identifying novel neonicotinoid insecticides with low bee toxicity, a series of compounds bearing thiazolidine moiety, which has been shown to be low bee toxic, were rationally designed through substructure splicing strategy and evaluated insecticidal activities. The optimal compounds A24 and A29 exhibited LC50 values of 30.01 and 17.08 mg/L against Aphis craccivora, respectively. Electrophysiological studies performed on Xenopus oocytes indicated that compound A29 acted on insect nAChR, with EC50 value of 50.11 μM. Docking binding mode analysis demonstrated that A29 bound to Lymnaea stagnalis acetylcholine binding protein through H-bonds with the residues of D_Arg55, D_Leu102, and D_Val114. Quantum mechanics calculation showed that A29 had a higher highest occupied molecular orbit (HOMO) energy and lower vertical ionization potential (IP) value compared to the high bee toxic imidacloprid, showing potentially low bee toxicity. Bee toxicity predictive model also indicated that A29 was nontoxic to honeybees. Our present work identified an innovative insecticidal scaffold and might facilitate the further exploration of low bee toxic neonicotinoid insecticides.

The Partition of Unity Finite Element Method for the Schrödinger Equation

Abstract A Schrödinger equation for the system’s wavefunctions in a parallelepiped unit cell subject to Bloch-periodic boundary conditions must be solved repeatedly in quantum mechanical computations to derive the materials’ properties. Recent studies have demonstrated how enriched finite element type Galerkin methods can substantially lower the number of degrees of freedom necessary to produce accurate solutions with respect to the standard plane-waves method. In particular, the flat-top partition of unity finite element method enriched with the radial eigenfunctions of the one-dimensional Schrödinger equation offers a very effective way of solving the three-dimensional Schrödinger eigenvalue problem. We investigate the theoretical properties of this approximation method, its well-posedness and stability, we prove its convergence and derive suitable bound for the ℎ- and 𝑝-refinement in the L 2 L^{2} and energy norm for both the eigenvalues and the eigenfunctions. Finally, we confirm these theoretical results by applying this method to the eigenvalue problem of the one-electron Schrödinger equation with the harmonic potential, for which the exact solution is known.

Lignin and Pluronic-based nanomicelles as promising amiodarone nanocarriers: Synthesis, physical characterization, biological, and in silico evaluations

Lignin, a major component of herbaceous plants, is one of the most abundant natural poly-mers that has lipophilic character and antipathogenic properties. Another biocompatible polymer is Pluronic F127, that can cross the blood brain barrier (BBB). Herein, novel drug delivery nanosystems based on oil-in-water microemulsions made of these two biocompatible polymers were developed to load amiodarone (AM), a cationic amphipathic drug used for treating cardiac arrhythmia that displays antifungal and antibacterial properties. The use of drug delivery nanocarriers enhances the solubilization and controlled release of this medication, thus reducing its therapeutic dosage and associated side effects. The morphology, size and surface charge of the nanomiceles was characterized via scanning and transmission electron microscopy (SEM and TEM), dynamic light scattering (DLS) and zeta potential measurements, respectively, which demonstrated their spherical shape, with an average diameter of 27 nm and a zeta potential of −25 mV. Very high entrapment efficiencies were attained for both types of nanomicelles (79.1% and 83.1% for lignin and F127, respectively). Furthermore, both types of AM-loaded nanomicelles exhibited a slower release profile compared to the free drug. Cytotoxicity assay with morphological examination of NIH/3T3 fibroblast cells confirmed a reduction in drug toxicity upon loading onto the nanocarriers. Blood cultures in a chocolate agar medium corroborated that the antibacterial properties of AM are preserved after nanomicelle encapsulation. The interactions of AM with F127 and lignin monomers were investigated via quantum mechanical computations, which revealed the formation of strong hydrogen bonds, the most intense being between AM and lignin. Overall, these novel formulations exhibit great potential for the sustained and targeted AM delivery.