Optimization Calculations Research Articles

DFT calculations of structural, chemical, electronic and thermodynamic properties of Rifampicin and Oxalic Acid

The thermodynamic properties of the compounds contribute to the theoretical analysis of the results of favorable energies that are subject to interaction. In this work, through the DFT study, the comparison of the functionals ωB97XD and B3LYP. Geometry optimization calculations and vibrational frequencies were performed for the individual ions and for the interactions. In all cases, all calculated vibrational frequencies are positive, confirming the optimized geometry obtained as a minimum on the potential energy surface. The calculations were carried out in solvent, considering the solvation effect in methanol using the IEFPCM (Integral Equation Formalism of the Polarizable Continuum Model) method. The present work aims to carry out a theoretical study, for in-depth investigations of structural, electronic and thermodynamic properties. In usability in the calculation of the thermodynamic properties, Rifampicin (RIF) and Oxalic Acid (OXA) and the interaction between RIF-OXA in the protonated form protonated RIF with charge +1 and deprotonated OXA with charge -1. In this context, the most favorable thermodynamic parameters in the interaction calculated RIF+-OXA- the values of ∆EZPVE+BSSE, ∆G298 and ∆H in kcal/mol more favorable are -19.62, -14.81 and -25,77.

Selection of aerodynamic characteristics and engine parameters of a maneuverable aircraft under epistemic uncertainty

At the preliminary stage of aircraft design, it is usually required to solve the problem of insufficient initial data for applying traditional algoristic-type mathematical programming models. In many cases, numerous input parameters cannot be accurately specified at the time of making design decisions. If the inaccuracy of parameters is not taken into account, the actual values of target functions may differ significantly from the calculated ones when solving optimization problems. In this regard, the issue of current interest is the development of algorithms to improve the reliability of design decisions under conditions of epistemological uncertainty when experts engage in the formation of initial data. The paper considers the problem of selecting aerodynamic characteristics and engine parameters of maneuverable aircraft under conditions of uncertainty associated with inaccuracy of expert data. The applied problem under consideration is further complicated by the necessity to include “black box” models in the algorithms being developed. The paper proposes algorithms that apply the uncertainty theory together with “black box” models that implement optimization calculation techniques derived from previous engineering practice of aircraft design. Using these algorithms, experts are able to set uncertain parameters whereby the lack of data is factored in using uncertainty distribution functions. In cases of monotonicity of uncertain parameters in target functions, application of the uncertainty theory provides a significant reduction in computational costs compared to the method of statistical modeling in optimization calculations. The paper presents the results of computational studies of the developed algorithms. A genetic algorithm (mathematical optimization solver) is used to optimize the search for design solutions. Pareto frontiers are obtained for different confidence levels enabling to make design decisions including values of aerodynamic characteristics and engine parameters of maneuverable aircraft.

Quad-Rotor Avoidance Trajectory Generation for Convex Polyhedron Obstacles

This study investigates a method for generating obstacle avoidance trajectories for arbitrary convex polyhedrons. We propose a formulation that converts discrete conditions into continuous equation forms to avoid convex polyhedron obstacles. The condition that the evaluation point be located outside of the convex polyhedron can be transformed into a constraint in the continuous equation form and incorporated into the optimization calculation to generate avoidance trajectories. Avoidance trajectory generation using the Legendre pseudospectral method is performed for convex polyhedral obstacles of various shapes. The results show that the proposed method successfully generates avoidance trajectories for arbitrary convex polyhedral obstacles.

Dynamics analysis and collaborative optimization of vehicle steering mechanism

In order to improve the dynamic response characteristics of the steering mechanism, a research scheme for increasing the natural frequency based on lightweight design was proposed. Based on the finite element method and the collaborative optimization method, the modal characteristics and harmonic response characteristics of the model were studied and analyzed to verify the strength and stiffness performance of the optimized structure. The modal shapes between the free mode and the constrained mode were compared and analyzed. With the second-order natural frequency as the optimization objective, the response surface function of the equivalent stiffness was constructed. Through optimization calculation, the design variables that satisfy the constraint conditions can be obtained. The results show that the optimized structure can increase the second-order natural frequency by 14.4 % on the premise of reducing the mass by 5.2 %, effectively avoiding the excitation frequency of the engine.

Quantification of Adeno-Associated Viral Genomes in Purified Vector Samples by Digital Droplet Polymerase Chain Reaction.

Adeno-associated virus (AAV) is a non-pathogenic virus used as a delivery vehicle to transfer therapeutic genes into patients. Accurate quantification of AAV genome copy number in vector preparations is essential for bioprocess optimization and dosage calculation in both preclinical and clinical studies of AAV-based gene therapy products. Currently, a consensus protocol for AAV viral genome titration is lacking. Here, we present a digital droplet PCR (dd_PCR) protocol for the quantification of viral genomes in purified vector samples. Samples are treated with DNase I to eliminate unpackaged contaminant DNA. DNase-treated samples are then mixed with an appropriate primer-probe set (designed according to the target AAV genome) and PCR reagents, and then loaded into a droplet generator. The prepared droplets are transferred into a PCR plate, where PCR amplification is performed and analyzed. The viral genome titer is calculated based on the concentration (copies/µL), accounting for sample dilutions. A successful measurement shows a clear separation of the positive and negative droplet clouds, has at least 10,000 accepted droplets, shows a value between 10 copies/µL and 10,000 copies/µL, and has a coefficient of variation (CV) between repeats lower than 20%. Reliable viral genome titration will aid in the development of safe and effective AAV-based gene therapy products.

Implementation of High-Precision Life Cycle Cost Analysis (HP-LCCA) on Indonesian Bridge Management System

Life Cycle Cost Analysis (LCCA) is a method used to determine the preservation costs required for an object, in this case, a bridge, throughout its service life. This method has been implemented in several advanced countries, including Japan. The LCCA calculation concept in Japan differs from those in other countries, as it involves a detailed segmentation of structural elements of bridges, making the model unique and highly detailed. This model is known as High-Precision Life Cycle Cost Analysis (HP-LCCA) and will be tested for application in Bridge Management Systems (BMS) in Indonesia. Implementing this model requires several adjustments, including aligning perceptions of visual inspection results and adapting the assessment concepts for each element based on research interpretations. Additionally, the difference between non-physical and physical condition assessment models presents a challenge for adopting this calculation model. The research shows a similar pattern and positive correlation between non-physical and physical assessment models. Furthermore, factors influencing LCC calculations include bridge age and the number of segments in structural elements. This research aims to provide optimal LCC calculations and facilitate their application in BMS in Indonesia.

Introducing KICK-MEP: exploring potential energy surfaces in systems with significant non-covalent interactions.

Exploring potential energy surfaces (PES) is fundamental in computational chemistry, as it provides insights into the relationship between molecular energy, geometry, and chemical reactivity. We introduce Kick-MEP, a hybrid method for exploring the PES of atomic and molecular clusters, particularly those dominated by non-covalent interactions. Kick-MEP computes the Coulomb integral between the maximum and minimum electrostatic potential values on a 0.001 a.u. electron density isosurface for two interacting fragments. This approach efficiently estimates interaction energies and selects low-energy configurations at reduced computational cost. Kick-MEP was evaluated on silicon-lithium clusters, water clusters, and thymol encapsulated within Cucurbit[7]uril, consistently identifying the lowest energy structures, including global minima and relevant local minima. Kick-MEP generates an initial population of molecular structures using the stochastic Kick algorithm, which combines two molecular fragments (A and B). The molecular electrostatic potential (MEP) values on a 0.001 a.u. electron density isosurface for each fragment are used to compute the Coulomb integral between them. Structures with the lowest Coulomb integral are selected and refined through gradient-based optimization and DFT calculations at the PBE0-D3/Def2-TZVP level. Molecular docking simulations for the thymol-Cucurbit[7]uril complex using AutoDock Vina were performed for benchmarking. Kick-MEP was validated across different molecular systems, demonstrating its effectiveness in identifying the lowest energy structures, including global minima and relevant local minima, while maintaining a low computational cost.

Optimization of atomization performance of external mixing air atomizing nozzle based on response surface agent model

Based on the finding that the atomization performance of the nozzle is affected by its structural parameters, a combination of finite element analysis and structural optimization calculations is used. Finite element analysis was performed through the VOF (Volume of Fluid) module of Fluent software to determine the structural parameters affecting the performance of the atomizing nozzle. The liquid cyclone tank inclination, the length of the flat section at the gas outlet, and the mixing chamber outlet diameter were used as optimization factors. The atomization cone angle and fuel atomization circumferential distribution uniformity index were used as the evaluation indexes of atomization performance. An orthogonal experimental design was carried out based on the above. Proxy model for atomization cone angle and fuel atomization circumferential distribution uniformity index based on response surface method. The optimal structure of the nozzle was obtained by optimization calculation of the agent model by genetic algorithm. The results show that the atomization performance is optimal when the inclination angle of the liquid rotating tank is 42.9, the length of the flat section at the gas outlet is 3.3, and the diameter of the mixing chamber outlet is 5.0. The atomization cone angle increased by 23.07 % compared with the original model, and the fuel atomization circumferential distribution uniformity index decreased by 45.06 %. A new solution for the design of externally mixed air atomizing nozzles is provided.

Knowledge-based planning, multicriteria optimization, and plan scorecards: A winning combination

Background and purposeThe ESTRO 2023 Physics Workshop hosted the Fully-Automated Radiotherapy Treatment Planning (Auto-RTP) Challenge, where participants were provided with CT images from 16 prostate cancer patients (6 prostate only, 6 prostate + nodes, and 4 prostate bed + nodes) across 3 challenge phases with the goal of automatically generating treatment plans with minimal user intervention. Here, we present our team’s winning approach developed to swiftly adapt to both different contouring guidelines and treatment prescriptions than those used in our clinic. Materials and methodsOur planning pipeline comprises two main components: 1) auto-contouring and 2) auto-planning engines, both internally developed and activated via DICOM operations. The auto-contouring engine employs 3D U-Net models trained on a dataset of 600 prostate cancer patients for normal tissues, 253 cases for pelvic lymph node, and 32 cases for prostate bed. The auto-planning engine, utilizing the Eclipse Scripting Application Programming Interface, automates target volume definition, field geometry, planning parameters, optimization, and dose calculation. RapidPlan models, combined with multicriteria optimization and scorecards defined on challenge scoring criteria, were employed to ensure plans met challenge objectives. We report leaderboard scores (0–100, where 100 is a perfect score) which combine organ-at-risk and target dose-metrics on the provided cases. ResultsOur team secured 1st place across all three challenge phases, achieving leaderboard scores of 79.9, 77.3, and 78.5 outperforming 2nd place scores by margins of 6.4, 0.4, and 2.9 points for each phase, respectively. Highest plan scores were for prostate only cases, with an average score exceeding 90. Upon challenge completion, a “Plan Only” phase was opened where organizers provided contours for planning. Our current score of 90.0 places us at the top of the “Plan Only” leaderboard. ConclusionsOur automated pipeline demonstrates adaptability to diverse guidelines, indicating progress towards fully automated radiotherapy planning. Future studies are needed to assess the clinical acceptability and integration of automatically generated plans.

Research on distributed optimal scheduling method based on consensus

Abstract With access to large-scale distributed power sources, the physical structure of the power grid system tends to be distributed. The application of traditional centralized optimal scheduling methods will lead to a surge in communication overhead and computational complexity, which will affect the performance and efficiency of the solution. In this paper, the minimum operating cost of the system is taken as the goal, and the distributed direct current optimal power flow (DC-OPF) optimization calculation of the photovoltaic-storage power generation system is considered to approximately solve the economic dispatch problem. The DC optimal power flow model with energy storage charging penalty is constructed. Then, the distributed optimization method based on the consensus alternating direction multiplier method (ADMM) is adopted. By decoupling the objective function and constraints of the whole system problem, the fully distributed DC-OPF calculation is realized by introducing the global consensus variable to deal with the boundary buses. Finally, the improved IEEE 30-bus example is used to test the method, and the simulation results verify the convergence and accuracy of the method.

Pioneering computational insights into the structural, magnetic, and thermoelectric properties of A3XN (A=Co, Fe; X=Cu, Zn) anti-perovskites for advanced material applications

This study pioneers the utilization of computer-controlled simulations to elucidate the structural, elastic, electronic, and thermoelectric properties of A3XN anti-perovskites (A = Co, Fe; X = Cu, Zn). Starting with the development of a detailed structural model, structural optimization calculations identify the stable Pm-3m cubic phase, aligning with experimental findings. Also, these optimizations indicate the ferromagnetic phase stability of A3XN anti-perovskites, further supported by positive Curie-Weiss constants of 60 K, 80 K, and 100 K for Co₃CuN, Co₃ZnN, and Fe₃CuN, respectively. The spin-dependent electronic properties, including band structure and density of states, are explored using multiple exchange-correlation (XC) functionals—GGA, GGA + U, and GGA + mBJ. The results uphold the metallic nature of the materials, accompanied by significant spin magnetic moments. Specifically, the calculated values of magnetic moments for Co3CuN, Co3ZnN, and Fe3CuN are 5.08 μB, 3.70 μB, and 7.61 μB, respectively. Furthermore, we compute the Curie temperatures for each compound, 942.48 K for Co3CuN, 692.7 K for Co3ZnN, and 1400.41 K for Fe3CuN, which are substantially elevated, indicating robust ferromagnetic behavior that persists well above ambient conditions. Mechanical properties, including stability, deformation behavior, and ductility, are validated through elastic calculations, with various mechanical anisotropy factors examined. From an application perspective, the thermoelectric characteristics of Co3CuN, Co3ZnN, and Fe3CuN are meticulously evaluated, focusing on parameters like the Seebeck coefficient, electrical conductivity, thermal conductivity, power factor and figure of merit (zT). The analysis highlights promising power factor values of 3.0×1011(W/cm.K2), 4.0×1011(W/cm.K2), and 6.0×1011(W/cm.K2) for Co3CuN, Co3ZnN, and Fe3CuN, respectively, suggesting potential for enhanced efficiency in thermopower generation, particularly in waste heat recovery applications. Furthermore, the study provides a comprehensive analysis of the ground-state optical properties of A3XN, including the dielectric constant, photoconductivity, reflectivity, refractive index, absorption coefficient, and extinction coefficient. The reflectivity spectra demonstrate high reflectivity of 45 % across visible and ultravioletregions, suggesting suitability for applications in coatings designed to mitigate solar heating effects.

Automatization of theoretical kinetic data generation for tabulated TS models building - Part 1: Application to 1,3-H-shift reactions

Estimation of kinetic parameters is a key aspect of chemical combustion modeling and several approaches were developed to approximate unknown data. In this work, a code in Python was developed to build tables of transition state (TS) models automatically for intramolecular H-shift reactions in alkyl radicals. The code generates the kinetic rules for all the possible combinations of methyl-substituted reactions based on the structures of the minimal, non-substituted, reactant, TS, and product. The code is able to create and differentiate multiple transition state configurations, considering the axial and equatorial positions for the cyclic substituents and including all the possible pathways for the reactions, which is shown to be an important feature in performing accurate automatic kinetic calculations. Each structure is automatically submitted to geometry optimization and electronic energy calculations, as well as the relaxed scans of the torsional modes identified by the code. From the results of electronic calculations, the rate constants for each pathway are obtained automatically by the application of the transition state theory with tunneling corrections, in a defined temperature range. The kinetic coefficients, as well as the modified Arrhenius parameters, are then assembled and organized to create a final table that connects the kinetic data with TS structure characteristics. These tables can be directly applied as a kinetic data source for reaction mechanism development. The ability of the code to generate reliable rate constants was tested for 1,3-H-shift reactions and the results were compared with theoretical data manually produced, and showed a good agreement. In particular, the code was able to create all the transition state configurations, with an exhaustive description of all possible reaction pathways, using a rigorous and systematic counting based on symmetry, stereocenters, and diastereomers. The proposed method leads to more accurate results on these aspects, compared to repetitive hand calculations of dozens of rate constants.

Fast CU decision method based on texture characteristics and decision tree for depth map intra-coding

As the demand for higher quality 3D videos continues to grow, the 3D extensions of the Efficient Video Coding (3D-HEVC) standard are gradually unable to meet the needs of users. Versatile Video Coding Standard (H. 266/VVC), as an advanced video coding standard, adopts the nested Multi-Type Tree quadtree (QTMT) partitioning structure that current fast depth map coding unit (CU) partitioning methods cannot apply. Therefore, we have designed a fast intra-frame CU partitioning algorithm for VVC 3D video depth maps. Our proposed algorithm in this article consists of two steps, including two sub-algorithms. First, by analyzing the relationship between image entropy and variance and depth map CU division, we establish a bi-criterion decision algorithm to determine whether the texture complexity of the current CU is low enough to terminate its partitioning process. Then, for CUs that have been determined by the first algorithm to need further partitioning, we use a decision tree model based on Light Gradient Boosting Machine (LGBM) to predict which direction of Rate-Distortion Optimization (RDO) calculation can be skipped, which can avoid some unnecessary RDO calculations in a certain direction. The final experiment demonstrated the effect of the proposed algorithm, which can reduce 47.65% complexity of VVC 3D video intra-coding with negligible 0.23% Bjøntegaard Delta Bitrate (BDBR) increase, superior to other advanced methods.

Influence of Supercritical Conditions on Isothermal Adsorption Capacity Calculation of Methane and Model Optimization.

The study of isothermal adsorption models for coal and methane under supercritical conditions helps us to understand the gas content distribution in coal seams and improve gas management in coal mines. Coal samples from the Hebi mine and Longshan coal mine were selected for this research. Using the weight method, isothermal adsorption curves of supercritical methane at temperatures of 308, 313, and 318 K were measured. The adsorption phase density of supercritical methane was obtained by using the intercept method and model fitting, and the absolute adsorption capacity of methane was calculated. Simultaneously, the pore volume and specific surface area of the coal samples were tested, and the isothermal adsorption model for supercritical methane was studied and optimized. The results indicate that using mercury intrusion, low-temperature N2, and low-temperature CO2 adsorption methods for testing coal sample pore structures allows for multiscale characterization of the coal pore structure. Based on the Gibbs excess adsorption theory, the phase density of methane obtained from the intercept method and model fitting effectively represent the isothermal adsorption curve of supercritical methane. By combination of the specific surface area and pore volume distribution of the coal with the absolute adsorption capacity of methane, the number of methane adsorption layers on the coal surface was calculated to be between 1.11 and 1.3 layers. This suggests that the isothermal adsorption model for supercritical methane on coal is not solely micropore filling or single molecular layer adsorption but primarily single molecular layer adsorption with concurrent micropore filling adsorption. Based on this adsorption mechanism, an L-DA isothermal adsorption model for supercritical methane on coal was established. The L-DA isothermal model shows good fitting results and effectively explains the adsorption characteristics of supercritical methane on coal.

Trivalent transition metal ion mediated template synthesis: In silico molecular docking, DNA binding, antimicrobial evaluation and DFT studies

In order to reduce the chances of multiple drug resistance, there is an urgent requirement for the designing of new antimicrobial agents. In this current research, series of novel hexaazamacrocyclic trivalent transition metal complexes of ChromiumIII and IronIII have been prepared by adopting the pathway of metal ion mediated template condensation. The newly synthesized macrocyclic complexes were analyzed by Infra-Red Spectroscopy, Carbon-Hydrogen-Nitrogen analyzer, UltraViolet–visible, Powder X-Ray Diffraction, Electron Paramagnetic Resonance, Magnetic Susceptibilities, Molar conductance, Electron Spray Ionisation-Mass Spectrometry and Thermogravimetric analysis techniques. The electro-lytic behaviour of the complexes was suggested by conductance (molar) values. All the complexes (T7-T12) can be formulated or represented as [MLX] X2·yH2O, where M = FeIII, CrIII and L is the macrocyclic ring resulting from 1,8-diaminonaphthalene and succinimide and X = NO3−, Cl−, CH3COO− and y = 1 or 2. All the macrocyclic complexes have been anticipated to have a penta coordinated square pyramidal shape using several physico-analytical approaches. Monomeric nature of the complexes was confirmed by CHN analysis and mass spectral data. Powder X-Ray Diffraction studies were carried out for interpreting the crystallinity of the complexes. Density Functional Theory studies were performed for energy optimization and theoretical calculations of UV & IR. The DNA interaction studies showed intercalative mode of binding is present in the newly designed complexes with the DNA. In addition to these, all the metal complexes were screened for their antibacterial and antifungal activity against pathogenic strains of bacteria and fungi, Complex T7 has effective bactericidal action against B. cereus and E. coli. Molecular docking studies were also performed on SARS Cov-2 and Mycobacterium tuberculosis. The used proteins are NSP15 Endoribonuclease from SARS CoV-2 and DNA of Mycobacterium tuberculosis H37Rv. The results revealed that complex T10 is having good binding affinity against DNA of Mycobacterium tuberculosis H37Rv.

A theoretical and kinetic study of key reactions between ammonia and fuel molecules, part III: H-atom abstraction from esters by ṄH2 radicals

Hydrogen atom abstraction reactions by ṄH2 radicals play a crucial role in determining the reactivity of ammonia/fuel binary blends. Esters are a typical component of environmentally friendly and economically promising biofuels. The feasibility of the ammonia/biofuel dual-fuel approach has been proven in practical engines. [Energy and Fuels 22 (2008) 2963] and [Int. J. Energy Res. 2023 (2023) 9920670]. ṄH2 radicals play a critical role in the combustion and pyrolysis chemistry of ammonia and N-containing-rich fuels. In ammonia/biofuels hybrid combustion, ṄH2 radicals can react with biofuel molecules in a reaction class that is particularly important especially when sufficient ammonia is blended in order to eliminate NOx emissions. To help unravel the chemistry of ammonia/biofuel blends, a systematic theoretical kinetic study of H-atom abstraction from eleven alky esters of CnH2n+1COOCH3 (n = 1–4), CH3COOCmH2m+1 (m = 1–4), and C2H5COOC2H5, by ṄH2 radicals is performed in this work. The geometry optimization, frequency, and zero-point energy calculations for all related species, as well as the hindrance potential energy surface for low frequency torsional modes in the reactants and transition states, were performed at the M06–2X/6–311++G(d,p) level of theory. Intrinsic reaction coordinate calculations were performed to validate the connections between the transition states and expected minima energy species. The energies of all of the species involved were calculated at the QCISD(T)/cc-pVXZ (X = D, T, Q) and MP2/cc-pVYZ (Y = T, Q) levels of theory and then extrapolated to the complete basis set. Rate constants of 39 reactions were calculated using the Master Equation System Solver (MESS) program in the temperature range of 500 – 2000 K. These rate constants for different H-atom abstraction sites are provided and can be extrapolated to larger esters. The kinetic effects from the functional group are also illustrated by performing detailed comparisons with the previous studies of ṄH2 radical reactions with alkanes, alcohols and ethers.

Experimental and computational insight in molecular interactions of imidazolium based deep eutectic solvent with selected alcohols (C1 and C2)

The experimental thermophysical properties (densities (ρ), speed of sound (u) and refractive (nD) indices) of binary mixtures containing 1:3 mol ratio of [1-butyl-3-dimethylimidazolium chloride to ethylene glycol] [BMIM]Cl: EG], deep eutectic solvent (DES), with selected alcohols (methanol and ethanol) were measured. The measurements of the binary mixtures and the pure solvents were conducted at temperatures ranging from (293.15 to 313.15) K in the interval of 5 K and at ambient pressure using an Anton Paar densitometer. Thermodynamic properties such as excess molar volumes (VmE), intermolecular free length (Lf), isentropic compressibilities (ks), deviation in isentropic compressibilities (Δks) and deviation in refractive indices (ΔnD) were computed from the measured data of physical properties. These excess thermodynamic properties are utilized to investigate the intermolecular interactions occurring between imidazolium DES and methanol or ethanol. Geometry optimization calculations were undertaken using Density Functional Theory (DFT) to model the structure of DES with a 1:1 mol ratio employing the B3LYP-D3 functional and a basis set of 6–31G++**. The DFT results revealed that the interaction energies within the DES in the presence of solvent favoured the formation of the complex. Furthermore, interrogation of the optimized structures at molecular level showed that the interactions were mediated by the electrostatic ionic bonding with the co-solvent playing a significant role in solubility. The excess molar volumes of binary mixtures were correlated using the Lorentz-Lorenz equation, and the densities and refractive indices were predicted using the Lorentz-Lorenz equation. The interaction energies and electrostatic interactions between the different solvents were predicted using quantum mechanics. The experimental data was found to be in good agreement with the theoretical data for the measured properties as well as the computational predictions of the stability of the systems.

Reactivity assessment of oligomeric systems associated with crystalline and amorphous cellulose for bioethanol production: a DFT study.

The production of bioethanol from renewable raw materials is a decisive factor in the economic development of many countries. However, the complexity of the processes and the numerous experimental variables involved require a deeper understanding of the chemical reactions that take place during bioethanol production to define optimal parameters. Here, we have employed density functional theory-based calculations to investigate the local reactivity of oligomeric systems by consideringcrystalline and amorphous cellulose models to better understand some details regarding pulp pretreatment processes. Our results evidence a higher chemical susceptibility of amorphous portions of cellulose to chemicals typically employed in acid hydrolysis. Additionally, we observed that glucose monomers coming from cellulose hydrolysis may undergo oxidation, leading to the formation of byproducts such as hydroxymethylfurfural (HMF), acetic acid, formic acid, and levulinic acid. The analysis of local chemical softness indexes indicated that cellulose hydrolysis may be associated with intermediate chemical steps. Finally, we investigated the influence of distinct solvents (dielectric constants) on the local reactivity of the systems, evidencing a relevant role of the solvent dielectric constant for cellulose degradation in glucose. Initial three-dimensional structures were constructed. Pre-optimizations were performed in a Hartree-Fock (HF) approach employing thePM7 semi-empirical hamiltonian. The structures were then re-optimized via density functional theory (DFT). The local reactivity study of the systems was conducted through the condensed-to-atoms Fukui indexes (CAFI). Systematic changes of the dielectric constants were also considered in geometry optimization and CAFI calculations to estimate the influence of solvents on the reactivity of the systems.

Predicting ELNES/XANES spectra by machine learning with an atomic coordinate-independent descriptor and its application to ground-state electronic structures

ELNES/XANES spectra can be observed using TEM or synchrotron radiation and can elucidate the unoccupied state electronic structures of an excited states. The computation of their features is usually demanding substantial computational resources due to the requisite structure optimization and electronic structure calculations. Herein, we leverage a machine learning technique alongside an atomic-coordinate-independent descriptor, SMILES, to yield the ELNES/XANES spectra, directly, with heightened precision. Moreover, our approach extends to obtain ground state electronic structure, namely PDOS at both occupied and unoccupied ground states, underscoring its viability for a ground-state spectroscopy. Our study revealed that incorporation of long-SMILES molecules into the training dataset enhances prediction accuracy for such molecular structures. This study's direct derivation of spectroscopy from SMILES strings holds promise for expediting spectroscopic inquiries.

Tutton salt (NH4)2Zn(SO4)2(H2O)6: thermostructural, spectroscopic, Hirshfeld surface, and DFT investigations

ContextAmmonium Tutton salts have been widely studied in recent years due to their thermostructural properties, which make them promising compounds for application in thermochemical energy storage devices. In this work, a detailed experimental study of the Tutton salt with the formula (NH4)2Zn(SO4)2(H2O)6 is carried out. Its structural, vibrational, and thermal properties are analyzed and discussed. Powder X-ray diffraction (PXRD) studies confirm that the compound crystallizes in a structure of a Tutton salt, with monoclinic symmetry and P21/a space group. The Hirshfeld surface analysis results indicate that the main contacts stabilizing the material crystal lattice are H···O/O···H, H···H, and O···O. In addition, a typical behavior of an insulating material is confirmed based on the electronic bandgap calculated from the band structure and experimental absorption coefficient. The Raman and infrared spectra calculated using DFT are in a good agreement with the respective experimental spectroscopic results. Thermal analysis in the range from 300 to 773 K reveals one exothermic and several endothermic events that are investigated using PXRD measurements as a function of temperature. With increasing temperature, two new structural phases are identified, one of which is resolved using the Le Bail method. Our findings suggest that the salt (NH4)2Zn(SO4)2(H2O)6 is a promising thermochemical material suitable for the development of heat storage systems, due to its low dehydration temperature (≈ 330 K), high enthalpy of dehydration (122.43 kJ/mol of H2O), and hydration after 24 h.MethodsComputational studies using Hirshfeld surfaces and void analysis are conducted to identify and quantify the intermolecular contacts occurring in the crystal structure. Furthermore, geometry optimization calculations are performed based on density functional theory (DFT) using the PBE functional and norm-conserving pseudopotentials implemented in the Cambridge Serial Total Energy Package (CASTEP). The primitive unit cell optimization was conducted using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm. The electronic properties of band structure and density of states, and vibrational modes of the optimized crystal lattice are calculated and analyzed.Graphical abstract