Experimental Reference Data Research Articles

Structural Properties of Metal-Organic Frameworks at Elevated Thermal Conditions via a Combined Density Functional Tight Binding Molecular Dynamics (DFTB MD) Approach.

The performance of different density functional tight binding (DFTB) methods for the description of six increasingly complex metal-organic framework (MOF) compounds have been assessed. In particular the self-consistent charge density functional tight binding (SCC DFTB) approach utilizing the 3ob and matsci parameter sets have been considered for a set of four Zn-based and two Al-based MOF systems. Moreover, the extended tight binding for geometries, frequencies, and noncovalent interactions (GFN2-xTB) approach has been considered as well. In addition to the application of energy minimizations of the respective unit cells, molecular dynamics (MD) simulations at constant temperature and pressure conditions (298.15 K, 1.013 bar) have been carried out to assess the performance of the different DFTB methods at nonzero thermal conditions. In order to obtain the XRD patterns from the MD simulations, a flexible workflow to obtain time-averaged XRD patterns from (in this study 5000) individual snapshots taken at regular intervals over the simulation trajectory has been applied. In addition, the comparison of pair-distribution functions (PDFs) directly accessible from the simulation data shows very good agreement with experimental reference data obtained via measurements employing synchrotron radiation in case of MOF-5. The comparison of the lattice constants and the associated X-ray diffraction (XRD) patterns with the experimental reference data demonstrate, that the SCC DFTB approach provides a highly efficient and accurate description of the target systems.

The relationship between structure and excited-state properties in polyanilines from geminal-based methods.

We employ state-of-the-art quantum chemistry methods to study the structure-to-property relationship in polyanilines (PANIs) of different lengths and oxidation states. Specifically, we focus on leucoemeraldine, emeraldine, and pernigraniline in their tetramer and octamer forms. We scrutinize their structural properties, HOMO and LUMO energies, HOMO-LUMO gaps, and vibrational and electronic spectroscopy using various Density Functional Approximations (DFAs). Furthermore, the accuracy of DFAs is assessed by comparing them to experimental and wavefunction-based reference data. We perform large-scale orbital-optimized pair-Coupled Cluster Doubles (oo-pCCD) calculations for ground and electronically excited states and conventional Configuration Interaction Singles (CIS) calculations for electronically excited states in all investigated systems. The EOM-pCCD+S approach with pCCD-optimized orbitals allows us to unambiguously identify charge transfer and local transitions across the investigated PANI systems-an analysis not possible within a delocalized canonical molecular orbital basis obtained, for instance, by DFAs. We show that the low-lying part of the emeraldine and pernigraniline spectrum is dominated by charge transfer excitations and that polymer elongation changes the character of the leading transitions. Furthermore, we augment our study with a quantum informational analysis of orbital correlations in various forms of PANIs.

Benchmarks for transition metal spin-state energetics: why and how to employ experimental reference data?

Accurate prediction of energy differences between alternative spin states of transition metal complexes is essential in computational (bio)inorganic chemistry-for example, in characterization of spin crossover materials and in the theoretical modeling of open-shell reaction mechanisms-but it remains one of the most compelling problems for quantum chemistry methods. A part of this challenge is to obtain reliable reference data for benchmark studies, as even the highest-level applicable methods are known to give divergent results. This Perspective discusses two possible approaches to method benchmarking for spin-state energetics: using either theoretically computed or experiment-derived reference data. With the focus on the latter approach, an extensive general review is provided for the available experimental data of spin-state energetics and their interpretations in the context of benchmark studies, targeting the possibility of back-correcting the vibrational effects and the influence of solvents or crystalline environments. With a growing amount of experience, these effects can be now not only qualitatively understood, but also quantitatively modeled, providing the way to derive nearly chemically accurate estimates of the electronic spin-state gaps to be used as benchmarks and advancing our understanding of the phenomena related to spin states in condensed phases.

Simple, accurate, adjustable-parameter-free prediction of NMR shifts for molecules in solution.

Accurate prediction of NMR shifts is invaluable for interpreting and assigning NMR spectra, especially for complex applications such as determining the identity of unknown substances or resolving stereochemical assignments. Statistical linear regression models have proven effective for accurately correlating density functional theory predictions of chemical shieldings with experimentally-measured shifts, but lack transferability - they must be reparameterised using a reasonably extensive training set at each level of theory and for each choice of NMR solvent. We have previously introduced a novel two-point "shift-and-scale" correction procedure for gas phase shieldings that overcomes these limitations without significant loss of accuracy. In this work, we demonstrate that this approach is equally applicable for predicting solution-phase shifts from computed gas phase shieldings, using acetaldehyde as an experimentally and computationally convenient reference system. We also present all of the required experimental reference data to enable this approach to be used for any target analyte in a range of commonly used NMR solvents (chloroform, dichloromethane, acetonitrile, methanol, acetone, DMSO, D2O, benzene, pyridine).

A mass–momentum consistent coupling for mesh-adaptive two-phase flow simulations

We present a novel mass–momentum consistent coupling between a geometric volume-of-fluid scheme and an incompressible flow solver with differing directional-splitting approaches. The advection of the volume fraction is performed using a direction-split algorithm, whereas the momentum advection algorithm uses a traditional unsplit, fractional-step approach. Both algorithms employ finite-volume discretizations based on Cartesian meshes. In solving the mass–momentum consistency problem, momentum fluxes at the cell faces are weighted by the density fluxes based on the already advected volume fraction. The success of our approach lies on introducing a Favre-averaged velocity interpolation at the liquid/gas interface along with a minmod slope limiter. Mesh-convergence studies show that when the minmod slope limiter is used, the two-phase solver retains an accuracy between first and second order, but when a purely upwind scheme is considered, its accuracy drops to first order. Finally, after considering several validation problems, the solver is shown to agree well with reference numerical and experimental data while retaining its robustness and efficiency.

Exact solution of Eshelby's inhomogeneity problem in strain gradient theory of elasticity and its applications in composite materials

A new micromechanical approach to deal with the problem of Eshelby's inhomogeneity is developed for the prediction of the effective properties of composite materials according to the strain gradient elasticity theory. The method is based on the Green's function technique leading to an integral equation of the heterogeneous elastic problem. Within the simplified strain gradient elasticity theory, the integral equation for an infinite heterogeneous medium subjected to non-homogeneous boundary conditions is acquired. Thanks to this integral equation, the exact solution of Eshelby's inhomogeneity problem is detailed for spherical inhomogeneity and isotropic elastic behavior. From the expression of strain localization relations, the effective elastic properties of a two-phase composite material are then predicted through Mori Tanaka's homogenization scheme. To test the relevance of the suggested approach, its predictions are compared with results issued from some reference models and experimental data.

Assessing the quality of QM/MM approaches to describe vacuo-to-water solvatochromic shifts.

The performance of different quantum mechanics/molecular mechanics embedding models to compute vacuo-to-water solvatochromic shifts is investigated. In particular, both nonpolarizable and polarizable approaches are analyzed and computed results are compared to reference experimental data. We show that none of the approaches outperform the others and that errors strongly depend on the nature of the molecular transition to be described. Thus, we prove that the best choice of embedding model highly depends on the molecular system and that the use of a specific approach as a black box can lead to significant errors and, sometimes, totally wrong predictions.

Assessment of implicit LES modelling for bypass transition of a boundary layer

The implicit LES model recently introduced by Dairay et al. (2017), which is based on numerical dissipation introduced via the discretisation of the viscous term, is assessed for the case of a flat plate boundary layer submitted to external turbulence and undergoing bypass transition. The free stream turbulent fluctuations are generated using a recently proposed linear forcing method adapted to control their intensity and length scale. Two configurations are considered, one with the leading edge of the plate taken into account and one without. LES results for the configuration without leading edge are compared with a DNS, and results for the configuration with leading edge are compared with available experimental and numerical reference data from the literature. Global parameters, unconditional and conditional statistics, as well as Reynolds stress budgets are analysed, and good agreements are obtained with reference data, hence confirming the ability of the model to predict accurately transitional flows. In particular, it is shown that, thanks to its action limited to the smallest resolved scales, the model is only active in the transitional and turbulent regions and therefore does not alter the development of the streaks in the laminar region of the boundary layer.

Development of a more accurate Geant4 quantum molecular dynamics model for hadron therapy

Objective. Although in heavy-ion therapy, the quantum molecular dynamics (QMD) model is one of the most fundamental physics models providing an accurate daughter-ion production yield in the final state, there are still non-negligible differences with the experimental results. The aim of this study is to improve fragment production in water phantoms by developing a more accurate QMD model in Geant4. Approach. A QMD model was developed by implementing modern Skyrme interaction parameter sets, as well as by incorporating with an ad hoc α-cluster model in the initial nuclear state. Two adjusting parameters were selected that can significantly affect the fragment productions in the QMD model: the radius to discriminate a cluster to which nucleons belong after the nucleus–nucleus reaction, denoted by R, and the squared standard deviation of the Gaussian packet, denoted by L. Squared Mahalanobis’s distance of fragment yields and angular distributions with 1, 2, and the higher atomic number for the produced fragments were employed as objective functions, and multi-objective optimization (MOO), which make it possible to compare quantitatively the simulated production yields with the reference experimental data, was performed. Main results. The MOO analysis showed that the QMD model with modern Skyrme parameters coupled with the proposed α-cluster model, denoted as SkM* α, can drastically improve light fragments yields in water. In addition, the proposed model reproduced the kinetic energy distribution of the fragments accurately. The optimized L in SkM* α was confirmed to be realistic by the charge radii analysis in the ground state formation. Significance. The proposed framework using MOO was demonstrated to be very useful in judging the superiority of the proposed nuclear model. The optimized QMD model is expected to improve the accuracy of heavy-ion therapy dosimetry.

Linking Viscosity to Equations of State Using Residual Entropy Scaling Theory

In our previous work (J Chem Eng Data 2021, 66(3):1385–1398), a residual entropy scaling (RES) approach was developed to link viscosity to residual entropy [a thermodynamic property calculated with an equation of state (EoS)] using a simple polynomial equation for refrigerants. Here, we present an extension of this approach to a much wider range of fluids: all pure fluids and their mixtures whose reference EoS and experimental viscosity data are available. A total of 84 877 experimental points for 124 pure fluids and 351 mixtures are collected from 1846 references. The investigated pure fluids contain a wide variety of fluids from light gases with quantum effects at low temperatures to dense fluids and fluids with strong intermolecular association. More than 68.2 % (corresponding to the standard deviation) of the evaluated experimental data agree with the RES model within 3.2 % and 8.0 % for pure fluids and mixtures, respectively. Compared to the recommended models implemented in the REFPROP 10.0 software (the state-of-the-art for thermophysical property calculation), if the dilute gas viscosity is calculated in the same way, our RES approach yields similar statistical agreement with the experimental data while having a much simpler formulation and fewer parameters. To use our RES model, a software package written in Python is provided in the supporting information.Graphical

Simulation of Fault Detection System of Automotive Coil Spring by using Acoustic Method

Due to rising client demand and accessibility to financing, local automotive manufacturer must become cost-competitive against well-known imported brand. As a result, manufacturer is facing more challengers in cost-effectiveness, manufacturing time, as well as quality of their production. Each product that reaches consumer are expected to be excellent in quality, and reliability. However, this could be a problem when quality check (QC) inspections are done using batch sampling method. This method only scans several samples due to complexity of structure and hard to detect fault occurred on the sample. Thus, this study is proposed to find a solution using acoustic method fault detection system to enable 100% automated inspection. This study focusses on automotive coil spring for its sample. Previous study has shown that each different sample conditions has its own distinctive vibration pattern when forced vibrated using same frequency of vibration. The study is done using coil spring model on Ansys simulation software platform that then verified against reference experimental data. Next, the model is used to simulate various fault conditions in order to recognize each different distinctive vibration pattern to reduce consumed cost and time to study the pattern trend. Results to this study shown that healthy and faulted coil spring’s vibration pattern were distinctive clear and easily recognizable. Thus, it is concluded that it is possible to automate 100 % inspection within manufacturing line.

Theoretical Prediction Model of the Explosion Limits for Multi-Component Gases (Multiple Combustible Gases Mixed with Inert Gases) under Different Temperatures

Combustible gases often lead to fire and explosion accidents due to their unsafe characteristics. Furthermore, their explosion limits are influenced by various factors. In the industrial production process, the operating unit is often in a high-temperature environment, and the multi-component gas explosion limits under this condition are difficult to determine. Therefore, it is urgent to have a universal theoretical prediction model to rapidly predict the multi-component gas explosion limits at high temperatures. This paper proposes a theoretical prediction model for the lower explosion limit of multi-combustible gases containing inert gases at different temperatures based on the heat balance equation and radiation heat loss, which can be used to solve the lower explosion limit of the “multiple combustible gases + multiple inert gases” mixture at different temperatures. It solves the explosion limits of methane, ethylene, propane, and propylene mixed with nitrogen with relative errors of 2.66%, 5.98%, 6.82%, and 5.88%, respectively, compared with experimental data. It also obtained theoretically predicted gas explosion limits for methane, ethylene, propane, and propylene mixed with carbon dioxide, with relative errors of 3.24%, 5.13%, 6.19%, and 5.58%, respectively. Although the reference experimental data made the model validation somewhat limited, validation with data for multiple single gases and temperatures still gave the model considerable reliability.

A New Framework for Quantifying Prehistoric Grave Wealth

Quantifying wealth in prehistoric graves is a long-standing unresolved issue. Previous approaches have focused on only one or a few aspects of grave wealth or grave good value, e.g. scarcity, or total number of object types (TOT), thus neglecting other value aspects, or, if combining value parameters, not in a reproducible or transparent way which makes application or comparison with other cases difficult. This study presents a new framework, QuantWealth, for combining different aspects of grave good value such as manufacturing time and skill, case-specific scarcity, prestige, and raw material distance, as well as estimated meat consumption from animal bones, all equally weighted and, in this study, used to perform PCA and calculate a Gini index. This Gini index can then be combined with Gini indices from more general grave wealth measures, including TOT and grave pit depth to form a more balanced Gini index of overall grave wealth. All of these parameters are calculated in a flexible and semi-automated framework based on experimental and prehistoric crafts reference data, which can be continuously updated and fine-tuned, flexibly integrates the respective <em>chaînes opératoires</em>, and which is openly available. As a case study, QuantWealth was applied to a dataset of 81 graves with preserved skeletal remains from 46 sites of the Corded Ware Culture (CWC) in Moravia, Czech Republic. PCA analysis of the grave good measures on these data along with age and sex/gender determination shows that males tend to be overall richer in grave goods than females, that juveniles have the highest meat expenditure, and that young adults rarely have visible meat expenditure.

Parametrization of the PM7 Semiempirical Quantum Mechanical Method for Silver Nanoclusters.

Semiempirical quantum mechanical methods (SEQMs) are widely used in computational chemistry because of their low computational cost, but their accuracy depends on the quality of the parameters. The neglect of diatomic differential overlap method PM7 is among the few SEQMs that contain parameters for Ag, but the experimental reference data was insufficient to obtain reliable parameters in the original parametrization. In this work, we reparametrize the PM7 parameters for Ag to accurately reproduce the ground-state potential energy surfaces of Ag clusters. Since little experimental data is available, we use reference data obtained from the ab initio method CCSD(T). The resulting parameters significantly reduce the errors in binding energies, energies required to displace clusters along their normal modes, and relative energies of isomers compared to the default PM7 Ag parameters.

Flame propagation regimes and critical conditions for flame acceleration and detonation transition for hydrogen-air mixtures at cryogenic temperatures

A series of more than 100 experiments with hydrogen-air mixtures have been performed at cryogenic temperatures from 90 to 130 K and ambient pressure. A wide range of hydrogen concentrations from 8 to 60%H2 in a shock tube of 5-m long and 54 mm id was tested. Flame propagation regimes were investigated for all hydrogen compositions at three different blockage ratios 0, 30% and 60% as a function of initial temperature. Piezoelectric pressure sensors and InGaAs photo-diodes have been applied to monitor the flame and shock propagation velocity of the combustion process. More than 150 experiments at ambient pressure and temperature were conducted as the reference data for cryogenic experiments. The critical expansion ratio σ∗ for an effective flame acceleration to the speed of sound was experimentally found at cryogenic temperatures. The detonability criteria for smooth and obstructed channels were used to evaluate the detonation cell sizes at cryogenic temperatures as well. The main peculiarities of cryogenic combustion with respect to the safety assessment were that the maximum combustion pressure was several times higher and the run-up-distance to detonation was two times shorter compared to ambient temperature independent of lower chemical reactivity at cryogenic conditions.

Evaluation of flow and thermal characteristics for flow through a wall-confined array of pin-fins using large-eddy simulation

In the present work, the flow and thermal characteristics for flow through a wall-confined array of pin-fins are studied using large-eddy simulation (LES). The geometry considered here resembles the trailing-edge portion of a early-stage gas-turbine blade. The wall-confined array of low-aspect ratio cylindrical fins are arranged in a staggered manner, and the direction of the coolant is perpendicular to the axis of the fins. The analysis is performed for a fixed spacing between the fins and for a Reynolds number of 5900. In view of the actual running conditions, large temperature differences, ranging from 25∘C to 300∘C, are considered between the walls and the coolant. Together with this, the effect of higher pressure, ranging from 5 bar to 10 bar, on the cooling performance is analyzed. The numerical solver used is thoroughly validated with the reference experimental and LES data available in the literature. A detailed investigation of the mechanism for heating of the fluid, transport, and diffusion of the heat flux is presented by analyzing Nusselt number, turbulent heat fluxes and vorticity contours. It is observed that, an increase in Nusselt number is due to encapsulation of small-scale vortices around the pin-fin surfaces and a decrease in Nusselt number downstream is due to the lower frequency of high-energy vortex. The localized Nusselt number is higher over the fin surfaces compared to end-walls, and the base vortex is responsible for higher energy extraction at the junction of the pin-fin and the end-walls and its effect increases downstream. The spanwise component of velocity is responsible for localized mixing than the remaining two components, and the coolant gets heated inside the recirculation zone and diffusion of which occurs mostly at the free shear layer. The analysis of higher pressure and temperature difference shows higher Nusselt number at high pressure, whereas higher heat flux at lower pressure.

Uncertainty quantification of phase transition quantities from cluster weighting calculations

In this work, we investigate how uncertainties in experimental input data influence the results of quantum cluster equilibrium calculations. In particular, we focus on the calculation of vaporization enthalpies and entropies of seven organic liquids, compare two computational approaches for their calculation, and investigate how these properties are affected by changes in the experimental input data. It is observed that the vaporization enthalpies and entropies show a smooth dependence on changes in the reference density and boiling point. The reference density is found to have only a small influence on the vaporization thermodynamics, whereas the boiling point has a large influence on the vaporization enthalpy but only a small influence on the vaporization entropy. Furthermore, we employed the Gauss--Hermite estimator in order to quantify the uncertainty in thermodynamic functions that stems from inaccuracies in the experimental reference data for the example of the vaporization enthalpy of (R)-butan-2-ol. We quantify the uncertainty as 30.95 · 10-3 kJ mol-1. In addition, we compare the convergence behavior and computational effort of the Gauss-Hermite estimator with the Monte Carlo approach and show the superiority of the former. Using this study, we present how uncertainty quantification can be applied to examples from theoretical chemistry.

Automated Identification of Linear Machine Tool Model Parameters Using Global Sensitivity Analysis

High-fidelity machine tool models are needed for condition monitoring, machine tool development, and process simulation. To accurately predict the dynamic behavior of their real counterparts, these models have to be identified, meaning that the values for the involved physical model parameters have to be found by comparing the model with measured data from its real counterpart. As of now, this can only be performed automatically for comparably simple models, which are only valid under limiting assumptions. In contrast, parameter identification for predictive high-fidelity models requires cumbersome manual effort in many intermediate steps. The present work addresses this problem by showing how to automatically identify the parameters of a complex structural dynamic machine tool model using global sensitivity analysis. The capability of the proposed approach is demonstrated in two steps for simulated reference data: first, with a model being able to perfectly replicate the reference data, and second, with a disturbed model, which can only approximate the reference because modeling is present. It is shown that, in both cases, globally valid model parameters, which lead to high conformity with the reference data, can be found, paving the way for calibrating models based on experimental reference data in future work.

Towards a transferable nonelectrostatic model for continuum solvation: The electrostatic and nonelectrostatic energy correction model.

In this work, we introduce an electrostatic and non-electrostatic (ENE) correction to the solvation energy based on the Solvent-Accessible Surface Area (SASA) of the solute and the solvent static dielectric constant. The proposed correction was developed for neutral solutes in non-aqueous solvents, considering three different implicit solvation models based on a Self-Consistent Reaction Field treatment of solute-solvent mutual polarization using an Apparent Surface Charge formalism, namely the Integral Equation Formalism of the Polarizable Continuum Model using a continuous surface charge scheme (PCM), the Solvation Model based on solute electron density (SMD), and the generalized Finite-Difference Poisson-Boltzmann (FDPB) model. The proposed correction was parametrized on a diverse training set of 4980 solvation data from the Solv@tum database of experimental solvation energies, and validated on the non-aqueous subset of the MNSOL database comprising 2140 solvation energies. The performances of the proposed ENE models with minimal and extended parameters formulations have been analyzed and the latter variant has been further compared to the widely used Cavity, Dispersion, and Solvent structural effects (CDS) non-electrostatic model originally developed for the SMx family of implicit solvation models. Overall, a very good agreement between the computed solvation energies with the ENE correction and the reference experimental data has been found on both the training and test sets for all continuum solvation models considered. Furthermore, results for the ENE correction are on par with the reference CDS non-electrostatic model for both SMD and FDPB electrostatics, but with the advantage of using a lower number of parameters and thus an improved transferability between different electrostatics treatments.

Processing and interpretation of core-electron XPS spectra of complex plasma-treated polyethylene-based surfaces using a theoretical peak model.

Interpretation of X-ray photoelectron spectroscopy (XPS) spectra of complex material surfaces, such as those obtained after surface plasma treatment of polymers, is confined by the available references. The limited understanding of the chemical surface composition may impact the ability to determine suitable coupling chemistries used for surface decoration or assess surface-related properties like biocompatibility. In this work, XPS is used to investigate the chemical composition of various ultra-high-molecular-weight polyethylene (UHMWPE) surfaces. UHMWPE doped with α-tocopherol or functionalised by active screen plasma nitriding (ASPN) was investigated as a model system. Subsequently, a more complex combined system obtained by ASPN treatment of α-tocopherol doped UHMWPE was investigated. Through ab initio orbital calculations and by employing Koopmans' theorem, the core-electron binding energies (CEBEs) were evaluated for a substantial number of possible chemical functionalities positioned on PE-based model structures. The calculated ΔCEBEs showed to be in reasonable agreement with experimental reference data. The calculated ΔCEBEs were used to develop a material-specific peak model suitable for the interpretation of merged high-resolution C 1s, N 1s and O 1s XPS spectra of PE-based materials. In contrast to conventional peak fitting, the presented approach allowed the distinction of functionality positioning (i.e. centred or end-chain) and evaluation of the long-range effects of the chemical functionalities on the PE carbon backbone. Altogether, a more detailed interpretation of the modified UHMWPE surfaces was achieved whilst reducing the need for manual input and personal bias introduced by the spectral analyst.