Terms Of Temperature Dependence Research Articles

Variation in the responses of carbon quantum dots (CQDs) synthesized from native coconut husk and coconut husk-derived charcoal

We compared the autoclave method for the synthesis of carbon quantum dots (CQDs) from plain coconut husks and husk-derived charcoal in the current study. Although several publications reported the synthesis of CQDs from the two types of husks, no prior reports were available for direct comparison of the two CQDs. The filtrated CQDs were characterized using Excitation-Emission Matrix (EEM) spectroscopy. In comparison to plain husk, the charcoal material was effective for obtaining high concentrations of CQDs because larger amounts of the charcoal husk could be packed into a vessel for autoclave treatment. EEM provided a thorough evaluation of the correlations between the excitation and emission spectra. CQDs synthesized from charcoal and plain exhibited markedly different EEM profiles. Between the two CQDs, we observed an opposite response of fluorescent (FL) intensity and peak wavelengths to pH variation in the aqueous solvent. In contrast, there was no difference in terms of temperature dependence. As an illustration of biological applications, the quenching of papain enzyme self-FL was also investigated. When papain molecules were combined with CQDs derived from plain husk, significant quenching of the papain self-FL was observed, but this phenomenon was not observed when CQDs derived from charcoal husk were used. Our research clarified the differences of CQDs from two types of coconut husks. The knowledge is helpful to apply the CQDs for various biological applications.

Artificial neural network-based path integral simulations of hydrogen isotope diffusion in palladium

The contribution of nuclear quantum effects (NQEs) to the kinetics and dynamics of interstitial H isotopes in face-centered cubic Pd was intensively investigated using several path-integral techniques, along with a newly developed machine-learning interatomic potential based on artificial neural networks for Pd–H alloys. The diffusion coefficients (D) of protium, deuterium, and tritium in Pd were predicted over a wide temperature range (50–1500 K) based on quantum transition-state theory (QTST) combined with path-integral molecular-dynamics simulations. The importance of NQEs even at high temperatures was illustrated in terms of the characteristic temperature dependence of the activation free energies for H-isotope migration in Pd. This illuminates the overall picture of anomalous D crossovers among the three H isotopes in Pd. In addition, the D of protium in Pd was directly computed using two approximate quantum-dynamics methods based on Feynman’s path-integral theory, i.e. centroid molecular dynamics (CMD) and ring-polymer molecular dynamics (RPMD), in the temperature range 370–1500 K. The D values obtained from the CMD and RPMD simulations were very similar and agreed better with the reported experimental values than the QTST results in this temperature range. Our machine learning-based path-integral calculations elucidate the underlying quantum nature of the ‘reversed S’-type nonlinear behavior of D for the three H isotopes in Pd on the Arrhenius plots.

Degradation kinetics of physicochemical and sensory properties of rice during storage at different temperatures

In this study, we applied Arrhenius kinetic models of physical, chemical, and sensory qualities of rice stored for 1 year at different temperatures and calculated their temperature dependence by analyzing their kinetic parameters and shelf lives. The physicochemical properties—germination rate, seed viability, and fat acidity—and the sensory properties—overall sensory quality, appearance, odor, taste, and texture—were well-fitted to Arrhenius plots (R2 > 0.90) following the first-order kinetic model. For the highest temperature differences, seed viability had the highest temperature dependence in terms of k, t1/2, D value, and shelf life, the highest Q10 and Ea, and lowest z value, followed by germination rate, all sensory characteristics, and fat acidity. Moreover, for these properties, the temperature rise led to an increased degradation rate and decreased shelf life in a logarithmic manner rather than linear. Considering overall sensory quality, shelf lives of 7.83, 2.42, and 0.82 years were observed at temperatures of 10, 20, and 30 °C, respectively. Additionally, we developed predictive equations for shelf life based on storage temperatures (R2 = 0.80–0.96). Our predictive equations and results of degradation kinetics can facilitate design and control of postharvest rice storage systems.

Relationship between network structure and ultimate properties in polyurethane during a chain scission process

To investigate the impact of chain scission on the tensile properties of elastomers, a polyester-based polyurethane was aged in seawater at several temperatures ranging from 40 °C to 90 °C. Before the hydrolysis process, water diffusion was first characterized and described by Fickian behaviour. In terms of temperature dependence, both mass at saturation and water diffusivity followed Arrhenius behaviour. For ageing durations that exceed saturation time, ester bond hydrolysis occurs and leads to chain scission within the polymer network. This chain scission rate could be described using a first-order reaction and followed Arrhenius behaviour with an activation energy of 71 kJ/mol. From a mechanical point of view, hydrolysis leads to large changes in both stress and strain at break. A gradual decrease in stress at break was observed for all ageing temperatures. Nevertheless, strain at break first increases during ageing and then drops off when the crosslink density is below a critical value of 1.25 kg/mol. After considering more than 30 ageing conditions, relationships between the average crosslink density and these ultimate properties were proposed and discussed here.

Mathematical and Circuit Level Analysis Interpretation and Recommendations on Neuron Models

Contrary to von Neumann computer architecture, neuromorphic computing is a biologically inspired method for building several sorts of brain-inspired computers. This computer technology uses silicon neurons and synapses to solve difficult machine learning and AI challenges. The goal of neuromorphic computing is to build a brain-like ability to compute, learn, and adapt. Building an appropriate neuroscience model, establishing a new architecture, modeling new devices, finding new materials for the devices, programming framework, and applications for these neuromorphic devices are major technological challenges. This study covers numerous neuron models from Hodgkin–Huxley to I&F, mathematical equations, circuit level analysis and motivations for neuromorphic computing. Here some of the most useful silicon neuron models are discussed in terms of biological plausibility, computational efficiency, and temperature dependency. This survey shows that more than 52 transistors make up the silicon HH neuron, which occupies less than 0.01[Formula: see text][Formula: see text] and consumes 60[Formula: see text]uW of power. On the other hand, an I&F neuron needs less than 20 transistors, occupies 442[Formula: see text][Formula: see text] and consumes 40[Formula: see text]pW of power.

Simulation of concrete structures deformation affected by alkali–silica reaction considering environmental conditions and multiaxial stress state

In this study, the expansion and deformation of alkali–silica reaction (ASR)-affected concrete structures under natural environment and multiaxial stress state are predicted. The performance of the ASR model proposed in previous research is quantitatively investigated in terms of relative humidity, multiaxial stress, and temperature dependencies based on experimental results. The simulation results indicate that the relative humidity-dependent expansion caused by the ASR can be simulated effectively by slightly modifying the relative humidity threshold in the model. In a simulation focusing on stress dependency, the insufficient consideration of the relationship between compressive stress and ASR gel absorption into pores in the model by previous research resulted in discrepancies between the simulation and experimental results. The performance of the model by previous research in simulating temperature dependency is improved by referring to the relationship between the expansion rate and temperature recorded from specimens exposed to the real environment. An exposure experiment of reinforced concrete (RC) slab on steel girders is simulated using the modified model. The results show that the modified model can reproduce the tendency of three-dimensional deformation of RC slab, while model improvement considering time-dependent and stress-dependent phenomena should be needed for long-term quantitative predictions.

Comparative study of microimage strain sensing system and FBG sensing system for strain measurement

Strain is one of the conventional parameters that evaluate structural performance in the field of bridge health monitoring. Among the various techniques that have been utilized to measure strain, fiber Bragg grating (FBG) sensing system has been broadly applied for long-term strain monitoring in civil engineering, whereas microimage strain sensing (MISS), with its corresponding sensors designed and fabricated, is a new technology for strain measurement. Furthermore, the MISS system is developed to monitor the strain of small and medium span bridges. To verify the performance of the MISS system in strain measurement, a comprehensive and comparative study of the MISS system and FBG strain sensor system is provided. First, the technical features of the two technologies were described. Moreover, more details were expounded in terms of service life, deployment, coverage, cost, and temperature dependence. Then, assisted data comparisons were carried out through component testing. Results show that the proposed MISS system is effective and robust. Therefore, the proposed MISS system will serve as a promising strain measuring alternative in the field of bridge structural health monitoring.

Improved multi-order parameter and multi-component model of polycrystalline solidification

• The grain boundary energy can be predicted even at larger undercoolings by tuning the coefficient of the new introduced interpolation function. • The kinetic coefficient can be adjusted to match the grain boundary migration situation encountered during solid state transition. • A self-consistent nucleation method was successfully incorporated into the model through introduction of noise effects. Accurate nucleation driving force is used and temperature dependent noise amplitude expression is given. • Through employing the parabolic free energy fitting technique, the developed model can be effectively used to study the entire solidification process for a variety of alloys. Temperature dependent phase field parameters selection strategy is proposed and proved. • Two solid phases nucleation of Al-Cu alloy is realized through self-consistent noise term. This approach is suitable to study multiple solid phase solidification phenomena. In this paper, we present an improved multi-order parameter model for multi-component model of polycrystalline solidification. We introduce an interpolation function in the phase field dynamical equation to obtain controllable grain boundary energy at large undercooling. The same interpolation function is also employed in the kinetics coefficient to allow for better control of grain boundary migration. Temperature dependent phase field parameters and noise terms are consistently coupled into the dynamics of a binary system in a manner that allows for quantitative simulations in the thin interface limit. The model is applied to multi-phase solidification in Al-Cu alloy, where a parabolic fitting method is employed to model the free energy of Al-Cu phases and two-phase nucleation is demonstrated in directional solidification.

Improvements for a fully consistent description of the new semi-empirical vapor density model for pure compounds

In chemical engineering, surrogate functions are commonly used in modeling thermodynamic properties of pure compounds because they are often more accurate than equations of state. In 2020, we presented a semi-empirical model describing the vapor density from the reduced triple point temperature to about a reduced temperature of 0.97 with only one temperature-dependent term. However, in many cases the temperature range up to critical temperature is necessary. Therefore, the existing semi-empirical model was extended by another temperature-dependent term. This allows the vapor density to be described from the triple point temperature up to the critical temperature. This model has the additional advantage that it can predict the vapor pressure data from vapor density data. Therefore, this model can also be used for thermodynamic consistency testing. This is not possible with conventionally known surrogate models for describing vapor density. The model was successfully tested using fluoromethane (R41) and difluoromethane (R32) as examples.

Parameter Identification of a Quasi-3D PEM Fuel Cell Model by Numerical Optimization

Polymer electrolyte membrane fuel cells (PEMFCs) supplied with green hydrogen from renewable sources are a promising technology for carbon dioxide-free energy conversion. Many mathematical models to describe and understand the internal processes have been developed to design more powerful and efficient PEMFCs. Parameterizing such models is challenging, but indispensable to predict the species transport and electrochemical conversion accurately. Many material parameters are unknown, or the measurement methods required to determine their values are expensive, time-consuming, and destructive. This work shows the parameterization of a quasi-3D PEMFC model using measurements from a stack test stand and numerical optimization algorithms. Differential evolution and the Nelder–Mead simplex algorithm were used to optimize eight material parameters of the membrane, cathode catalyst layer (CCL), and gas diffusion layer (GDL). Measurements with different operating temperatures and gas inlet pressures were available for optimization and validation. Due to the low operating temperature of the stack, special attention was paid to the temperature dependent terms in the governing equations. Simulations with optimized parameters predicted the steady-state and transient behavior of the stack well. Therefore, valuable data for the characterization of the membrane, the CCL and GDL was created that can be used for more detailed CFD simulations in the future.

Systematical studies of theE1photon strength functions combining the Skyrme-Hartree-Fock-Bogoliubov plus quasiparticle random-phase approximation model and experimental giant dipole resonance properties

Valuable theoretical predictions of nuclear dipole excitations in the whole nuclear chart are of great interest for different applications, including in particular nuclear astrophysics. We present here the systematic study of the electric-dipole $(E1)$ photon strength functions combining the microscopic Hartree-Fock-Bogoliubov plus quasiparticle random-phase approximation (HFB $+$ QRPA) model and the parametrizations constrained by the available experimental giant dipole resonance (GDR) data. For about 10 000 nuclei with $8\ensuremath{\le}\mathrm{Z}\ensuremath{\le}124$ lying between the proton and the neutron drip-lines on nuclear chart, the particle-hole (ph) strength distributions are computed using the HFB + QRPA model under the assumption of spherical symmetry and making use of the BSk27 Skyrme effective interaction derived from the most accurate HFB mass model (HFB-27) so far achieved. Large-scale calculations of the BSk27 + QRPA $E1$ photon strength functions are performed in the framework of a specific folding procedure describing the damping of nuclear collective motion empirically. In particular, three phenomenological improvements are considered in this folding procedure. First, two interference factors are introduced and adjusted to reproduce at best the available experimental GDR data. Second, an empirical expression accounting for the deformation effect is applied to describe the peak splitting of the strength function. Third, the width of the strength function is corrected by a temperature-dependent term, which effectively increases the deexcitation photon strength function at low energy. The theoretical $E1$ photon strength functions as well as the extracted GDR peaks and widths are comprehensively compared with available experimental data. A relatively good agreement with data indicates the reliability of the present calculations. Eventually, the astrophysical rates of $(n,\ensuremath{\gamma})$ reactions for all the 10 000 nuclei with $8\ensuremath{\le}Z\ensuremath{\le}124$ lying between the proton and the neutron drip lines are estimated using the present $E1$ photon strength functions. The resulting reaction rates are compared with the previous BSk7 + QRPA results as well as the Gogny-HFB + QRPA predictions based on the D1M interaction.

Temperature-dependent structure of 1-propanol/water mixtures: X-ray diffraction experiments and computer simulations at low and high alcohol contents

Aqueous mixtures of 1-propanol have been investigated by high-energy synchrotron X-ray diffraction upon cooling. X-ray weighted total scattering structure factors of 6 mixtures, from 8 mol% to 89 mol% alcohol content, as well as that of pure 1-propanol are reported from room temperature down to the freezing points of the liquids. Molecular dynamics simulations have been performed, in order to interpret measured data. The all atom OPLS-AA potential model was used for 1-propanol, combined with both the SPC/E and the TIP4P/2005 water models: both combinations provide a semi-quantitative description of the measured total structure factors at low and high alcohol contents, while the agreement is qualitative for the mixture with 71 mol% of 1-propanol. From the simulated particle configurations, partial radial distribution functions were calculated. Furthermore, detailed description of the hydrogen bonded network is provided, in terms of hydrogen bond numbers, analysis of proton donor–acceptor ratios, size distributions of hydrogen bonded clusters and ring size statistics. Strong temperature dependence of the percolation threshold, as well as of the participation of the number of doubly hydrogen bonded molecules in cyclic entities, has been found for the mixture with 89 mol% of 1-propanol. Above an alcohol content of 20 mol%, 5-fold rings are the most frequent cyclic entities, with a strong temperature dependence in terms of the number of rings.

Bouncing drop impingement on heated hydrophobic surfaces

We extend a diffuse interface phase-field method for two-phase flow simulations so as to include interfacial heat transfer and the thermal Marangoni effect. The set of governing equations hold non-standard terms, which originally stem from the underlying variational consideration of the total free energy of the two-phase system. It consists of the coupled Cahn-Hilliard Navier-Stokes equations with a temperature-dependent mixing energy term and a temperature transport equation implemented in the OpenFOAM framework. The underlying solver phaseFieldFoam is validated for the test cases of thermocapillary convection in a two-fluid-layer and thermocapillary migration of a drop.In the main part of the paper, hydrodynamics and heat transfer of a droplet impinging on a heated hydrophobic surface with subsequent bouncing are studied in detail. By comprehensive simulations, the effects of impact velocity, droplet diameter (in mm range) and substrate wettability (contact angle) are investigated. The numerical results for spreading ratio, wall contact time and cooling effectiveness are found to compare well with experiments indicating that the developed code is well suited for heat transfer simulation in two-phase flow. For the maximum spreading ratio, a new generalizing correlation is proposed which models the kinetic energy and energy losses at maximum spreading by two coefficients, which are determined from simulation results. A new correlation is also proposed for the contact time, which takes into account surface wettability. For the time evolution of drop mean temperature, a crossover is observed when comparing simulations with constant and temperature-dependent surface tension, indicating that the inclusion of Marangoni effects increases both, the heat transfer between drop and wall during spreading and the heat transfer between drop and surrounding air after rebound.

The influence of variable emissivity on lava flow propagation modeling

Modeling lava flow propagation is important to determine potential hazards to local populations. Thermo-rheological models such as PyFLOWGO track downflow cooling and rheological responses for open-channel, cooling-limited flows. The dominant radiative cooling component is governed partly by the lava emissivity, which is a material property that governs the radiative efficiency. Emissivity is commonly treated as a constant in cooling models, but is shown here to vary with temperature. To establish the effect of temperature on emissivity, high spatiotemporal, multispectral thermal infrared data were acquired of a small flow emplaced from a tumulus. An inverse correlation between temperature and emissivity was found, which was then integrated into the PyFLOWGO model. Incorporating a temperature-dependent emissivity term results in a ∼5% increase in flow length and < 75% lower total cumulative heat flux for the small flow. To evaluate the scalability of this relationship, we applied the modified PyFLOWGO model to simulations of the 2018 Lower East Rift Zone fissure 8 flow, emplaced between May 27 and June 3. Our model improves the emplacement match because of the ~ 30% lower heat flux resulting in a ∼7% longer flow compared to modeling using a constant emissivity (0.95). This 5–7% increase in length prior to ocean entry, realized by an accurate temperature-dependent emissivity term, is critical for developing the most accurate model of future flow hazard assessments, particularly if population centers lie in the flow’s path.

Casimir Interaction between a Plane and a Sphere: Correction to the Proximity-Force Approximation at Intermediate Temperatures

We consider the Casimir interaction energy between a plane and a sphere of radius R at finite temperature T as a function of the distance of closest approach L. Typical experimental conditions are such that the thermal wavelength λT=ℏc/kBT satisfies the condition L≪λT≪R. We derive the leading correction to the proximity-force approximation valid for such intermediate temperatures by developing the scattering formula in the plane-wave basis. Our analytical result captures the joint effect of the spherical geometry and temperature and is written as a sum of temperature-dependent logarithmic terms. Surprisingly, two of the logarithmic terms arise from the Matsubara zero-frequency contribution.

Correlation between kinetic fragility and Poisson's ratio from analysis of data for soft colloids

We consider the link between fragility and elasticity that follows from the analysis of the data for a set of soft colloid materials consisting of deformable spheres reported by [Mattsson et al., Nature, 2009, 462, 83]. The present work makes a quantitative analysis through an explicit definition for fragility index m in terms of density dependence, extending the corresponding formula of m for molecular systems in terms of temperature dependence. In addition, we fit the data for the high-frequency shear modulus for the respective soft-colloid to a corresponding theoretical expression for the same modulus. This expression for the elastic constant is in terms of the corresponding pair correlation function for the liquid treated as of uniform density. The pair correlation function is adjusted through a proper choice of the parameters for the two body interaction potential for the respective soft-colloid material. The nature of correlation between the fragility and Poisson ratio observed for the soft colloids is qualitatively different, as compared to the same for molecular glasses. The observed link between fragility of a metastable liquid and its elastic coefficients is a manifestation of the effects of structure of the fluid on its dynamics. The present work thus analyses the data on soft colloids and by introducing definitions from statistical mechanics obtains a correlation between kinetic fragility and Poissons's ratio for the soft material.

A Variational Principle for the Steady-State Heat Transfer Process in a Rigid Continuous Mixture

The subject of this paper is the steady-state heat transfer process in a rigid mixture with N continuous constituents, each of them representing a given continuous body. A continuous mixture consists of a convenient representation for bodies composed by several different materials or phases, in which the actual interfaces do not allow an adequate Classical Continuum Mechanics approach, once that the boundary conditions make the mathematical description of the problem unfeasible (as for instance in reinforced concrete, polymer strengthened concrete, and porous media). The phenomenon is mathematically described by a set of N partial differential equations coupled by temperature-dependent terms that play the role of internal energy sources. These internal energy sources arise because, at each spatial point, there are different temperatures, each one associated with one constituent of the mixture. The coupling among the partial differential equations arises from the thermal interchange among continua in a thermal nonequilibrium context (different temperature levels). In this work, it is presented a functional whose minimization is equivalent to the solution of the original steady-state problem (variational principle). The features of this functional give rise to proofs of solution existence and solution uniqueness. It is remarkable that, with the functional to be proposed here, instead of solving a system of N coupled partial differential equations, we need to look only for the minimum of a single functional.

Metadynamics simulations of strontium-vacancy diffusion in SrTiO3

The sluggish diffusion of strontium vacancies in the perovskite-oxide ${\mathrm{SrTiO}}_{3}$ was studied by means of classical metadynamics simulations. Two different mechanisms were examined: the migration of an isolated strontium vacancy and the migration of a strontium vacancy in a defect associate with an oxygen vacancy. Combining activation Gibbs energies of migration with the appropriate temperature-dependent pre-exponential terms, we obtained diffusivities of strontium vacancies by the two mechanisms for the temperature range $1000\ensuremath{\le}T/K\ensuremath{\le}2000$. Comparisons with experimental data (where available) yield excellent agreement, both in terms of the effective activation enthalpy of migration as well as the absolute rate of diffusion. In this way we demonstrate the ability of classical metadynamics simulations to predict diffusion coefficients quantitatively for extremely slow-moving defects in oxides, and we highlight the complexity of cation diffusion in perovskite materials.

Experimental insight into the third‐order intercepts and nonlinear distortion of GaN HEMTs

This research is about investigating the third-order intercept point (TOI) and nonlinear distortion level (NDL) for two GaN HEMTs of different gate lengths with temperature and frequency. As a multi-biasing, input power, frequency and temperature-dependent term; the TOI point and as well as the nonlinear distortion level are particular figures merit relevant to the third-order intermodulation distortion (IMD3) product. The primary results are the output referenced TOI reduced whereas the input referenced TOI raised as the frequency goes higher and the lower gated device exhibits a bit greater magnitude. Over the temperature range measured; the magnitude of TOI and nonlinear distortion considerably changed in accordance to the performance of third order intermodulation distortion (IMD3) component. This investigation of TOI is used to determine what extent distortion is generated, and comparing that to the entryway of the antenna provides a clear strategy for determining if the spec can be met or not. However, distortion level investigation is a critical point to choose the best biasing preference with the device's inlet measurements to establish a solution that fits with the intended usage.

From universal profiles to universal scaling laws in X-ray galaxy clusters

As the end products of the hierarchical process of cosmic structure formation, galaxy clusters present some predictable properties, like those mostly driven by gravity, and some others more affected by astrophysical dissipative processes that can be recovered from observations and that show remarkable universal behaviour once rescaled by halo mass and redshift. However, a consistent picture that links these universal radial profiles and the integrated values of the thermodynamical quantities of the intracluster medium, also quantifying the deviations from the standard self-similar gravity-driven scenario, has to be demonstrated. In this work we use a semi-analytic model based on a universal pressure profile in hydrostatic equilibrium within a cold dark matter halo with a defined relation between mass and concentration to reconstruct the scaling laws between the X-ray properties of galaxy clusters. We also quantify any deviation from the self-similar predictions in terms of temperature dependence of a few physical quantities such as the gas mass fraction, the relation between spectroscopic temperature and its global value, and, if present, the hydrostatic mass bias. This model allows us to reconstruct both the observed profiles and the scaling laws between integrated quantities. We use the Planck Early Sunyaev-Zeldovich sample, a Planck-selected sample of objects homogeneously analysed in X-rays, to calibrate the predicted scaling laws between gas mass, temperature, luminosity, and total mass. Our universal model reproduces well the observed thermodynamic properties and provides a way to interpret the observed deviations from the standard self-similar behaviour, also allowing us to define a framework to modify accordingly the characteristic physical quantities that renormalise the observed profiles. By combining these results with the constraints on the observed YSZ − T relation we show how we can quantify the level of gas clumping affecting the studied sample, estimate the clumping-free gas mass fraction, and suggest the average level of hydrostatic bias present.