Temperature-dependent Properties Research Articles

The analysis of carrier transport mechanism at the interface of BZOPET-GR Schottky contact

Abstract Through the hydrothermal technique, we successfully deposited boron (B)-doped zinc oxide nanorods (ZnO NRs) onto a polyethylene terephthalate (PET)/graphene (GR) flexible substrate, creating a B-ZnO/PET/GR Schottky contact. The ZnO NRs exhibited a well-defined hexagonal structure with a lattice constant size of approximately 0.502 nm, as evidenced by characterization results. X-ray Photoelectron Spectroscopy (XPS) analysis revealed a reduction in defective oxygen content with increasing B ion doping.The current-voltage (I-V) characteristics of the Schottky contacts were systematically investigated over a temperature range of 160-300K. As the temperature increased, the barrier height exhibited an upward trend, while the ideality factor decreased. This behavior was ascribed to barrier inhomogeneity at the Schottky contact interface. Employing a single Gauss distribution function for barrier height, we verified and elucidated this phenomenon, contributing to a comprehensive understanding of the observed temperature-dependent electrical properties.

Dynamic Hybrid Visual-Thermal Multimodal Perception Neuromorphic Devices Based on Defect Modulation of Electrospun Nanofibers

Abstract Neuromorphic devices, inspired by the intricate architecture of the human brain, have garnered recognition for their prodigious computational speed and sophisticated parallel computing capabilities. Vision, the primary mode of external information acquisition in living organisms, has garnered substantial scholarly interest. Notwithstanding numerous studies simulating the retina through optical synapses, their applications remain circumscribed to single-mode perception. Moreover, the pivotal role of temperature, a fundamental regulator of biological activities, has regrettably been relegated to the periphery. To address these limitations, we proffer a neuromorphic device endowed with multimodal perception, grounded in the principles of light-modulated semiconductors. This device seamlessly accomplishes dynamic hybrid visual and thermal multimodal perception, featuring temperature-dependent PPF properties and adaptive storage. Crucially, our meticulous examination of transfer curves, capacitance-voltage (C-V) tests, and noise measurements provides insights into interface and bulk defects, elucidating the physical mechanisms underlying adaptive storage and other functionalities. Additionally, the device demonstrates a variety of synaptic functionalities, including filtering properties, Ebbinghaus curves, and memory applications in image recognition. Surprisingly, the digital recognition rate achieves a remarkable value of 98.8%. These discernments furnish crucial insights for the prospective evolution of intricate neuromorphic systems.

Numerical study of the influence of the geometrical aspect ratio and nanoparticles diameter on forced convection in a micro-channel heat sink of a nanofluid water/CuO based on a Brownian diffusion model

In order to cool electronic equipment with a high efficiency we can use the flow of a nanofluid in a rectangular micro-channel heat sink. The paper reports the results of the study of a hydrodynamically fully developed laminar forced convective heat transfer flow in two different geometries G1and G2. The study is numerical and was achieved using as nanofluid with and a single-phase approach. Calculations were first made with constant thermo-physical properties at and then made using temperature and nanoparticles diameter dependent thermo-physical properties based on a Brownian diffusion model. A three-dimensional conjugate heat transfer model was used and numerical simulations were based on a finite volume method. The simulations were made for a range of Reynolds numbers , for nanoparticle diameter in the range of and for a heat flux through the bottom surface of the heat sinks .The results of thermal and hydrodynamic fields show that nanofluids can provoke an increase in the local and average Nusselt numbers, a decrease of bottom surface local temperature and a slight decrease of the shear stress on the wall, particularly in the case of geometry G2. At the end of the study, the best geometry, volume fraction of nanofluid and nanoparticle diameter to be recommended for cooling were found based on minimum total thermal resistance of the micro-channel heat sink.

Temperature-dependent optical and surface electrical properties of Pb(Zr0.3Ti0.7)O3 /p-GaN film

Understanding the temperature-dependent optical and electrical properties of PZT, a multifunctional ferroelectric thin film with temperature sensitivity, is crucial for its applications. This study systematically investigated the microstructure, optical, and surface electrical features of Pb(Zr0.3Ti0.7)O3 thin film deposited on p-GaN substrate (PZT/p-GaN), with an emphasis on their response to temperature variations. Band gap energy (3.643 eV) and the three interband electronic transitions (3.528 eV, 4.662 eV, 6.582 eV) were extracted from optical measurements, which govern the photoelectron transmission behavior of the PZT/p-GaN. Additionally, we identify three phase-transition temperatures (450 K, 550 K, and 620 K) through temperature-dependent optical behavior analysis. With increasing temperature, the electronic transitions and bandgap show a redshift trend, and the bandgap change follows the O'Donnell equation with a significant electron-phonon coupling coefficient (S = 10.284), revealing a strong electron-phonon coupling effect in PZT/p-GaN. The temperature-dependent kelvin piezoelectric force microscopy (KPFM) shows that the surface potential and work function of PZT/p-GaN exhibit different linear variations over three temperature ranges divided by the phase transition temperature point as a demarcation. Furthermore, we observed that the optical and surface electrical properties exhibit anomalous trends at the phase transition point. These findings offer a theoretical reference for the application of PZT thin films in optoelectronics and electronic devices.

A low-temperature synthesis of strongly thermochromic W and Sr co-doped VO2 films with a low transition temperature

The reversible semiconductor-to-metal transition of vanadium dioxide (VO2) makes VO2-based coatings a promising candidate for thermochromic smart windows, reducing the energy consumption of buildings. We report low-temperature (320 °C) depositions of thermochromic V1−x−yWxSryO2 films with a thickness of 71–73 nm onto 170–175 nm thick Y-stabilized ZrO2 layers on a 1 mm thick conventional soda-lime glass. The developed deposition technique is based on reactive high-power impulse magnetron sputtering with a pulsed O2 flow feedback control allowing us to prepare crystalline W and Sr co-doped VO2 films of the required stoichiometry without any substrate bias or post-deposition annealing. The W doping of VO2 decreases the transition temperature below 25 °C, while the Sr doping of VO2 increases the integral luminous transmittance, Tlum, significantly due to widening of the visible-range optical bandgap, which is consistent with lowering of the absorption coefficient of films. We present the discussion of the effect of the Sr content in the metal sublattice of VO2 on the electronic and crystal structure of V1−x−yWxSryO2 films, and on their temperature-dependent optical and electrical properties. An optimized V0.855W0.018Sr0.127O2 film exhibits a high Tlum = 56.8% and modulation of the solar energy transmittance ΔTsol = 8.3%, which are 1.50 times and 1.28 times, respectively, higher compared with those of the V0.984W0.016O2 film. The achieved results constitute an important step toward a low-temperature synthesis of large-area thermochromic VO2-based coatings for future smart-window applications, as it is easy to further increase the Tlum and ΔTsol by >6% and >3%, respectively, using a 280 nm thick top SiO2 antireflection layer.

A novel tape-free sample preparation method for human osteochondral cryosections for high throughput hyperspectral imaging.

Understanding the osteochondral junction, where non-mineralised cartilage and mineralised bone converge, is crucial for joint health. Current sample preparation techniques are insufficient for detailed spatial hyperspectral imaging analysis. Using the enhanced Kawamoto method, we used the super cryo embedding medium's temperature-dependent properties to transfer high-quality tissue samples onto slides for spatial imaging analysis. We transferred osteochondral samples using a tape-free system and successfully tested them in hematoxylin and eosin (HE), Safranin-O, nanomechanical assessments and nano-Fourier transform infrared (FTIR) mapping. This protocol elucidates the structural and elemental gradients, mechanical characteristics and distinctive biochemical layering, making it a useful tool for analysing biochemical properties' co-distribution in healthy and diseased situations.

Temperature-dependent solid material properties of GRCop-42 for an additively manufactured liquid rocket engine LOx cooling channel

Recent technological developments in the field of Additive Manufacturing (AM) provide a number of opportunities for the utilisation of high-performance copper alloys for aerospace applications. The additively manufactured LOx/LNG DemoP1 aerospike engine demonstrator designed by Pangea Aerospace is a characteristic example based on the Direct Metal Laser Sintering (DMLS) technology. The aerospike engine thrust chamber and LOx cooling channels are manufactured using GRCop-42 material powder, a Cu-Cr-Nb based copper alloy developed by the National Aeronautics and Space Administration (NASA) for the regenerative cooling technology of high thermal demand thrust chambers and nozzles. In the current work temperature-dependent correlations are derived for the density, specific heat capacity at constant pressure and thermal conductivity of the GRCop-42 material. The correlations for the solid material properties are then introduced into the ANSYS Fluent 2023 R2 Computational Fluid Dynamics (CFD) package and their capabilities are investigated for the characterisation of the flow-field characteristics of the LOx flow in the cooling channel. The numerical solution of the coolant flow in the AM cooling channel is compared against experimental data of the DemoP1 engine demonstrator. The main objective of this study is to provide a realistic physical description of the temperature-dependent properties of the AM solid material in high heat flux applications where the material properties are mostly considered as constant in previous studies.

Sensitive multimode luminescence thermometry through CaZnOS:Pb2+/Mn2+ microcrystals

Developing advanced luminescent thermometers that offer various thermometry modes is essential for remote temperature measurement with high precision. In this study, a novel tri-mode optical thermometer was designed using Pb2+ and Mn2+ co-doped CaZnOS microcrystals. The structure, luminescence properties, energy transfer (ET) mechanism, and temperature sensing performance were comprehensively investigated. Dual emission of Pb2+ and Mn2+ was achieved by excitation at 290 or 358 nm. Additionally, ET from Pb2+ to Mn2+ was demonstrated in the CaZnOS host. Based on excellent temperature-dependent optical properties, parameters including luminescence intensity ratio (LIR), coordinates of Commission Internationale de L'Eclairage (CIE), and excitation intensity ratio (EIR) were developed for temperature sensing. The maximum relative sensitivity (Sr) is 2.92% K−1 (303 K) through LIR mode, 0.562% K−1 (324 K) through CIE mode, and 0.879% K−1 (303 K) through EIR mode, respectively. The excellent thermometric performance indicates the rationally designed material has great potential in multimode optical thermometry.

Photoluminescence properties of Li3Sc1-x(BO3)2:xCr3+ phosphors and enhanced near-infrared emission and thermal stability by Yb3+ codoping

Cr3+ activated broadband near-infrared (NIR) emitting phosphors have attracted more attention worldwide as they are strongly expected to be promising light convertors for phosphor-converted NIR light sources for NIR spectroscopy and imaging technologies. Herein, a new broadband NIR emitting phosphor Cr3+-doped Li3Sc(BO3)2 (LSBO) is introduced. Microcrystalline powders of LSBO doped with different Cr3+ concentrations were synthesized by solid state reactions and show an NIR emission extending from 700 to 1100 nm with a peak at 830 nm upon excitation at 460 nm. The structure, concentration and temperature-dependent luminescence properties of LSBO:Cr3+ phosphors were discussed in detail. The optical properties of Cr3+ ions in LSBO were examined in terms of spectroscopic parameters. Moreover, efficient energy transfer from Cr3+ to Yb3+ is leveraged to significantly improve the NIR emission intensity and the thermal stability. The enhancement and energy transfer mechanisms have been discussed in detail. These results open up new ways to realize efficient NIR-emitting materials.

Free vibration behaviour of bio-inspired helicoidal laminated composite panels of revolution under thermal conditions: Multi-output machine learning approach

The present work aims to study the free vibration behaviour of bio-inspired helicoidal laminated composite spherical, toroid, and conical shell panels using a single-output Support Vector Machine (SVM) algorithm trained in the chassis of parabolic shear deformation theory under thermal conditions. Different helicoidal lamination schemes are adopted, such as Fibonacci, semi-circular, exponential, recursive, and linear helicoidal schemes. Temperature-dependent material properties are adopted. The effect of the geometry of the shell, temperature, and lamination scheme on the free vibration behaviour of spherical, toroid, and conical shell panels is studied. Also, the mode shapes are obtained using different multi-output SVM surrogate in which the displacements are obtained at different locations and are predicted to obtain the fundamental mode shape. The trained surrogate model can predict the values of fundamental frequency and mode shapes much faster than the parabolic shear deformation theory.

A hybrid approach portraying the dynamics of free convection condensation around a circular cylinder

We introduce a hybrid framework to model the fluid dynamics of free convection condensation of saturated steam outside a circular cylinder. The liquid film is modeled analytically, and the adjacent vapor flow field is resolved numerically. The model incorporates temperature-dependent thermophysical properties of the condensate. We explore the subtle role of Jakob number (Ja) and Weber number (We) in the two-phase flow and establish the criteria for dynamic similarity of the flow field with two new dimensionless numbers, viz., free-fall Reynolds number and similarity number. For fixed base Prandtl number of the condensate, the increases in the subcooling rate with Ja and the cylinder's surface area to volume ratio with We cause film thickening. We develop a theoretical correlation to predict the average film thickness (δm). We identify entrainment and bypass zones in the vapor flow field demarcated by a separating streamline. The entrainment zone's streamlines converge to the interface, yielding a net condensate drainage. The bypass streamlines never reach the interface and reduce the condensation efficiency. The results show that the tangential velocity is dominant within the liquid film, the radial velocity is dominant within the vapor flow field, and they are of the same order at the interface. We locate the point of flow separation influenced by a surface tension-induced adverse pressure gradient. The location of the flow separation point shifts upstream, and the separating streamlines become steeper with the increase in We. Our investigation reveals the zone of tangential flow reversal near the interface, promoted with increasing We.

Programable shape recovery properties and snap-through instabilities of viscoelastic and shape-memory NS metamaterials

The combination of smart material and mechanical metamaterial has the potential to bring novel properties and additional functionalities, which, however, has been ignored for a long time. This work numerically, experimentally, and analytically examines the negative stiffness (NS) metamaterials based on shape memory polymers (SMPs) with a focus on the tunable and temperature-dependent properties induced by the interaction of material and geometry nonlinearity. A universal discrete model of a series of shape-memory NS metamaterial is developed by separating the bending effect and stretching effect, where the viscoelastic material is described by the generalized Maxwell-Wiechert model, and an SMP constitutive model is proposed based on multiplicative decomposition of the deformation gradient. The mechanical and shape-memory properties influenced by temperature, geometry, material and loading rate are experimentally observed through relaxation tests and cyclic compression tests. Then the discrete model and finite element analysis (FEA) is adopted to examine the novel mechanical responses in a wide range of parameters. Results show that viscoelasticity and loading rate play a significant role in mechanical responses, and tunable load-capacity and stability can be achieved for shape-memory metamaterial. A phase diagram of different stabilities is constructed showing strictly monotonic, S-shaped, and snapping responses. Additionally, repeated compression and recovery performance proves the possibility of reusable applications. This work provides new opportunities for functional metamaterial to obtain programmable shape recovery and mechanical responses.

Fluid and thermal effect on temperature-dependent power increase of electric vehicle's permanent magnet synchronous motor using compound water cooling method

Taking advantage of compound housing water jacket (HWJ) and hollow-shaft water jacket (SWJ) cooling based on the temperature-dependent power of permanent magnet synchronous motor (PMSM) is a solution for enhanced electric vehicle (EV) performance. The fluid and temperature field of a 40 kW PMSM at three typical continuous working points were studied, covering low to high speeds of EVs. The influence of different coolant flowrates on power of motor was obtained by multi-physics field coupling analysis method. The impact of current control modes was also investigated. 3D computational fluid dynamics (CFD) conjugate heat transfer calculation combined with 3D lumped parameter thermal network (LPTN) was adopted to calculate the flow and temperature. Temperature-dependent material properties were taken into consideration in electromagnetic finite element analysis (FEA). The models were modified and validated by experiments. Once compounding SWJ on the basis of a strong HWJ cooling, the PM temperature can continue to decrease over 20 degC. The insensitive characteristic of PM temperature towards SWJ flow rate was observed. Under constant current control mode, 3.8 %, 6 % and 4 % PMSM power enhancement by compound cooling were proved at three typical working points. Under current open-loop, 7 %, 16 %, and 10 % increases with compound cooling were confirmed.

Size-dependent nonlinear dynamics of two-directional functionally graded microbeams in thermal environment under a moving mass

The size-dependent nonlinear dynamics of two-directional functionally graded (2D-FG) microbeams in a thermal environment under a moving mass is studied for the first time in the framework of the refined higher-order shear deformation theory (HSDT) and modified couple stress theory (MCST). The variation of the temperature-dependent material properties in the axial and thickness directions is estimated by the Mori–Tanaka homogenization scheme. Considering the rotary inertia and shear deformation, the nonlinear differential equations of motion, obtained from Hamilton’s principle, are discretized using an enriched beam element. Numerical results determined by the Newmark method in combination with Newton–Raphson iterative procedure confirm the efficiency of the derived beam formulation in predicting the nonlinear dynamics. The enriched beam element, which is derived herein by using hierarchical functions to enrich the conventional shape functions, is capable of furnishing accurate nonlinear dynamic characteristics with fewer elements compared to the conventional one. It is shown that the difference between the dynamic response predicted by the linear analysis and the nonlinear one increases by increasing the temperature, but it decreases by increasing the size scale parameter. The effects of the material gradation, temperature rise and micro-scale parameter on the nonlinear dynamic behavior of the 2D-FG microbeams are studied in detail and highlighted.

Dual-Vibration-Assisted Charge Transport Through Hexabenzocoronene in Single-Molecule Junctions.

Gaining deep understanding and effective regulation of the charge transport mechanism within molecular junctions is essential for the development of electronic devices. In this work, a series of hexabenzocoronene-based single-molecule junctions are successfully constructed, and their temperature-dependent charge transport properties are studied. It is found that rotational vibrations of both benzene and hexabenzocoronene rings are sequentially excited as the temperature increases, and the electron-vibration coupling enhances charge tunneling. In addition, the transition temperature between distinct vibration-assisted tunneling modes and the activation energies showstrong correlations with the molecular vibration frequency and molecular length. This study unveils the distinct dual-vibration-assisted molecular tunneling mechanism, significantly enhancing the ability to precisely control molecular charge transport and develop functional molecular devices.

Interdiffusivity matrices and atomic mobilities in fcc Ni–Fe–Mo alloys: Experiment and modeling

Accurate diffusivities in fcc Ni–Fe–Mo alloys are of significant importance in designing high-quality magnetic alloys. In this work, totally twelve fcc single-phase diffusion couples are assembled to determine the diffusivities of fcc Ni–Fe–Mo alloys at 1373, 1423 and 1437 K. The diffusivity matrices at the intersection compositions of diffusion paths are determined by the Matano-Kirkaldy method. In addition, the diffusivity matrices along the whole composition profiles of individual diffusion couple and the atomic mobilities of fcc Ni–Fe–Mo alloys are evaluated by the numerical inverse approach incorporated in CALTPP program. The reliability of the obtained atomic mobilities is verified by comparing the predicted diffusion behaviors with the experimental ones. Furthermore, applying the presently obtained atomic mobilities in combination with thermodynamic descriptions, the three-dimensional maps of interdiffusivites, activation energy and frequency-factor planes of fcc Ni–Fe–Mo alloys are constructed to display the composition- and temperature-dependent diffusion properties. The presently obtained diffusivities and atomic mobilities of the Ni–Fe–Mo fcc phase are expected to contribute to high-efficiency Ni–Fe–Mo magnetic alloy design.

A data-driven intelligent learning algorithm for simultaneous prediction of aerodynamic heat and thermo-physical property parameters

It is of great importance and challenging to simultaneously determine time-varying aerodynamic heat and temperature-dependent thermo-physical property parameters with high accuracy, for the optimization of thermal protection systems of hypersonic vehicles. However, it is difficult to directly measure these parameters under high temperature conditions. It is an effective way to determine thermo-physical property parameters and aerodynamic heat by solving inverse problems, based on measurable or easily measured transient temperatures. However, the prediction error of these parameters may be too large, if the measurement error is large, due to the thermal inertia. To deal with this issue, an intelligent algorithm is proposed to simultaneously predict the aerodynamic heat and thermo-physical property parameters for the thermal protection systems of hypersonic vehicles, based on the temperature measurement information. It combines a genetic algorithm and a machine learning algorithm, and the genetic algorithm is employed to update the relevant parameters in the neural network. By training the neural network, the relationship among the predicted parameters and transient temperatures could be established. Thereafter, the aerodynamic heat subjected to the outer surface of the aircraft and the temperature-dependent non-linear thermo-physical property parameters could be predicted. Examples are given to verify the present algorithm. The results show that this work provides an accurate and efficient method for simultaneously determining the aerodynamic heat and thermo-physical property parameters for the thermal protection system of a hypersonic vehicle. The prediction errors of aerodynamic heat and thermo-physical property parameters are much smaller than the measurement errors, when there are relatively large measurement errors in the input data.

Similarity transform-based numerical analysis of natural convection over an inclined flat plate using nanofluid*

ABSTRACT Nanofluids serve as a working medium in many state-of-the-art heating and cooling systems, where natural convection is a primary medium of thermal energy transfer. Based on the review of recently published literature, the present study is devoted to heat transfer analysis, based on similarity transformations and numerical solutions. The study aims to provide reliable, predictive analytical expressions for heat transfer coefficients and heat transfer rates in a schematic of the natural convection phenomenon. The objective is to analyse laminar free convection across a stagnant Al2O3-water nanofluid layer, spread over an inclined plane surface and exposed to the ambient. A novel similarity transformation method is applied to laminar boundary layer flow, capable of handling coupled influences of flow parameters, thermal boundary conditions and temperature-dependent thermophysical properties. This analysis also considers the effects of concentration and shape factor of nanoparticles on heat transfer. The physical properties are transformed into equivalent (temperature-dependent) physical property factors, along with similarity transformations of velocity and temperature fields. The fifth-order Runge-Kutta method is used to solve the coupled governing equations. The solutions are compared with predictive formulae for wall temperature gradients, heat transfer rates, and the convection heat transfer coefficient. Calculations based on predictive formulae agree well with published data.

Assessment of Thermal Resistance of Hot Water in Pasteurization.

Pasteurization is a process that eliminates microorganisms and minimizes nutrient loss in fruit juices, thus extending their shelf life. It is effective for juices with a pH range of 3.5-4.6. It involved three computational domains: the bath fluid, the thickness of the container, and the juice-filled container. The temperature-dependent properties of real fruit juices were converted into experimental model equations. They were incorporated into the computational fluid dynamics (CFD) simulation. The governing equations were solved simultaneously in each domain. We activated conjugate heat transfer, allowing heat transport between domains through fluid-solid and solid-fluid interfaces. Simulation results were validated with experimental measurements of time-temperature history at the can's center. Three CFD formulations were used to investigate the thermal resistance of hot water in pasteurization. Three domains were simulated simultaneously in the first approach. In the second method, the bath temperature was directly specified on the inner wall of the sealed container. During the third approach, we deactivated natural convection in a juice-filled container suspended in hot water. The findings indicate that using hot water as a heat source extends the duration by 10 min compared to isothermal conditions on the inner wall, regardless of the type of juices filled in the container.

Comprehensive experimental datasets of quasicrystals and their approximants

Quasicrystals are solid-state materials that typically exhibit unique symmetries, such as icosahedral or decagonal diffraction symmetry. They were first discovered in 1984. Over the past four decades of quasicrystal research, around 100 stable quasicrystals have been discovered. In recent years, machine learning has been employed to explore quasicrystals with unique properties inherent to quasiperiodic systems. However, the lack of open data on quasicrystal composition, structure, and physical properties has hindered the widespread use of machine learning in quasicrystal research. This study involves a comprehensive literature review and manual data extraction to develop open datasets consisting of composition, structure types, phase diagrams, and sample fabrication processes for a wide range of stable and metastable quasicrystals and approximant crystals, as well as the temperature-dependent thermal, electrical, and magnetic properties.