Thermal management in Li‐ion batteries is critical for their safety, reliability, and performance. Understanding the thermal conductivity of the battery materials is crucial for controlling the ...temperature and temperature distribution in batteries. This work provides systemic quantitative measurements of the thermal conductivity of three important classes of solid electrolytes (SEs) over the temperature range 150 < T < 350 K. Studies include the oxides Li1.5Al0.5Ge1.5(PO4)3 and Li6.4La3Zr1.4Ta0.6O12, sulfides Li2S–P2S5, Li6PS5Cl, and Na3PS4, and halides Li3InCl6 and Li3YCl6. Thermal conductivities of sulfide and halide SEs are in the range 0.45–0.70 W m−1 K−1; thermal conductivities of Li6.4La3Zr1.4Ta0.6O12 and Li1.5Al0.5Ge1.5(PO4)3 are 1.4 and 2.2 W m−1 K−1, respectively. For most of the SEs studied in this work, the thermal conductivity increases with increasing temperature, that is, the thermal conductivity has a glass‐like temperature dependence. The measured room‐temperature thermal conductivities agree well with the calculated minimum thermal conductivities indicating that the phonon mean‐free‐paths in these SEs are close to an atomic spacing. The low, glass‐like thermal conductivity of the SEs investigated is attributed to the combination of their complex crystal structures and the atomic‐scale disorder induced by the materials processing methods that are typically needed to produce high ionic conductivities.
Thermal management is critical for the safety, reliability, and performance of Li‐ion batteries. Understanding the thermal conductivity of battery materials is crucial for controlling the temperature in batteries. It is found that good crystalline solid electrolytes have glass‐like thermal conductivity due to complex crystal structures and atomic‐scale disorders which are typically necessary for high ion conductivities.
Polymer composites with super-high thermal conductivity have attracted many interests in aerospace and electrical fields. However, traditional polymer composites usually suffer from low thermal ...conductivity because of the high interfacial thermal resistance. Herein, by adopting a multi-dimensional filler composed of micro-silver (AgMP) and nano-silver (AgNP) particles, we prepare an epoxy/Ag composite with the maximum thermal conductivity of 58.3 W/m·K. Based on this, by introducing trace amount (0.12 vol%) of MXene, the thermal conductivity of the epoxy/Ag/MXene composite further increases to 72.7 W/m·K, which is 24.7% higher than that of Ag/Epoxy composites. Both of the super-high thermal conductivity enhancement in epoxy/Ag and epoxy/Ag/MXene composites should be attributed to the unique bridging effect of AgNP particles or MXene flakes. AgNP bridges AgMP via sintering while the MXene flakes bridge AgNP and/or AgMP by the strong interaction between MXene flakes and the Ag particles. The significant effect of the bridging between filler particles on the thermal conductivity of composites is elucidated and verified by FEM simulations. These findings provide new insights into the thermal transport in polymer-based composites and also suggest an approach to prepare polymer composites with super-high thermal conductivity.
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Bi2Se3, as a Te‐free alternative of room‐temperature state‐of‐the‐art thermoelectric (TE) Bi2Te3, has attracted little attention due to its poor electrical transport properties and high thermal ...conductivity. Interestingly, BiSbSe3, a product of alloying 50% Sb on Bi sites, shows outstanding electron and phonon transports. BiSbSe3 possesses orthorhombic structure and exhibits multiple conduction bands, which can be activated when the carrier density is increased as high as ≈3.7 × 1020 cm−3 through heavily Br doping, resulting in simultaneously enhancing the electrical conductivities and Seebeck coefficients. Meanwhile, an extremely low thermal conductivity (≈0.6–0.4 W m−1 K−1 at 300–800 K) is found in BiSbSe3. Both first‐principles calculations and elastic properties measurements show the strong anharmonicity and support the ultra‐low thermal conductivity of BiSbSe3. Finally, a maximum dimensionless figure of merit ZT ∼ 1.4 at 800 K is achieved in BiSb(Se0.94Br0.06)3, which is comparable to the most n‐type Te‐free TE materials. The present results indicate that BiSbSe3 is a new and a robust candidate for TE power generation in medium‐temperature range.
BiSbSe3, as a new promising mid‐temperature thermoelectric material, has an intrinsically low thermal conductivity. Its multiple conduction bands could be activated by heavy Br doping. Collectively, an impressive overall thermoelectric performance was obtained, maximum ZT ~ 1.4 at 800 K in BiSbSe3, which is evolved from Se substitution in Bi2Te3 (Bi2Se3) and followed by Sb substitution (BiSbSe3), and which outperforms them.
This paper describes the development of toroid-based seawater conductivity sensors and instrumentation for 0 to 60 mS/cm conductivity range and 50 bar hydrostatic pressure operational capability ...which is equivalent to 500 metres of ocean depth. Double core toroidal transformer concept was used and investigated for Mn-Zn and Fe based nanocrystalline cores, turns ratio and temperature dependence. Different excitation and sense coil turn numbers were fabricated by keeping the turn's ratio 1:2, 1:4, 1:6 and 1:8. Optimum frequency of Mn-Zn based conductivity sensors with lower and higher turn numbers were observed for turn ratio 1:8 and 1:4 respectively at 120 kHz and obtained voltage responses of 952 and 1567 mV. Fe based Nano crystalline core with turn ratio 1:8 shows an optimum frequency of 70 kHz and giving a voltage difference of 830 mV. Two dimensional polynomials of order 2 were presented for temperature dependence of conductivity for Mn-Zn core based sensors. Sensor responses of Fe based nanocrystalline core sensors in 'lower turn number' configuration with same turn ratio is presented and observed linear temperature dependence compared to Mn-Zn based sensors. The mechanical design and frequency of operation of developed conductivity sensors gives inherent immunity to ASW band of frequency interference. The efficacy of conductivity sensor with measuring electronics and commercial standard sensors profiling was proved experimentally compared up to 500 metres in sea profiling and obtained a root mean square error of 0.42 for profile data.
We studied water uptake variability at the plant scale using a three-dimensional detailed model. Specifically, we investigated the sensitivity of the R-SWMS model under different plant collar ...conditions by comparing computed water fluxes, flow variability, and soil water distributions for different case scenarios and different parameterizations. The relative radial root conductivity and soil hydraulic conductivity were shown to control the plant water extraction distribution. Highly conductive soils promote water uptake but at the same time decrease the variability of the soil water content. A large radial root conductivity increases the amount of water extracted by the root and generates very heterogeneous water extraction profiles. Increasing the xylem conductivity has less impact because the xylem is generally the most conductive part of the system. It was also determined that, due to the different magnitudes of soil and root conductivities, similar one-dimensional sink-term profiles can result in very different water content and flux distributions at the plant scale. Furthermore, an analysis based on soil texture showed that the ability of a soil to sustain high plant transpiration demand cannot be predicted a priori from the soil hydraulic properties only, as it depends on the evaporative demand and on the three-dimensional distributions of the soil/root conductivity ratio and soil capacity, which continuously evolve with time. Combining soil and root hydraulic properties led to very complex one-dimensional sink functions that are quite different from the simple reduction functions usually found in the literature. The R-SWMS model could be used to develop more realistic one-dimensional reduction functions.
Reduced graphene oxide (RGO) films are promising in applications ranging from electronics to flexible sensors. Though high electrical and thermal conductivities have been reported for RGO films, ...existing thermal conductivity data for RGO films show large variations from 30 to 2600 W m−1 K−1. Further, there is a lack of data at low temperatures (<300 K), which is critical for the understanding of thermal transport mechanisms. In this work, a temperature‐dependent study of thermal (10–300 K) and electrical (10–3000 K) transport in annealed RGO films indicates the potential application of RGO films for sensing temperatures across an extremely wide range. The room‐temperature thermal conductivity increases significantly from 46.1 to 118.7 W m−1 K−1 with increasing annealing temperature from 1000 to 3000 K with a corresponding increase in the electrical conductivity from 5.2 to 1481.0 S cm−1. In addition, films reduced at 3000 K are promising for sensing extreme temperatures as demonstrated through the measured electrical resistivity from 10 to 3000 K. Sensors based on RGO films are advantageous over conventional temperature sensors due to the wide temperature range and flexibility. Thus, this material is useful in many applications including flexible electronics and thermal management systems.
The impact of the reduction temperature on electrical and thermal transport is experimentally quantified and theoretically analyzed. Further, the reduced graphene oxide film reduced at 3000 K shows promise for extremely wide‐range flexible temperature sensors.
Coherent Phonon Heat Conduction in Superlattices Luckyanova, Maria N.; Garg, Jivtesh; Esfarjani, Keivan ...
Science (American Association for the Advancement of Science),
11/2012, Volume:
338, Issue:
6109
Journal Article
Peer reviewed
The control of heat conduction through the manipulation of phonons as coherent waves in solids is of fundamental interest and could also be exploited in applications, but coherent heat conduction has ...not been experimentally confirmed. We report the experimental observation of coherent heat conduction through the use of finite-thickness superlattices with varying numbers of periods. The measured thermal conductivity increased linearly with increasing total superlattice thickness over a temperature range from 30 to 150 kelvin, which is consistent with a coherent phonon heat conduction process. First-principles and Green's function-based simulations further support this coherent transport model. Accessing the coherent heat conduction regime opens a new venue for phonon engineering for an array of applications.
Polymers are widely used in daily life, but exhibit low strength and low thermal conductivity as compared to most structural materials. In this work, we develop crystalline polymer nanofibers that ...exhibit a superb combination of ultra-high strength (11 GPa) and thermal conductivity, exceeding any existing soft materials. Specifically, we demonstrate unique low-dimensionality phonon physics for thermal transport in the nanofibers by measuring their thermal conductivity in a broad temperature range from 20 to 320 K, where the thermal conductivity increases with increasing temperature following an unusual ~T
trend below 100 K and eventually peaks around 130-150 K reaching a metal-like value of 90 W m
K
, and then decays as 1/T. The polymer nanofibers are purely electrically insulating and bio-compatible. Combined with their remarkable lightweight-thermal-mechanical concurrent functionality, unique applications in electronics and biology emerge.
In this study, Carbon nanofiber (CNF), Functionalized Carbon nanofiber (F-CNF), Reduced graphene oxide (rGO), and rGo coated over F-CNF (F-CNF/rGO) were produced using Hummers modified method and ...chemical reduction methods as well as a hydrothermal technique. All of which were characterized by SEM, TEM, X-ray Photoelectron Spectrometer, and X-ray diffraction. Stability, density, viscosity, thermal and electrical conductivities of the prepared nanofluids (0.04 vol%) were experimentally obtained. Significant enhancements in thermal and electrical conductivity were obtained. F-CNF/rGO (hybrid) nanofluid showed enhanced thermal conductivity and lower electrical conductivity compared to the other prepared nanofluids. Results showed that the hydrothermal F-CNF/rGO (hybrid) nanofluid could result in better heat transfer compared to conventional heat transfer fluids. Moreover, based on the experimental dataset, an accurate model that simulates the thermophysical properties of nanofluids is created by fuzzy logic. A well-fitting is obtained between the experimental results and the fuzzy model. The suggested numbers for fuzzy models rules were 11, 16, 16 and 16 for density, viscosity, thermal conductivity, electrical conductivity models, respectively. Every fuzzy model has been trained for 50 epochs. The MSE of the fuzzy models' outputs are 1.4379e-07, 0.00011349, 1.0709e-05 and 1.9827e-06 density, viscosity, thermal conductivity and electrical conductivity.
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•Mono and hybrid nanofluids were produced.•Stable nanofluids were obtained for a period of 6 months.•Maximum increase in thermal conductivity was observed in F-CNF/rGO nanofluid.•Hydrothermal F-CNF/rGO (hybrid) nanofluid could result in better heat transfer.•A well-fitting is obtained between the experimental results and the fuzzy model.
•The significant effect of pore distribution and shape on the effective thermal conductivities of porous media are identified.•Five structural descriptors with explicit physical meanings are ...proposed: shape factor, bottleneck, channel factor, perpendicular nonuniformity, and dominant paths.•These descriptors effectively quantify the anisotropy of pore morphology and strongly correlate with effective thermal conductivities.•The proposed descriptors are incorporated into machine learning models to predict the effective thermal conductivity of porous media and show significantly improved accuracy than using porosity alone.
Understanding the thermal transport mechanism in porous media is important for various engineering and industrial applications. The effective thermal conductivity of porous media is known to be related to the morphology of porous structures. However, existing effective medium approaches usually miss the morphology effects, and numerical simulations are expensive and not physically intuitive. Machine learning methods have recently been successful in predicting effective thermal conductivity, but the lack of descriptors limits physical insights. In this work, we investigate structural features that have significant effects on thermal transport in porous media and identify five physics-based descriptors to characterize the structural features: shape factor, bottleneck, channel factor, perpendicular nonuniformity, and dominant paths. These descriptors can effectively quantify the anisotropy of pore morphology and strongly correlate with effective thermal conductivities. The proposed descriptors are incorporated into machine learning models to predict the effective thermal conductivity of porous media, and the results are shown to be fairly accurate. They provide new insights into the thermal transport mechanisms in complex heterogeneous media.
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