Wide Temperature Research Articles

Garnet-based solid state batteries benefitting from an ionic/electronic mixed conductive interface constructed by lithiation of porous FeS2

Garnet-based solid-state lithium metal batteries are considered as the potential candidates for the next-generation energy storage systems due to their high energy density, wide operating temperature, and high safety. However, the poor wettability of the lithium metal anode/garnet interface, the large interface resistance, and the risk of lithium dendrites growing and even penetrating electrolytes during cycling limit the practical application of garnet-based solid-state lithium metal batteries. In this work, a porous network FeS2 with an amorphized structure is prepared by using the solvothermal method and used as the Li/garnet interface modification layer. The porous FeS2 can be in situ converted into a Li2S/Fe mixed conductive layer by the thermal lithiation of molten metallic lithium. This mixed conductive layer can significantly reduce the interface resistance, ensure the close contact between Li and garnet, and inhibit the growth of lithium dendrites. The interface resistance of the modified Li/FeS2-LLZTO (LLZTO is Li6.5La3Zr1.5Ta0.5O12) interface at 60 °C is as small as 15.20 Ω cm2. The ionic conductivity of fully lithiated FeS2 is estimated to be 1.58 × 10−6 S cm−1 at room temperature. The Li/FeS2-LLZTO/Li symmetrical cell can cycle stably for more than 400 h at a high current density of 400 μA cm−2, with the voltage polarization of only about 25 mV, and can withstand a larger current density of 600 μA cm−2 without the polarization exceeding 50 mV. These results demonstrate the feasibility of in situ lithiation of porous iron sulfide into a mixed ion/electron conductive layer as a solid-state garnet interface modification strategy and provide the new interface method for the development of high-performance solid-state lithium metal batteries.

Interphase Engineering via Solvent Molecule Chemistry for Stable Lithium Metal Batteries

AbstractLithium metal battery has been regarded as promising next‐generation battery system aiming for higher energy density. However, the lithium metal anode suffers severe side‐reaction and dendrite issues. Its electrochemical performance is significantly dependant on the electrolyte components and solvation structure. Herein, a series of fluorinated ethers are synthesized with weak‐solvation ability owing to the duple steric effect derived from the designed longer carbon chain and methine group. The electrolyte solvation structure rich in AGGs (97.96 %) enables remarkable CE of 99.71 % (25 °C) as well as high CE of 98.56 % even at −20 °C. Moreover, the lithium‐sulfur battery exhibits excellent performance in a wide temperature range (−20 to 50 °C) ascribed to the modified interphase rich in LiF/LiO2. Furthermore, the pouch cell delivers superior energy density of 344.4 Wh kg−1 and maintains 80 % capacity retention after 50 cycles. The novel solvent design via molecule chemistry provides alternative strategy to adjust solvation structure and thus favors high‐energy density lithium metal batteries.

Interphase Engineering via Solvent Molecule Chemistry for Stable Lithium Metal Batteries.

Lithium metal battery has been regarded as promising next-generation battery system aiming for higher energy density. However, the lithium metal anode suffers severe side-reaction and dendrite issues. Its electrochemical performance is significantly dependant on the electrolyte components and solvation structure. Herein, a series of fluorinated ethers are synthesized with weak-solvation ability owing to the duple steric effect derived from the designed longer carbon chain and methine group. The electrolyte solvation structure rich in AGGs (97.96 %) enables remarkable CE of 99.71 % (25 °C) as well as high CE of 98.56 % even at -20 °C. Moreover, the lithium-sulfur battery exhibits excellent performance in a wide temperature range (-20 to 50 °C) ascribed to the modified interphase rich in LiF/LiO2. Furthermore, the pouch cell delivers superior energy density of 344.4 Wh kg-1 and maintains 80 % capacity retention after 50 cycles. The novel solvent design via molecule chemistry provides alternative strategy to adjust solvation structure and thus favors high-energy density lithium metal batteries.

Temperature and Strain Rate Related Deformation Behavior of UHMWPE Fiber-Reinforced Composites.

As they possess the qualities of high specific strength, high specific modulus, high specific energy absorption, and excellent designability, ultra-high molecular weight polyethylene (UHMWPE) fiber-reinforced composites have gradually replaced traditional materials such as ceramics and steel plates as the main ballistic protection materials. Using an improved test method, the uniaxial tensile tests of UHMWPE fiber-reinforced composites at two strain rates of 10-4 s-1 and 10-2 s-1 and a temperature range from -20 °C to 80 °C are carried out to study the effects of strain rate and temperature on the tensile behavior of UHMWPE fiber-reinforced composites. The experimental results indicate that the tensile responses exhibit nonlinear characteristics and the sensitivity of strain rate and temperature. The yield strength and modulus decrease with increasing temperature and increase with the increase in strain rate. A phenomenological viscoelastic constitutive model composed of a nonlinear spring and a nonlinear Maxwell element is proposed to characterize the temperature and strain rate dependent deformation behavior of UHMWPE fiber-reinforced composites before yielding. The results show that the model can accurately predict the tensile nonlinear viscoelastic responses of UHMWPE fiber-reinforced composites before yielding over a wide temperature range under quasi-static loading.

Analysis of the Cooperation of a Compressor Heat Pump with a PV System

The decarbonization of heating systems is one of the present political and legislative directions of the European Union and its Member States. The main activities concern the energy performance of buildings and energy efficiency. The mentioned UE directives are the basis for the financial support of high-emission fossil fuel thermal energy source replacement with emission-free ones, in particular heat pumps. Other aspects are the support of PV installations and the thermal insulation of buildings. 85% of EU buildings were built before 2000, and among those, 75% have poor energy performance. Therefore, a significant number of buildings have only high-temperature wall radiators, and this was a motivation to prepare this article. The main innovation of this research was a new theoretical design of a high-temperature heat pump based on ecological refrigerants. The presented solution allows wall radiators to receive a hot water supply with temperatures of up to 85 °C during external temperatures of up to −20 °C. Typical heat pumps do not have these kinds of parameters, so the authors decided to verify the possibility of operating this device in such a wide temperature range. Another important aspect was the analysis of PV support. Finally, this paper investigates the possibility of heating an energy-efficient house with the newly designed high-temperature heat pump. Depending on the location in Poland, i.e., Suwałki, Warsaw, and Wrocław, the total electric energy supplied to the compressors was 2538–3364 kWh. The energy provided by the PV to supply power to the compressors is 482–570 kWh. The achieved PV energy self-consumption is 16.9–19.0%. The Seasonal Coefficient of Performance (SCOP) of the heat pump is 1.825–2.038 without PV and 2.515–2.970 with PV.

Multifunctional Zincophilic Hydrogel Electrolyte with Abundant Hydrogen Bonds for Zinc-Ion Capacitors and Supercapacitors.

The new-generation flexible Zn-ion capacitors (ZICs) require multifunctionality and environmental adaptability for practical applications. This essentially means that hydrogel electrolytes are expected to possess superior mechanical properties, temperature resistance, and tunable interface properties to resist flexibility loss and performance degradation over a wide operating temperatures range. Herein, a multifunctional polyzwitterionic hydrogel electrolyte (PAM/LA/PSBMA) with wide operating temperatures, excellent tensile ability, high water retention, and self-adhesion is designed. Molecular dynamics simulations and experimental results show that polar functional groups (-COO-, -SO3-, -C═O, and -NHCO-) in the hydrogel can form abundant hydrogen bonds with water molecules, which can destroy the original hydrogen bonds (HBs) network between the water molecules and have a low freezing point. It can also form coordination with Zn2+, so that the deposition of Zn2+ electric field homogenization effectively alleviates the growth of Zn dendrites. On this basis, the constructed Zn//Zn cell can be stably cycled 290 h at 10 mA cm-2 (1 mA h cm-2). The constructed ZICs and supercapacitor have a high specific capacitance, excellent energy density, good ionic conductivity, and long cycling stability. This study provides guidance on molecular design for the development of integrated multifunctional smart electronic devices that are environmentally adaptable, resistant to drying, and highly flexible.

A Room‐Temperature Curing Plant Protein‐Based Adhesive with High Strength and Flame Retardancy for Heat‐Free Adhesion

AbstractPlant protein‐based adhesives are gaining traction owing to their low cost and eco‐friendliness. However, achieving flame retardancy and long‐term water resistance in them under room‐temperature curing conditions remains a challenge due to the hydrophilicity and low reactivity of plant proteins. Herein, a novel adhesive synthesized from soybean meal (SM), activated sodium alginate (aSA), nano‐hydroxyapatite (nHA), and polyamidoamine‐epichlorohydrin (PAE) resin addresses this challenge. aSA as a reactive bio‐based cross‐linker formed covalent cross‐linking structures with SM matrix at room temperature, while the nHA‐induced biomineralization and PAE‐constructed supramolecular cross‐linking promote water drainage from the adhesive, preventing water erosion of the adhesive structure. The developed adhesive shows versatility across multiple substrates, with its wet shear strength on wood reaching 0.76 MPa, surpassing that of the commercial aldehyde‐based adhesive. The adhesive is effective over a wide temperature range from room temperature to 150 °C due to the reactivity of the PAE resin above 60 °C. Moreover, it exhibits excellent flame retardancy (limiting oxygen index of 31.2%) owing to its dense structure and the abundance of N‐containing and P‐containing components. This work is expected to break the monopoly of petroleum‐based adhesives in the realm of room‐temperature adhesives.

Predicting thermophysical properties of molten salts in the MgCl2-NaCl-KCl-LiCl system with a shell-model potential

Ternary eutectic salts composed of MgCl2, NaCl, and KCl, referred to as MNK salts, have recently emerged as promising candidates as high-temperature heat transfer fluids and thermal energy storage media. In this study, we performed classical molecular dynamics (MD) simulations to predict the densities, specific heat capacities, viscosities, and ionic self-diffusivities for MNK salts over a wide temperature range. The impact of LiCl additive on their thermophysical properties was also investigated. To capture the electronic polarization of Cl anions by neighboring cations, we developed a novel shell-model potential using the force-matching method and a dataset of ab initio calculated interatomic forces. Our extensive MD simulations predict structure and properties for pure salts and binary/ternary salt mixtures in the MgCl2-NaCl-KCl-LiCl system in overall good agreement with available experimental and theoretical data, which corroborates the accuracy and reliability of our developed potential.

Benchmarking core temperature forecasting for lithium-ion battery using typical recurrent neural networks

One of the factors hindering the scaled application of lithium-ion batteries is their thermal safety issues. Real-time monitoring of core temperature holds promise in alleviating this concern. However, calibrating individual models for thousands of battery cells poses challenges and leads to big data issues. The maturing and rapidly advancing artificial intelligence technologies hold promise in addressing the task of core temperature prediction. In this study, we conduct a benchmark test using typical recurrent neural networks for core temperature prediction. The test encompasses three main aspects: data acquisition, data processing, and data analysis. Firstly, we conduct dynamic battery tests across a wide temperature range on a custom-built experimental platform. Subsequently, we employ big data techniques for data pre-processing, including filtering, normalization, and sliding window methods. Next, hyperparameter optimization is then performed using the Bayesian optimization with Tree-structured Parzen Estimator, followed by K-fold cross validation. Consequently, we obtain three optimal performing models based on typical recurrent neural networks. Finally, we extensively compare these models in terms of performance and complexity. According to the results, all data-driven methods achieve satisfactory model performance, with RMSE within 0.17 °C and MAE within 0.15 °C. Among the models with similar predictive performance conditions, gated recurrent unit exhibits the lowest model complexity and faster training speed. Meanwhile, we also validate the portability and generalizability of the forecasting models. This study lays the foundation for future research in this area and can provide guidance for engineering practical applications to ensure the safe operation of battery energy storage systems.

Sustainable Snail‐Inspired Bio‐Based Adhesives with Ultra‐High Adhesion

AbstractAdhesives play a crucial role in modern everyday applications, prompting a growing environmental consciousness regarding their source, composition, utilization, and disposal. Sustainability concerns are frequently generated due to the complex or energy‐intensive manufacturing processes in the production of conventional water‐based adhesives. Here, a coacervate‐based snail‐inspired solvent‐free adhesive (SFA) is engineered by strategically modulating electrostatic interactions and molecular entanglement of two polypeptides under environmentally friendly conditions. The SFA has a record‐breaking adhesion strength of 28 MPa on ceramics, setting a new standard for bio‐based adhesives. The SFA demonstrates robust adhesion performance across a wide temperature ranging from −150 to 300 °C and allows for reusability without compromising adhesion properties. Moreover, it can be easily removed using a non‐toxic alkaline solution. The study presents a promising opportunity for developing high‐performance, reusable adhesives made from renewable materials suitable for industrial applications, relics repair, and even spacecraft processing.

Phase-field simulation and machine learning of low-field magneto-elastocaloric effect in a multiferroic composite

Achieving appreciable elastocaloric effect under low external field is critical for solid-state cooling technology. Here, a non-isothermal Phase-Field Model (PFM) coupling martensitic transformation with mechanics, heat transfer and magnetostrictive behavior is proposed to simulate Magneto-elastoCaloric Effect (M-eCE) that is induced by magnetic field in a multiferroic composite (e.g., Magnetostrictive-Shape Memory Alloys (MEA-SMA) composite). In the PFM, a nonlinear constitutive hyperbolic tangent model is utilized to model the macroscopic magnetostrictive behavior of MEA, and the heat transfer coupled with phase transformation is employed to calculate the adiabatic temperature change (ΔTad) during M-eC cooling cycles. The influences of magnetic field, geometrical dimension, and ambient temperature on ΔTad are comprehensively investigated. Machine Learning (ML) is further conducted on the database from PFM simulations to accelerate the prediction and design of MEA-SMA composite with an improved ΔTad. It is found that a large ΔTad of 10–14 K and a wide working temperature window of 30 K can be achieved under ultra-low magnetic field of 0.15–0.38 T by optimizing the composite’s geometrical dimension. The present work combining PFM and ML for evaluating M-eCE provides a theoretical framework for the optimization of M-eC cooling devices, and is also potentially extended to other multicaloric effects (e.g., electro-elastocaloric effect).

Electrical actuation of single-crystal diamond MEMS resonators at high temperatures

Achieving efficient low-voltage actuation of microelectromechanical system (MEMS) resonators in high-temperature environments poses a difficult topic due to the thermal interference and the risk of high-temperature failure. In this work, the single-crystal diamond (SCD) resonators fabricated through the ion implantation-assisted lift-off (IAL) technique exhibit a SCD-on-SCD cantilever structure. We propose an electrical actuation system based on the electrostatic effect specifically designed for SCD MEMS resonators with a low radio-frequency amplitude of ∼ 100 mV. The SCD resonators demonstrate stable and efficient actuation across a wide temperature range, from room temperature to 500 °C. Importantly, the actuation voltage exhibits little impact on the resonance frequency and the Q factor of the resonator. The SCD resonator showcases exceptional thermal stability in resonance frequency, with a low temperature coefficient of frequency (TCF) below −12 ppm/°C up to 500 °C. The developed actuation scheme holds tremendous potential as a robust platform for realizing SCD MEMS devices, particularly in applications requiring high integration at high temperatures.

Efficient ionic transport over wide temperature range in oxide enabled by interfacial reaction of molten carbonate

The development of solid oxide fuel cell (SOFC) operated at low and intermediate temperatures is limited by the poor performance of inorganic ionic conductors. Oxide-based ion conductors have attracted much attention due to their excellent stability and tunable ion conduction behavior. In this study, we propose a new approach for the construction of regulated ionic transport pathways in a composite oxide ionic conductor made of WO3/ZrO2 (WZ) and (Li0.68K0.32)2CO3. The interfacial reaction between WO3/ZrO2 and (Li0.68K0.32)2CO3 is used to enhance the interaction between the oxide and carbonate interfaces and introduce hydrophilic phases for water retention, thus achieving ultra-high ionic conductivity of the oxide/carbonate composites at low and intermediate temperatures. The optimal ionic conductor, 13WZ-30(Li0.68K0.32)2CO3 (13WZ-30C), has a superior ionic conductivity of 25.8-6.28 mS cm−1 from room temperature to 250 °C. The ion conduction mechanism of the composite is investigated. This study emphasizes the significance of interfacial chemistry regulation between oxides and carbonates for achieving superior ion conduction performance.

Tunnel-Structured Phosphate Exhibiting High Proton Conductivity and Thermal Stability over a Wide Intermediate Temperature Range.

For the practical application of fuel cells in vehicles, it is a challenge to develop a proton solid electrolyte that coexhibits thermal stability and high proton conductivity at wide intermediate temperatures. Here, we report on the tunnel structured phosphate KNi1-xH2x(PO3)3·yH2O, which exhibits high proton conductivity at room temperature up to 500 °C, with the conductivity value reaching 1.7 × 10-2 S cm-1 at 275 °C for x = 0.18. This material, composed of the smallest cations that form the tunnel framework with face-shared (KO6) and (NiO6) chains and PO4 tetrahedral chains, retained the rigid framework up to 600 °C. Two oxygen sites of water molecules located adjacent to each other along the PO4 tetrahedral chains in the tunnel provided the proton conduction pathway. The sample maintained a conductivity of 5.0 × 10-3 S cm-1 for 10 h at 150 °C while changing the measurement atmosphere to a N2 gas flow, a 4% H2-96% Ar gas flow, and an O2 gas flow. The conductivity value at x = 0.18 obtained from the DC measurement was in the order of 10-6 S cm-1, close to the instrument's measurement limit. These results demonstrate that tunnel phosphate has potential as a proton solid electrolyte for next-generation fuel cells.

Dependence of mechanical properties on the phase composition of intercritically annealed medium-Mn steel as the main competitor of high-strength DP steels

Depending on the alloy composition, intercritical annealing may provide different phases in the microstructure. For low-alloyed dual-phase (DP) steels it is usually ferrite and martensite, while for medium-Mn steels retained austenite is also formed. In a present study, a wide intercritical temperature range was applied to a 5% Mn steel to investigate possible microstructure combinations: ranging from fully ferritic, through ferritic-austenitic, multiphase, to fully martensitic, which were next investigated in terms of mechanical properties to clarify the behavior of this type of material. The obtained results together with technological issues and economic indicators were next compared to mechanical properties of typical DP steels in order to assess the possibility of replacing this material in car production. The mechanical properties were evaluated using static tensile and hardness tests. The phase composition was determined qualitatively and quantitatively using dilatometry, X-ray diffraction measurements, and electron backscatter diffraction analysis. The results suggest that both initial austenite and martensite fractions have a decisive influence on the yielding and elongation of steel; however, the tensile strength depends mainly on the sum of martensite initially present in the microstructure and the strain-induced martensite formed from the plastically deformed austenite regardless of the initial retained austenite—martensite ratio. The results indicate superior total elongation of medium-Mn steels reaching 30% compared to DP steels with a similar strength level in the range between 900 and 1400 MPa. However, medium-Mn steels could be a significant competitor to dual phase steels only if some technological problems like discontinuous yielding and serrations are significantly reduced.

Mössbauer and magnetization measurements of multicomponent iron garnets

Four Gd-containing iron garnets were investigated using Mössbauer spectroscopy and Vibrating Sample Magnetometry over a wide temperature range, from 4K to ∼600K. The magnetic ordering temperature and hyperfine parameters determined on the basis of Mössbauer spectra for all samples were found to be surprisingly similar, differences were only noted for the average magnetic moments, which turned out to be strongly correlated with the magnetic moments of rare earth elements present in the structure. Further differences between the systems were also highlighted in measurements in the external 9T magnetic field, especially around the compensation temperature. Changes in the nature of the Mössbauer spectra were interpreted based on the crystal field approximation confirming the correctness of the interpretation of the temperature dependence of magnetization for these samples.

Temperature Dependence of Hot-Electron Graphene Fet Bolometric Detectors Response to Modulated Terahertz Radiation

In this paper, we analyze the modulation characteristics and the ultimate modulation frequency of the terahertz (THz) hot-electron FET bolometers with the graphene channels (GCs), metal gate (MG), and gate barrier layers (BLs) in a wide temperature range. Our results predict that the responsivity of GC-FET bolometers decreases with decreasing operating temperature. This is attributed to a dramatic drop in the thermionic GC-MG current (characterized by the relatively large activation energy) and its modulated component when the temperature lowers. A further decrease in the temperature results in a fairly strong responsivity roll-off. In contrast, the responsivity of the GC-FET detectors with the temperature-adjusted load resistance rises with decreasing temperature because the temperature lowering leads to an increase in the electron energy relaxation time and promotes more effective heating by the impinging THz radiation. In this case, the weakening of the thermionic current is compensated by the commensurate increase in the load resistance.

A force field for the solubility of cellulose in DMSO/Ionic liquids

AbstractWe present the extension of our all-atom force field BILFF (Bio-polymers in Ionic Liquids Force Field) to the co-solvent dimethyl sulfoxide (DMSO). BILFF already includes force field parameters for several imidazolium- and triazolium-based ionic liquids, water, and the bio-molecule cellulose. DMSO is known to increase the cellulose solubility of [EMIm][OAc] when applied as an additive. Our focus is on a correct reproduction of the hydrogen bonds in the ternary system of [EMIm]$$^+$$ + , [OAc]$$^-$$ - , water and DMSO compared to ab initio molecular dynamics simulations. For this purpose, the results from force field MD simulations such as radial and distance–angle distribution functions are compared with the reference AIMD simulation. Based on this, the force field parameters (starting from OPLS–AA) are iteratively adjusted. Four systems, pure and aqueous DMSO as well as DMSO in pure and aqueous [EMIm][OAc], are considered and additionally compared to DMSO-free [EMIm][OAc] systems. A very good agreement with respect to the microstructure of the quantum chemical reference simulations as well as to experimental data such as density, diffusion coefficients, enthalpy of vaporization, compressibility and thermal expansion coefficients can be observed over a wide temperature range. BILFF thus enables accurate simulations of larger systems of solvated cellulose in (aqueous) [EMIm][OAc] and the co-solvent DMSO.

Modeling of strain hardening behaviors of 6061 aluminum alloy considering strain rate and temperature effects

This paper focuses on the plastic strain hardening behaviors of 6061 aluminum alloy (AA6061), considering its dependence on strain rate and temperature. Quasi-static tensile tests were conducted over a wide temperature range (20 °C-300 °C), and the digital image correlation technique was used to capture the deformation process of specimens. Additionally, the uniaxial compressive mechanical response of AA6061 was tested utilizing quasi-static compression and split Hopkinson pressure bar experiments over a wide range of strain rates (0.001 s−1–6000 s−1). Experimental results showed that the flow stress decreased and increased nonlinearly with temperature and strain rate, respectively. A modified Johnson–Cook (MJC) model was developed by incorporating a temperature-dependent strain softening term, along with corrections to the temperature and strain rate product terms, to reproduce the nonlinear dependence. Furthermore, the MJC model was proven to be able to accurately reproduce the deformation of the specimens tested in Taylor impact experiments (strain rates up to 105 s−1), suggesting its effectiveness for interpolating and extrapolating stress-strain relationships. This model provides applicable modeling for materials with nonlinear rate sensitivity and temperature sensitivity, and it is expected to be applied in engineering problems involving ultra-high strain rates.

Modeling of water gas shift reaction using neural network trained on detailed kinetic mechanisms

For the optimization of a chemical reactor or its control, computational fluid dynamics (CFD) that considers accurate reaction models is effective. Although detailed kinetic mechanisms can accurately predict gas-phase reactions, integrating them with CFD is too computationally expensive. In contrast, global reactions have lower computational costs but significantly reduced accuracy outside of tuned conditions. This study proposes a method for constructing a model using a neural network to predict the reaction rate of water gas shift reaction based on detailed kinetic mechanisms. It includes techniques to avoid unrealistic solutions inherent to detailed kinetic mechanisms and methods to minimize biases in training data. The neural network input was log-transformed concentrations and inverse temperatures, and the output was the logarithm of the absolute value of the reaction rate and direction, enabling the prediction of bidirectional reactions over a wide temperature range. The quality of the dataset significantly impacted the accuracy of the neural network. Using a dataset with less bias in chemical species concentrations, the model achieved accuracy similar to detailed models while facilitating an over 400 times faster computation. The study also discussed the impact of temperature change rate, showing that at about 72 K/min, the detailed kinetic mechanism's solution can be accurately replicated. Still, at 720 K/min, the radical concentration deviates from the quasi-steady state, leading to discrepancies. This study opens up new possibilities for computational methods in the prediction and optimization of chemical reactions.