With increasing energy storage demands across various applications, reliable batteries capable of performing in harsh environments, such as extreme temperatures, are crucial. However, current lithium-ion batteries (LIBs) exhibit limitations in both low and high-temperature performance, restricting their use in critical fields like defense, military, and aerospace. These challenges stem from the narrow operational temperature range and safety concerns of existing electrolyte systems. To enable LIBs to function effectively under extreme temperatures, the optimization and design of novel electrolytes are essential. Given the urgency for LIBs operating in extreme temperatures and the notable progress in this research field, a comprehensive and timely review is imperative. This article presents an overview of challenges associated with extreme temperature applications and strategies used to design electrolytes with enhanced performance. Additionally, the significance of understanding underlying electrolyte behavior mechanisms and the role of different electrolyte components in determining battery performance are emphasized. Last, future research directions and perspectives on electrolyte design for LIBs under extreme temperatures are discussed. Overall, this article offers valuable insights into the development of electrolytes for LIBs capable of reliable operation in extreme conditions.
Recently, cross-domain collaborative filtering (CDCF) has been widely used to solve the data sparsity problem in recommendation systems. Therein, the dual-target cross-domain recommendation becomes a research hotspot, which aims to improve the recommendation performance of both target and source domains. Most existing approaches tend to use fixed weights or self-attention in a single representation space for the bi-directional inter-domain transfer of the user representation. However, a single representation space leads to limited representation capability, which makes the transfer of the user representation coarse-grained and inaccurate. In this paper, Multi-head Attention Based Dual Target Graph Collaborative Filtering Network (MA-DTGCF) is proposed. The core of the model is the bi-directional transfer graph convolution layer, consisting of a graph convolution layer and a bi-directional transfer layer based on a multi-head attention mechanism. The latter can achieve fine-grained and adaptive transfer of user features in multiple representation subspaces. It is worth noting that by stacking multiple bi-directional transfer graph convolutional layers, we can get high-order user and item features and achieve adaptive transfer of each order user features. Experimental results on three real datasets show that the proposed MA-DTGCF model significantly outperforms the state-of-the-art models in terms of HR and NDCG.
The comprehensive regulation of an in situ grown overlayer and ionic liquid additive enables the Zn anode to harvest homoepitaxial deposition along certain Zn crystal facets, facilitating the commercial application of aqueous Zn-ion batteries.
Abstract Natural dissipative assembly (DSA) often exhibit energy‐driven shifts in natural functions. However, creating man‐made DSA that can mimic such biological activities transformation remains relatively rare. Herein, we introduce a cytomembrane‐like dissipative assembly system based on chiral supramolecules. This system employs benzoyl cysteine in an out of equilibrium manner, enabling the shifts in biofunctions while minimizing material use. Specifically, aroyl‐cystine derivatives primarily assemble into stable M‐helix nanofibers under equilibrium conditions. These nanofibers enhance fibroblast adhesion and proliferation through stereospecific interactions with chiral cellular membranes. Upon the addition of chemical fuels, these functional nanofibers temporarily transform into non‐equilibrium nanospheres, facilitating efficient drug delivery. Subsequently, these nanospheres revert to their original nanofiber state, effectively recycling the drug. The programmable function‐shifting ability of this DSA establishes it as a novel, fuel‐driven drug delivery vehicle. And the bioactive DSA not only addresses a gap in synthetic DSAs within biological applications but also sets the stage for innovative designs of ′living′ materials.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
The capillary gas chromatography-negative chemical ionization mass spectrometry(GC-NCI-MS) technique has been applied for the determination of hexachlorobenzene(HCB) pesticide residues in picloram samples.The sensitivity gained by GC-NCI-MS is 100 times higher than that gained by the capillary gas chromatography-electron ionization mass spectrometry(GC-EI-MS).The parameters of negative chemical ionization mass spectrometry,such as ion source temperature,the flow of reaction gas are emphatically studied.Ion source temperature of 100℃ and the flow of reaction gas of 2.5mL/min are the suitable technical parameters.When selected-ions monitoring(m/z) are 283,285and 287,detection limit of 0.012μg/L,lower limit quantify of 1μg/L,and square of correlation coefficient(R2) of 0.9991 are obtained using GC-NCI-MS.In picloram samples,the contents between 0.727 and 1.527μg/g are detected.The recoveries were in the range of 81.2%～113.8%.
Hybrid piezoelectric/triboelectric nanogenerators combine the merits of piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs), possessing enhanced electrical output and sensitivity. However, the structures of the majority of hybrid nanogenerators are rather complex in integrating both functions, limiting their practical application in wearable electronics. Herein, we propose to construct a piezoelectric/triboelectric hybrid nanogenerator (PT-NG) with a simple structure based on a composite film to simultaneously achieve the coupling of piezoelectric charge generation and triboelectrification with improved energy conversion efficiency. The composite film consists of electrospun PVDF nanofibers embedded in the surface of the PDMS film, which not only forms a rough nanomorphology on the surface of PDMS but also provides structural protection to the PVDF nanofibers by PDMS during compressive deformation. The results have shown that the PT-NG can generate much higher electrical outputs than individual TENG and PENG devices. The PT-NG devices exhibit a high level of mechanical-to-electrical energy conversion efficiency with superior performance in charging capacitors and functioning as self-powered wearable sensors for the detection of different signals from finger movement, the recognition of various gestures, and the monitoring of respiration. More importantly, the composite device possesses an impressive structure durability, maintaining its layered structure over 5000 testing cycles without noticing any obvious damage on the nanofibers or detachment between the layers. Our results have demonstrated that the combining of piezoelectric nanofibers and triboelectric substrate is an efficient way to fabricate highly efficient energy harvesting devices for intelligent identification and health monitoring.
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