bluuebunny/crossref_metadata_2025_split huggingface dataset:
2D Layered Materials Based Triboelectric Self‐Powered Sensors
Authors: Rajaboina Rakesh Kumar , Khanapuram Uday Kumar , Kulandaivel Anu 
Published: June 2024

AbstractSensors play a crucial role in enhancing the quality of life, ensuring safety, and facilitating technological advancements. Over the past decade, 2D layered materials have been added as new sensing element in addition to existing materials such as metal oxides, semiconductors, metals, and polymers. 2D Layered materials are typically characterized by their single or few‐layer thickness and offer a high surface‐to‐volume ratio, exceptional mechanical strength, and unique electronic attributes. These properties make them ideal candidates for a variety of sensing applications. This review article focused on utilizing 2D layered materials in triboelectric nanogenerators (TENGs) for different sensing applications. The best part of TENG‐based sensing is that it is self‐powered, so no external power supply is required. The initial part of the review focused on the importance of the 2D layered materials and their innovative integration methods in TENGs. Further, this review discusses various sensing applications, including humidity, touch, force, temperature, and gas sensing, highlighting the impact of 2D layered materials in enhancing the sensitivity and selectivity of TENG sensors. The last part of the review discusses the challenges and prospects of TENG‐based self‐powered sensors.
Design and Characterization of a Dual‐Interval Elastic Force Sensor for Robot‐Assisted Microinjection
Authors: Lyu Zekui , Ai Nana , Ge Wei , Xu Qingsong 
Published: June 2024

AbstractRobot‐assisted microinjection has been widely implemented in the field of experimental biology research. Force perception is more accurate than visual feedback in determining the state of interaction between the micropipette and the biological sample. The existing micro‐force sensors are difficult to directly combine with micropipettes to fully utilize their capabilities. This paper develops a new integrated force‐sensing microinjector with both micro‐force sensing and micropipette carrying functions using a symmetrical compliant guide mechanism and highly sensitive semiconductor strain gauges. Overload protection is considered in the structure design of the sensor, which is beneficial in reducing damage caused by displacement overshot due to misuse. The mechanical performance of the proposed dual‐interval force sensing device is verified through theoretical derivation, simulation analysis, and experimental testing. The sensitivity, resolution, accuracy, dynamic response, stability, and repeatability of the sensor are investigated and evaluated in the established experimental platform. Finally, puncture experiments are conducted on zebrafish larvae and crab eggs using the proposed force‐sensing microinjector. The results indicate that the sensor is effective in recording force signals during penetration of the sample.
Spatial Isolation of Oversized Lithium and Separator via Janus Carbon Fabric Anode for Safer and Steadier Lithium Metal Batteries
Authors: Li Dongdong , Li Tingting , Han Xuan , Cui Jiajie , Liu Qingyi , Xu Jun , Hu Henghui , Yang Shengchen , Lai Wen‐Yong 
Published: June 2024

AbstractAlthough Li metal is regarded as a promising anode material, the undesired dendritic growth and continuous consumption of lithium during battery cycling result in severe safety risks and low Coulombic efficiency. Herein, a critical spatial‐isolation strategy is demonstrated to separate the originally adjacent lithium metal and separator for higher safety and stability of lithium metal batteries by designing a Janus carbon fabric (CF) anode. Transferring lithium from the anode/separator interface to CF bottom shuts down the prerequisite of lithium dendrite formation, while the oversized lithium at CF bottom can be also used to compensate for the loss of lithium during the charge‐discharge cycling. As a result, the Janus CF//Li anode exhibits an ultralong cyclic life of 450 h at 2 mA cm−2 and >250 h at 4 mA cm−2, which significantly exceeds the common CF//Li anodes. Full cells coupling the Janus CF//Li anodes demonstrate longer cycle life (550 cycles) than that of the CF//Li anodes (450 cycles) at 1C, along with higher rate capability, and excellent cyclic stability at 2C. The remarkable results, as a proof of concept, signify the superior anode structure for improving both battery safety and cyclic stability for the realistic application of lithium metal batteries.
Nexus Between Water Consumption and Economic Output for the Metallic and Non‐Metallic Mineral Products Sector: An Empirical Analysis at the Enterprise Level
Authors: Wang Chenglong , Shuai Chenyang , Chen Xi , Sun Jingran , Zhao Bu 
Published: June 2024

AbstractWith rapid urbanization and industrialization in China, the demand for mineral products and subsequent water consumption have significantly increased, posing challenges to sustainable economic growth due to escalating water scarcity. Few studies have explored the nexus between water use and economic output from the enterprise perspective. This study focuses on the metallic and non‐metallic mineral products sector, quantifying the nexus between water consumption and economic output at the enterprise level, analyzing the heterogeneity of water consumption elasticity of economic output across different regions and sub‐sectors, and identifying key sub‐sectors within each region that are highly dependent on water consumption. The results indicate that for the metallic and non‐metallic mineral products sector, a 1% increase or decrease in water consumption leads to a corresponding increase or decrease in economic output by 0.096%. Water consumption elasticity of economic output varies from 0.056 to 0.131 according to the regions. And it ranges from 0.048 to 0.104 for different sub‐sectors. This study identifies regions and sub‐sectors where economic output is highly dependent on water resources. The findings may help tailor policies to measure the value of water, especially in the context of potential water shortages.
Biomimetic Hydrogel‐Mediated Mechano‐Immunometabolic Therapy for Inhibition of ccRCC Recurrence After Surgery
Authors: Dong Yunze , Luo Jun , Pei Mingliang , Liu Shuai , Gao Yuchen , Zhou Hongmin , Nueraihemaiti Yimingniyizi , Zhan Xiangcheng , Xie Tiancheng , Yao Xudong , Guan Xin , Xu Yunfei 
Published: June 2024

AbstractThe unique physical tumor microenvironment (TME) and aberrant immune metabolic status are two obstacles that must be overcome in cancer immunotherapy to improve clinical outcomes. Here, an in situ mechano‐immunometabolic therapy involving the injection of a biomimetic hydrogel is presented with sequential release of the anti‐fibrotic agent pirfenidone, which softens the stiff extracellular matrix, and small interfering RNA IDO1, which disrupts kynurenine‐mediated immunosuppressive metabolic pathways, together with the multi‐kinase inhibitor sorafenib, which induces immunogenic cell death. This combination synergistically augmented tumor immunogenicity and induced anti‐tumor immunity. In mouse models of clear cell renal cell carcinoma, a single‐dose peritumoral injection of a biomimetic hydrogel facilitated the perioperative TME toward a more immunostimulatory landscape, which prevented tumor relapse post‐surgery and prolonged mouse survival. Additionally, the systemic anti‐tumor surveillance effect induced by local treatment decreased lung metastasis by inhibiting epithelial‐mesenchymal transition conversion. The versatile localized mechano‐immunometabolic therapy can serve as a universal strategy for conferring efficient tumoricidal immunity in “cold” tumor postoperative interventions.
Optimizing Nanofluidic Energy Harvesting in Synthetic Clay‐based Membranes by Annealing Treatment
Authors: Zavala‐Galindo Yozelin , Yang Guoliang , Zang Hanwen , Lei Weiwei , Liu Dan 
Published: June 2024

AbstractNanofluidic energy harvesting from salinity gradients is studied in 2D nanomaterials‐based membranes with promising performance as high ion selectivity and fast ion transport. In addition, moving forward to scalable, feasible systems requires environmentally friendly materials to make the application sustainable. Clay‐based membranes are attractive for being environmentally friendly, non‐hazardous, and easy to manipulate materials. However, achieving underwater stability for clay‐based membranes remains challenging. In this work, the synthetic clay Laponite is used to prepare clay‐based membranes with high stability and excellent performance for osmotic energy harvesting. The Laponite membranes (Lap‐membranes) are stabilized by low‐temperature annealing treatment to effectively reduce the interlayer space, achieving a continuous operation under salinity gradients. Furthermore, the Lap‐membranes conserve integrity while soaking in water for more than one month. The output power density improves from ≈4.97 W m−2 on the pristine membrane to ≈9.89 W m−2 in the membrane treated 12 h at 300 °C from a 30‐fold concentration gradient. Especially, It is found that the presence of interlayer water to be favorable for ion transport. Different mechanisms are proposed in the Lap‐membranes involved for efficient ion selectivity and the states found with varying annealing temperatures. This work demonstrates the potential application of Laponite based nanomaterials for nanofluidic energy harvesting.
Targeting Nr2e3 to Modulate Tet2 Expression: Therapeutic Potential for Depression Treatment
Authors: Ma Xiaohua , Xu Shiyao , Zhou Yaohui , Zhang Qian , Yang Hao , Wan Bo , Yang Yong , Miao Zhigang , Xu Xingshun 
Published: June 2024

AbstractEpigenetic mechanisms such as DNA methylation and hydroxymethylation play a significant role in depression. This research has shown that Ten‐eleven translocation 2 (Tet2) deficiency prompts depression‐like behaviors, but Tet2's transcriptional regulation remains unclear. In the study, bioinformatics is used to identify nuclear receptor subfamily 2 group E member 3 (Nr2e3) as a potential Tet2 regulator. Nr2e3 is found to enhance Tet2's transcriptional activity by binding to its promoter region. Nr2e3 knockdown in mouse hippocampus leads to reduced Tet2 expression, depression‐like behaviors, decreased hydroxymethylation of synaptic genes, and downregulation of synaptic proteins like postsynaptic density 95 KDa (PSD95) and N‐methy‐d‐aspartate receptor 1 (NMDAR1). Fewer dendritic spines are also observed. Nr2e3 thus appears to play an antidepressant role under stress. In search of potential treatments, small molecule compounds to increase Nr2e3 expression are screened. Azacyclonal (AZA) is found to enhance the Nr2e3/Tet2 pathway and exhibited antidepressant effects in stressed mice, increasing PSD95 and NMDAR1 expression and dendritic spine density. This study illuminates Tet2's upstream regulatory mechanism, providing a new target for identifying early depression biomarkers and developing treatments.
Mechanically Robust Lubricating Hydrogels Beyond the Natural Cartilage as Compliant Artificial Joint Coating
Authors: Zhao Weiyi , Zhang Yunlei , Zhao Xiaoduo , Sheng Wenbo , Ma Shuanhong , Zhou Feng 
Published: June 2024

AbstractNatural cartilage exhibits superior lubricity as well as an ultra‐long service lifetime, which is related to its surface hydration, load‐bearing, and deformation recovery feature. Until now, it is of great challenge to develop reliable cartilage lubricating materials or coatings with persistent robustness. Inspired by the unique biochemical structure and mechanics of natural cartilage, the study reports a novel cartilage‐hydrogel composed of top composite lubrication layer and bottom mechanical load‐bearing layer, by covalently manufacturing thick polyelectrolyte brush phase through sub‐surface of tough hydrogel matrix with multi‐level crystallization phase. Due to multiple network dissipation mechanisms of matrix, this hydrogel can achieve a high compression modulus of 11.8 MPa, a reversible creep recovery (creep strain: ≈2%), along with excellent anti‐swelling feature in physiological medium (v/v0 < 5%). Using low‐viscosity PBS as lubricant, this hydrogel demonstrates persistent lubricity (average COF: ≈0.027) under a high contact pressure of 2.06 MPa with encountering 100k reciprocating sliding cycles, negligible wear and a deformation recovery of collapse pit in testing area. The extraordinary lubrication performance of this hydrogel is comparable to but beyond the natural animal cartilage, and can be used as compliant coating for implantable articular material of UHMWPE to present, offering more robust lubricity than current commercial system.
Macrophage‐Mimicking Cellular Nanoparticles Scavenge Proinflammatory Cytokines in Specimens of Patients with Inflammatory Disorders
Authors: Zhou Zhidong , Mukundan Nilesh , Zhang Jiayuan Alex , Wu You‐Ting , Zhang Qiangzhe , Wang Dan , Fang Ronnie H. , Gao Weiwei , Zhang Liangfang 
Published: June 2024

AbstractEffectively neutralizing inflammatory cytokines is crucial for managing a variety of inflammatory disorders. Current techniques that target only a subset of cytokines often fall short due to the intricate nature of redundant and compensatory cytokine networks. A promising solution to this challenge is using cell membrane‐coated nanoparticles (CNPs). These nanoparticles replicate the complex interactions between cells and cytokines observed in disease pathology, providing a potential avenue for multiplex cytokine scavenging. While the development of CNPs using experimental animal models has shown great promise, their effectiveness in scavenging multiple cytokines in human diseases has yet to be demonstrated. To bridge this gap, this study selected macrophage membrane‐coated CNPs (MФ‐CNPs) and assessed their ability to scavenge inflammatory cytokines in serum samples from patients with COVID‐19, sepsis, acute pancreatitis, or type‐1 diabetes, along with synovial fluid samples from patients with rheumatoid arthritis. The results show that MФ‐CNPs effectively scavenge critical inflammatory cytokines, including interleukin (IL)‐6, IL‐8, interferon (IFN)‐γ, and tumor necrosis factor (TNF)‐α, in a dose‐dependent manner. Overall, this study demonstrates MФ‐CNPs as a multiplex cytokine scavenging formulation with promising applications in clinical settings to treat a range of inflammatory disorders.
Droplet Micro‐Sensor and Detection of Respiratory Droplet Transmission
Authors: Lu Jiaqi , Chen Xiangdong , Ding Xing , Jia Zhuolin , Li Mengxiang , Zhang Mengxi , Liu Fang , Tang Kun , Yu Xiang , Li Guoping 
Published: June 2024

AbstractDroplet transmission is the primary infection route for respiratory diseases like COVID‐19 and influenza, but small and low‐cost wearable droplet detection devices are a significant challenge. Herein, a respiratory droplet micro‐sensor based on graphene oxide quantum dots (GOQDs) assembled onto SiO2 microspheres by the nebulized natural deposition is presented. Benefiting from the energy dissipation of the microsphere to droplets, the sensor can detect droplets as far as 2 m from coughing. With this sensor, droplet signal variations caused by some factors like distance, speech, angles, and wind directions are explored, and the effectiveness of different protective measures in preventing droplet transmission is evaluated. This droplet detection technology is expected to be utilized for the development of personal detection and protection devices against infectious respiratory diseases.
Dynamic Addressing Molecular Robot (DAMR): An Effective and Efficient Trial‐and‐Error Approach for the Analysis of Single Nucleotide Polymorphisms
Authors: Chen Tianshu , Chen Guifang , Cao Siyu , Tang Xiaochen , Li Wenxing , Liu Chenbin , Gou Hongquan , Sun Pei , Mao Yichun , Pan Qiuhui , Zhang Penghui , Zhu Xiaoli 
Published: June 2024

AbstractAccurate and efficient molecular recognition plays a crucial role in the fields of molecular detection and diagnostics. Conventional trial‐and‐error‐based molecular recognition approaches have always been challenged in distinguishing minimal differences between targets and non‐targets, such as single nucleotide polymorphisms (SNPs) of oligonucleotides. To address these challenges, here, a novel concept of dynamic addressing analysis is proposed. In this concept, by dissecting the regions of the target and creating a corresponding recognizer, it is possible to eliminate the inaccuracy and inefficiency of recognition. To achieve this concept, a Dynamic Addressing Molecular Robot (DAMR), a DNA‐based dynamic addressing device is developed which is capable of dynamically locating targets. DAMR is designed to first bind to the conserved region of the target while addressing the specific region dynamically until accurate recognition is achieved. DAMR has provided an approach for analyzing low‐resolution targets and has been used for analyzing SNP of miR‐196a2 in both cell and serum samples, which has opened new avenues for effective and efficient molecular recognition.
Enantioselective Synthesis of Oxazocines via MQ‐Phos Enabled Palladium‐Catalyzed Asymmetric Formal [4+4]‐Cycloadditions
Authors: Meng Qiaojing , Meng Yinggao , Liu Qinglin , Yu Bing , Li Zhong‐Jun , Li Er‐Qing , Zhang Junliang 
Published: June 2024

AbstractOxazocines are key structural intermediates in the synthesis of natural products and pharmaceutical molecules. However, the synthesis of oxazocines especially in a highly enantioselective manner, is a long‐standing formidable challenge due to unfavorable energetics involved in cyclization. Herein, a series of new PNP‐Ligand P‐chiral stereocenter is first designed and synthesized, called MQ‐Phos, and successfully applied it in the Pd‐catalyzed enantioselective higher‐order formal [4+4]‐cycloaddition of α, β‐unsaturated imines with 2‐(hydroxymethyl)‐1‐arylallyl carbonates. The reaction features mild conditions, excellent regio‐ and enantiocontrol and a broad substrate scope (54 examples). Various medium‐sized rings can be afforded in moderate to excellent yields (up to 92%) and excellent enantioselectivity (up to 99% ee). The newly developed MQ‐Phos is critical for synthesis of the medium‐sized ring in excellent catalytic reactivity and enantioselectivity.
Highly‐Polarized Emission Provided by Giant Optical Orientation of Exciton Spins in Lead Halide Perovskite Crystals
Authors: Kopteva Nataliia E. , Yakovlev Dmitri R. , Yalcin Eyüp , Akimov Ilya A. , Nestoklon Mikhail O. , Glazov Mikhail M. , Kotur Mladen , Kudlacik Dennis , Zhukov Evgeny A. , Kirstein Erik , Hordiichuk Oleh , Dirin Dmitry N. , Kovalenko Maksym V. , Bayer Manfred 
Published: June 2024

AbstractQuantum technologic and spintronic applications require reliable material platforms that enable significant and long‐living spin polarization of excitations, the ability to manipulate it optically in external fields, and the possibility to implement quantum correlations between spins, i.e., entanglement. Here it is demonstrated that these conditions are met in bulk crystals of lead halide perovskites. A giant optical orientation of 85% of excitons, approaching the ultimate limit of unity, in FA0.9Cs0.1PbI2.8Br0.2 crystals is reported. The exciton spin orientation is maintained during the exciton lifetime of 55 ps resulting in high circular polarization of the exciton emission. The optical orientation is robust to detuning of the excitation energy up to 0.3 eV above the exciton resonance and remains larger than 20% up to detunings of 0.9 eV. It evidences pure chiral selection rules and suppressed spin relaxation of electrons and holes, even with large kinetic energies. The exciton and electron–hole recombinations are distinguished by means of the spin dynamics detected via coherent spin quantum beats in magnetic field. Further, electron–hole spin correlations are demonstrated through linear polarization beats after circularly polarized excitation. These findings are supported by atomistic calculations. All‐in‐all, the results establish lead halide perovskite semiconductors as suitable platform for quantum technologies.
Assessment of Segal method for identifying crystallinity evolution in developing cotton fibers
Authors: Nam Sunghyun , Liu Yongliang , He Zhongqi , Hinchliffe Doug J. , Fang David 
Published: June 2024

AbstractThe crystallinity index (CI) is an important parameter in evaluating cotton fiber quality. Due to its ease and speed in measuring CIs from X‐ray diffraction (XRD) patterns, the Segal method is popularly used. In this study, we assessed the Segal method for monitoring the crystallinity evolution in developing cotton (Gossypium L.) fibers between 20 and 60 days post anthesis (DPAs) by comparing Segal CIs with those obtained from a Fourier transform infrared spectroscopy‐based method and other XRD‐based methods. The Segal method estimated higher CIs than other methods, especially for shorter DPAs. The Segal method suggested a rapid evolution of crystallinity in the early developmental stage, whereas other methods suggested a gradual increase in crystallinity. The calculation of diffraction patterns for cellulose Iβ crystallites with different sizes showed very little effect of the crystallite size on the Segal CIs for developing cotton fibers studied.
Random Projection‐Based Locality‐Sensitive Hashing in a Memristor Crossbar Array with Stochasticity for Sparse Self‐Attention‐Based Transformer
Authors: Wang Xinxin , Valov Ilia , Li Huanglong 
Published: June 2024

AbstractSelf‐attention mechanism is critically central to the state‐of‐the‐art transformer models. Because the standard full self‐attention has quadratic complexity with respect to the input's length L, resulting in prohibitively large memory for very long sequences, sparse self‐attention enabled by random projection (RP)‐based locality‐sensitive hashing (LSH) has recently been proposed to reduce the complexity to O(L log L). However, in current digital computing hardware with a von Neumann architecture, RP, which is essentially a matrix multiplication operation, incurs unavoidable time and energy‐consuming data shuttling between off‐chip memory and processing units. In addition, it is known that digital computers simply cannot generate provably random numbers. With the emerging analog memristive technology, it is shown that it is feasible to harness the intrinsic device‐to‐device variability in the memristor crossbar array for implementing the RP matrix and perform RP‐LSH computation in memory. On this basis, sequence prediction tasks are performed with a sparse self‐attention‐based Transformer in a hybrid software‐hardware approach, achieving a testing accuracy over 70% with much less computational complexity. By further harnessing the cycle‐to‐cycle variability for multi‐round hashing, 12% increase in the testing accuracy is demonstrated. This work extends the range of applications of memristor crossbar arrays to the state‐of‐the‐art large language models (LLMs).