Cell Reports Physical Science最新文献

Solution-based synthesis of complex molecules with high efficiency leverages supramolecular control over covalent bond formation. Herein, we present the mechanosynthesis of chiral mono-biotinylated hemicucurbit[8]urils (mixHC[8]s) via the condensation of D-biotin, (R,R)- or (S,S)-cyclohexa-1,2-diylurea, and paraformaldehyde. The selectivity of self-assembly is enhanced through mechanochemistry and by fostering non-covalent interactions, achieved by eliminating solvents and conducting the reaction in the solid state. Rigorous analysis of intermediates reveals key processes and chemical parameters influencing dynamic covalent chemistry. The library of ca. 50,000 theoretically predicted intermediates and products leads to covalent self-assembly of chiral hemicucurbiturils. Mechanochemically prepared diastereomeric (−)- and (+)-mixHC[8]s are suitable for anion binding and derivatization. Immobilization of the macrocycles on aminated silica produces a functional material capable of selective capture of anions, as demonstrated by efficient perchlorate removal from a spiked mineral matrix.

Aneurysm is a common disease that poses a threat to human health. Currently, treating aneurysms mainly relies on embolization using metallic microcoils. However, it is extremely difficult to insert metallic microcoils into the aneurysm inside tortuous vessels. Besides, adapting fixed metallic microcoils to different aneurysms is also a major problem. In this paper, we propose a shape-programmable robot based on a magnetic and radio frequency (RF) dual-responsive shape memory polymer (SMP). The SMP robot can move automatically to the target under a programmable magnetic field. Meanwhile, it can be heated up and will transform from a small-sized ball shape to the aneurysm shape using RF. In addition, the dual-responsive SMP has excellent mechanical properties; its tensile modulus is 50 times higher than that of traditional hydrogels, reducing the possibility of fracture during embolization. In the future, this SMP robot could be potentially suitable for clinical translation.

In the Eigen-Weller framework, acid-base reactions are described as those consisting of serial steps. The steps include the encounter of acid and base compounds, short-range proton transfer within the encounter complexes, and separation of the resulting Eigen complexes (ECs) equivalent to long-range proton diffusion. Although the initial proton transfer step in the encounter complexes has been extensively explored, the final step requisite to terminating the acid-base reactions has been overlooked. Using time-resolved fluorescence spectroscopy and chemical kinetics analysis, we track the excited-state proton transfer of a cationic acid to an aprotic base in binary solvent mixtures, where the lifetimes of ECs are prolonged. Identifying the ECs spectrally and kinetically, we investigate the molecularity in the consecutive steps of the hydrogen-bond formation between the acid and base and the dissociation of the EC to unveil the cooperative nature of the aprotic base molecules in the model reaction.

Ultrathin heat pipes (UHPs) have attracted tremendous attention in recent years. However, fabricating UHPs with high heat-transfer efficiency and low thermal expansion remains a challenge. Here, we report a design of an inverse opal complex wick for UHPs. The design enables the wick to have abundant random micropores for the transportation of vapor and ordered nanopores for the return of condensate. With the assistance of a Cu/MoCu/Cu shell, the UHP with a thickness of 0.985 mm can maintain a low coefficient of thermal expansion (7.3E−6 /K) and allow a gallium nitride (GaN) chip to work at a heat flux of 208 W/cm². When the liquid filling ratio reaches 54%, a lower thermal resistance of 0.8 K/W and a higher thermal conductivity of 11,076 W/(m⋅K) are realized. This study demonstrates the successful fabrication of high-performance UHPs, promoting the development of inverse opal wicks from materials to devices.

Artificial intelligence (AI) is progressively reshaping the way that researchers design and study highly complex systems. In this perspective, we introduce an engineering design methodology aimed at fostering creativity through “constructive dialogues with a generative AI” and exemplify its potential through a set of methodically developed case studies. This creativity promotion approach starts with computer-aided design (CAD) models of lattices, metamaterials, and architected materials, which are provided as initial inputs to a generative AI through a chat. Then, the conversation starts with researchers asking the generative AI to modify the provided CAD model images by incorporating new elements, placing them in quasi-real-life environments, or adapting the provided designs to the structures of new products. To illustrate the methodology, a varied set of selected case studies of constructive dialogues leading to highly innovative designs are provided, bridging the gap between tissue engineering scaffolds and building architectures, biohybrid materials and product design, and innovative structures and medical devices, to cite a few.

Energy density, power density, and safety of commercial lithium-ion batteries are largely dictated by anodes. Considering the multi-scale nature (10⁻⁸–10² cm) as well as the multi-physics properties—including electricity, force, and heat—of lithium-ion batteries, it is imperative to systematically categorize and summarize the failure-detection techniques for anodes in commercial lithium-ion batteries, namely, carbon-based and silicon-based anodes. In this perspective, we categorize the state-of-the-art failure-detection techniques for anodes into four dimensions—bulk of anode particles, interface/interphase of anode particles, electrodes, and batteries—aiming to develop the framework of multi-dimension failure detection. Based on the above four dimensions, this paper elaborates on characterization techniques applicable to different detection scales and the corresponding failure causes. Through examples that integrate multi-physical moduli or multi-dimensional characterization techniques, we further discuss the importance of developing collaborative characterization methods to acquire different physio-chemical information for anodes, providing relevant professionals with effective technical guidance.

Innovative approaches on clean alternative energy sources are important for future decarbonization. Electrification and hydrogen energy are crucial pathways for decarbonization in both transportation and buildings. However, life-cycle stage-wise carbon intensity is still unclear for both hydrogen- and electricity-driven energy. Furthermore, systematic evaluation on low-carbon transition pathways is insufficient specifically within the Internet of Energy that interfaces hydrogen and electricity. Here, a generic approach is proposed for quantifying life-cycle stage-wise carbon intensity of both hydrogen- and electricity-driven energy internets. Life-cycle decarbonization effects on vehicle pathways are compared with traditional vehicles with internal-combustion engines. Techno-economic and environmental feasibility of the future advanced hydrogen-driven Internet of Energy is analyzed based on net present value. The region-wise carbon-intensity map and associated decarbonization strategies will help researchers and policymakers in promoting sustainable development with the hydrogen economy.

Silicon anodes for lithium-ion batteries offer high theoretical capacity but face practical challenges of capacity fading due to significant volumetric changes during charge-discharge cycles. To reveal the underlying mechanisms, we employ reactive force fields (ReaxFFs) in molecular dynamics simulations to conduct atomic analyses of lithiation and delithiation cycles of silicon particles with three diameters. Our simulations demonstrate a volumetric expansion exceeding 280%, primarily along the ⟨110⟩ direction, with an inward movement of the interface between lithiated and unlithiated regions. We introduce a metric, “geometric defect,” derived from the centroid deviation of neighboring atoms, to evaluate the structural integrity of the silicon anode. Geometric defect state of charge curves show a 5% capacity fade due to silicon loss after the initial cycle. Experimental validation confirms a capacity loss exceeding 40% after the first cycle, attributed to internal defects within silicon particles, aligning well with our simulation results.

Emulating nature’s living properties in functional materials is a crucial step toward creating adaptive and self-regulating systems capable of integration with biological tissues. In this perspective, we first investigate the various strategies employed in the field of bioelectronics and engineered living materials to replicate nature's living functionalities. Then, we explore the convergence of bioelectronics and engineered living materials, highlighting an approach called living bioelectronics. We posit that merging these two fields can enable the creation of robust, adaptable devices that replicate the dynamic functionalities of living systems. Living bioelectronics integrate the strength of both disciplines while complementing their weaknesses, heralding opportunities for biosensing, personalized therapies, and applications beyond healthcare.