Chromium-Induced High Covalent Co-O Bonds for Efficient Anodic Catalysts in PEM Electrolyzer

The proton exchange membrane water electrolyzer (PEMWE), crucial for green hydrogen production, is challenged by the scarcity and high cost of iridium-based materials. Cobalt oxides, as ideal electrocatalysts for oxygen evolution reaction (OER), have not been extensively applied in PEMWE, due to extremely high voltage and poor stability at large current density, caused by complicated structural variations of cobalt compounds during the OER process. Thus, the authors sought to introduce chromium into a cobalt spinel (Co3O4) catalyst to regulate the electronic structure of cobalt, exhibiting a higher oxidation state and increased Co-O covalency with a stable structure. In-depth operando characterizations and theoretical calculations revealed that the activated Co-O covalency and adaptable redox behavior are crucial for facilitating its OER activity. Both turnover frequency and mass activity of Cr-doped Co3O4 (CoCr) at 1.67 V (vs RHE) increased by over eight times than those of as-synthesized Co3O4. The obtained CoCr catalyst achieved 1500 mA cm-2 at 2.17 V and exhibited notable durability over extended operation periods - over 100 h at 500 mA cm-2 and 500 h at 100 mA cm-2, demonstrating promising application in the PEMWE industry.

From Polyester Plastics to Diverse Monomers via Low-Energy Upcycling

Polyester plastics, constituting over 10% of the total plastic production, are widely used in packaging, fiber, single-use beverage bottles, etc. However, their current depolymerization processes face challenges such as non-broad spectrum recyclability, lack of diversified high-value-added depolymerization products, and crucially high energy consumption. Herein, an efficient strategy is developed for dismantling the compact structure of polyester plastics to achieve diverse monomer recovery. Polyester plastics undergo swelling and decrystallization with a low depolymerization energy barrier via synergistic effects of polyfluorine/hydrogen bonding, which is further demonstrated via density functional theory calculations. The swelling process is elucidated through scanning electron microscopy analysis. Obvious destruction of the crystalline region is demonstrated through X-ray crystal diffractometry curves. PET undergoes different aminolysis efficiently, yielding nine corresponding high-value-added monomers via low-energy upcycling. Furthermore, four types of polyester plastics and five types of blended polyester plastics are closed-loop recycled, affording diverse monomers with exceeding 90% yields. Kilogram-scale depolymerization of real polyethylene terephthalate (PET) waste plastics is successfully achieved with a 96% yield.

Decreased Electrically and Increased Ionically Conducting Scaffolds for Long-Life, High-Rate and Deep-Capacity Lithium-Metal Anodes

Lithium (Li) metal batteries are deemed as promising next-generation power solutions but are hindered by the uncontrolled dendrite growth and infinite volume change of Li anodes. The extensively studied 3D scaffolds as solutions generally lead to undesired "top-growth" of Li due to their high electrical conductivity and the lack of ion-transporting pathways. Here, by reducing electrical conductivity and increasing the ionic conductivity of the scaffold, the deposition spot of Li to the bottom of the scaffold can be regulated, thus resulting in a safe bottom-up plating mode of the Li and dendrite-free Li deposition. The resulting symmetrical cells with these scaffolds, despite with a limited pre-plated Li capacity of 5 mAh cm-2, exhibit ultra-stable Li plating/stripping for over 1 year (11 000 h) at a high current density of 3 mA cm-2 and a high areal capacity of 3 mAh cm-2. Moreover, the full cells with these scaffolds further demonstrate high cycling stability under challenging conditions, including high cathode loading of 21.6 mg cm-2, low negative-to-positive ratio of 1.6, and limited electrolyte-to-capacity ratio of 4.2 g Ah-1.

Polypyrrole regulates Active Sites in Co-based Catalyst in Direct Borohydride Fuel Cells

Direct borohydride fuel cells (DBFCs) convert borohydride (NaBH4) chemical energy into clean electricity. However, catalytic active site deactivation in NaBH4 solution limits their performance and stability. We propose a strategy to regulate active sites in Co-based catalysts using polypyrrole modification (Co-PX catalyst) to enhance electrochemical borohydride oxidation reaction (eBOR). As an anode catalyst, the synthesized Co-PX catalyst exhibits excellent eBOR performance in DBFCs, with current density of 280 mA ⋅ cm-2 and power density of 151 mW ⋅ cm-2, nearly twice that of the unmodified catalyst. The Co-PX catalyst shows no degradation after 120-hour operation, unlike the rapidly degrading control. In-situ electrochemical attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIRS) and density functional theory (DFT) suggest that polypyrrole-modified carbon support regulate the charge distribution, increasing oxidation state and optimizing adsorption/desorption of intermediates. A possible reaction pathway is proposed. This work presents a promising strategy for efficient polymer-modulated catalysts in advanced DBFCs.

High-Performance Artificial Ligament Made from Helical Polyester Fibers Wrapped with Aligned Carbon Nanotube Sheets

Repairing high-load connective tissues, such as ligaments, by surgically implanting artificial grafts after injury is challenging because they lack biointegration with host bones for stable interfaces. Herein, a high-performance helical composite fiber (HCF) ligament by wrapping aligned carbon nanotube (CNT) sheets around polyester fibers is proposed. Anterior cruciate ligament (ACL) reconstruction surgery shows that HCF grafts could induce effective bone regeneration, thus allowing the narrowing of bone tunnel defects. Such repair of the bone tunnel is in strong contrast to the tunnel enlargement of more than 50% for commercial artificial ligaments made from bare polyester fibers. Rats reconstructed with this HCF ligament show normal jumping, walking, and running without limping. This work allows bone regeneration in vivo through a one-step surgery without seeding cells or transforming growth factors, thereby opening an avenue for high-performance artificial tissues.

Anti-Inflammatory Ergosteroid Derivatives from the Coral-Associated Fungi Penicillium oxalicum HL-44

To obtain the optimal fermentation condition for more abundant secondary metabolites, Potato Dextrose Agar (PDA) medium was chosen for the scale-up fermentation of the fungus Penicillium oxalicum HL-44 associated with the soft coral Sinularia gaweli. The EtOAc extract of the fungi HL-44 was subjected to repeated column chromatography (CC) on silica gel and Sephadex LH-20 and semipreparative RP-HPLC to afford a new ergostane-type sterol ester (1) together with fifteen derivatives (2-16). Their structures were determined with spectroscopic analyses and comparisons with reported data. The anti-inflammatory activity of the tested isolates was assessed by evaluating the expression of pro-inflammatory factors Tnfα and Ifnb1 in Raw264.7 cells stimulated with LPS or DMXAA. Compounds 2, 9, and 14 exhibited significant inhibition of Ifnb1 expression, while compounds 2, 4, and 5 showed strong inhibition of Tnfα expression in LPS-stimulated cells. In DMXAA-stimulated cells, compounds 1, 5, and 7 effectively suppressed Ifnb1 expression, whereas compounds 7, 8, and 11 demonstrated the most potent inhibition of Tnfα expression. These findings suggest that the tested compounds may exert their anti-inflammatory effects by modulating the cGAS-STING pathway. This study provides valuable insight into the chemical diversity of ergosteroid derivatives and their potential as anti-inflammatory agents.

Indoor Photovoltaic Fiber with an Efficiency of 25.53% under 1500 Lux Illumination

Photovoltaic devices represent an efficient electricity generation mode. Integrating them into textiles offers exciting opportunities for smart electronic textiles-with the ultimate goal of supplying power for wearable technology-which is poised to change how electronic devices are designed. Many human activities occur indoors, so realizing indoor photovoltaic fibers (IPVFs) that can be woven into textiles to power wearables is critical, although currently unavailable. Here, a dye-sensitized IPVF is constructed by incorporating titanium dioxide nanoparticles into aligned nanotubes to produce close contact and stable interfaces among active layers on a curved fiber substrate, thus presenting efficient charge transport and low charge recombination in the photoanode. With the combination of highly conductive core-sheath Ti/carbon nanotube fiber as a counter electrode, the IPVF shows a certified power conversion efficiency of 25.53% under 1500 lux illuminance. Its performance variation is below 5% after bending, twisting, or pressing for 1000 cycles. These IPVFs are further integrated with fiber batteries as self-charging power textiles, which are demonstrated to effectively supply electricity for wearables, solving the power supply problem in this important direction.

Multistep Dissolution of Lamellar Crystals Generates Superthin Amorphous Ni(OH)2 Catalyst for UOR

Urea oxidation reaction (UOR) is an ideal replacement of the conventional anodic oxygen evolution reaction (OER) for efficient hydrogen production due to the favorable thermodynamics. However, the UOR activity is severely limited by the high oxidation potential of Ni-based catalysts to form Ni³⁺ , which is considered as the active site for UOR. Herein, by using in situ cryoTEM, cryo-electron tomography, and in situ Raman, combined with theoretical calculations, a multistep dissolution process of nickel molybdate hydrate is reported, whereby NiMoO₄ ·xH₂ O nanosheets exfoliate from the bulk NiMoO₄ ·H₂ O nanorods due to the dissolution of Mo species and crystalline water, and further dissolution results in superthin and amorphous nickel (II) hydroxide (ANH) flocculus catalyst. Owing to the superthin and amorphous structure, the ANH catalyst can be oxidized to NiOOH at a much lower potential than conventional Ni(OH)₂ and finally exhibits more than an order of magnitude higher current density (640 mA cm^-2 ), 30 times higher mass activity, 27 times higher TOF than those of Ni(OH)₂ catalyst. The multistep dissolution mechanism provides an effective methodology for the preparation of highly active amorphous catalysts.

Affinity selection of double-click triazole libraries for rapid discovery of allosteric modulators for GLP-1 receptor

The recently developed double-click reaction sequence [G. Meng et al., Nature 574, 86-89 (2019)] is expected to vastly expand the number and diversity of synthetically accessible 1,2,3-triazole derivatives. However, it remains elusive how to rapidly navigate the extensive chemical space created by double-click chemistry for bioactive compound discovery. In this study, we selected a particularly challenging drug target, the glucagon-like-peptide-1 receptor (GLP-1R), to benchmark our new platform for the design, synthesis, and screening of double-click triazole libraries. First, we achieved a streamlined synthesis of customized triazole libraries on an unprecedented scale (composed of 38,400 new compounds). By interfacing affinity-selection mass spectrometry and functional assays, we identified a series of positive allosteric modulators (PAMs) with unreported scaffolds that can selectively and robustly enhance the signaling activity of the endogenous GLP-1(9-36) peptide. Intriguingly, we further revealed an unexpected binding mode of new PAMs which likely act as a molecular glue between the receptor and the peptide agonist. We anticipate the merger of double-click library synthesis with the hybrid screening platform allows for efficient and economic discovery of drug candidates or chemical probes for various therapeutic targets.

Geometry-aware view reconstruction network for light field image compression

Light Field (LF) imaging empowers many attractive applications by simultaneously recording spatial and angular information of light rays. In order to meet the challenges of LF storage and transmission, many view reconstruction-based LF compression methods are put forward. However, occlusion issue and under-exploitation of LF rich structure information limit the view reconstruction qualities, which further influence LF compression efficiency. In order to alleviate these problems, in this paper, we propose a geometry-aware view reconstruction network for LF compression. In our method, only sparsely-sampled LF views are encoded, which are further used as priors to reconstruct the un-sampled LF views at the decoder side. The proposed reconstruction process contains two stages including geometry-aware reconstruction and texture refinement. The geometry-aware reconstruction stage utilizes a multi-stream framework, which can fully explore LF spatial-angular, location and geometry information. The texture refinement stage can adequately fuse such rich LF information to further improve LF reconstruction quality. Comprehensive experimental results validate the superiority of the proposed method. The rate-distortion performance and the perceptual quality of reconstructed views further demonstrate that the proposed method can save more bitrate while increasing LF reconstruction quality.

Ultrasensitive and Self-Powered Terahertz Detection Driven by Nodal-Line Dirac Fermions and Van der Waals Architecture

Terahertz detection has been highly sought to open a range of cutting-edge applications in biomedical, high-speed communications, astronomy, security screening, and military surveillance. Nonetheless, these ideal prospects are hindered by the difficulties in photodetection featuring self-powered operation at room temperature. Here, this challenge is addressed for the first time by synthesizing the high-quality ZrGeSe with extraordinary quantum properties of Dirac nodal-line semimetal. Benefiting from its high mobility and gapless nature, a metal-ZrGeSe-metal photodetector with broken mirror symmetry allows for a high-efficiency photoelectric conversion assisted by the photo-thermoelectric effect. The designed architecture features ultrahigh sensitivity, excellent ambient stability, and an efficient rectified signal even above 0.26 THz. Maximum responsivity larger than 0.11 A W-1 , response time of 8.3 µs, noise equivalent power (NEP) less than 0.15 nW Hz-1/2 , and demonstrative imaging application are all achieved. The superb performances with a lower dark current and NEP less than 15 pW Hz-1/2 are validated through integrating the van der Waals heterostructure. These results open up an appealing perspective to explore the nontrivial topology of Dirac nodal-line semimetal by devising the peculiar device geometry that allows for a novel roadmap to address targeted terahertz application requirements.

Polymer-Supported Liquid Layer Electrolyzer Enabled Electrochemical CO2 Reduction to CO with High Energy Efficiency

The electrochemical conversion of carbon dioxide (CO2 ) to carbon monoxide (CO) is a favorable approach to reduce CO2 emission while converting excess sustainable energy to important chemical feedstocks. At high current density (>100 mA cm-2 ), low energy efficiency (EE) and unaffordable cell cost limit the industrial application of conventional CO2 electrolyzers. Thus, a crucial and urgent task is to design a new type of CO2 electrolyzer that can work efficiently at high current density. Here we report a polymer-supported liquid layer (PSL) electrolyzer using polypropylene non-woven fabric as a separator between anode and cathode. Ag based cathode was fed with humid CO2 and potassium hydroxide was fed to earth-abundant NiFe-based anode. In this configuration, the PSL provided high-pH condition for the cathode reaction and reduced the cell resistance, achieving a high full cell EE over 66 % at 100 mA cm-2 .

Synthetic Approaches to Tricyclic Aminoketones in the Total Synthesis of Aspidosperma and Kopsia Alkaloids

Aspidosperma and kopsia alkaloids are significant functional molecules because of their potent biological activities. Their intricate structures present an intrinsic synthetic challenge and thus attract significant attention from synthetic organic academic community. Over the past decades, a series of elegant strategies has been developed, in particular, the Stork's original Fischer indolization of tricyclic aminoketones 1. Herein, we report a comprehensive review on various synthetic approaches access to tricyclic aminoketones 1 and provide a practical guidance to readers whose are interested in employing tricyclic aminoketones 1 as versatile building blocks in the realm of total synthesis of aspidosperma, kopsia and structurally related alkaloids.

M 3Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening From CT Imaging

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preventing the spread of the pandemic. Considering the limited training cases and resources (e.g, time and budget), we propose a Multi-task Multi-slice Deep Learning System (M 3Lung-Sys) for multi-class lung pneumonia screening from CT imaging, which only consists of two 2D CNN networks, i.e., slice- and patient-level classification networks. The former aims to seek the feature representations from abundant CT slices instead of limited CT volumes, and for the overall pneumonia screening, the latter one could recover the temporal information by feature refinement and aggregation between different slices. In addition to distinguish COVID-19 from Healthy, H1N1, and CAP cases, our M 3Lung-Sys also be able to locate the areas of relevant lesions, without any pixel-level annotation. To further demonstrate the effectiveness of our model, we conduct extensive experiments on a chest CT imaging dataset with a total of 734 patients (251 healthy people, 245 COVID-19 patients, 105 H1N1 patients, and 133 CAP patients). The quantitative results with plenty of metrics indicate the superiority of our proposed model on both slice- and patient-level classification tasks. More importantly, the generated lesion location maps make our system interpretable and more valuable to clinicians.

Digital Quantum Simulation of Nonadiabatic Geometric Gates via Shortcuts to Adiabaticity

Geometric phases are used to construct quantum gates since it naturally resists local noises, acting as the modularized units of geometric quantum computing. Meanwhile, fast nonadiabatic geometric gates are required for reducing the information loss induced by decoherence. Here, we propose a digital simulation of nonadiabatic geometric quantum gates in terms of shortcuts to adiabaticity (STA). More specifically, we combine the invariant-based inverse engineering with optimal control theory for designing the fast and robust Abelian geometric gates against systematic error, in the context of two-level qubit systems. We exemplify X and T gates, in which the fidelities and robustness are evaluated by simulations in ideal quantum circuits. Our results can also be extended to constructing two-qubit gates, for example, a controlled-PHASE gate, which shares the equivalent effective Hamiltonian with rotation around the Z-axis of a single qubit. These STA-inspired nonadiabatic geometric gates can realize quantum error correction physically, leading to fault-tolerant quantum computing in the Noisy Intermediate-Scale Quantum (NISQ) era.

UBTOR/KIAA1024 regulates neurite outgrowth and neoplasia through mTOR signaling

The mTOR signaling pathways regulate cell growth and are involved in multiple human diseases. Here, we identify UBTOR, a previously unannotated gene as a functional player in regulating cell growth and mTOR signaling. Reduction of UBTOR function in cultured hippocampal neurons and PC12 cells promotes neurite outgrowth. UBTOR depletion activates mTOR signaling and promotes cell growth, whilst UBTOR overexpression suppresses colony formation in cancer cell lines. Studies in cultured cells and zebrafish model show that UBTOR inhibits mTOR signaling by stabilizing the mTOR complex component DEPTOR, and ubtor gene disruption result in higher mTOR activity and aggravate HRAS(G12V) induced neoplasia in the zebrafish. Lastly, UBTOR depletion promotes tumor growth and mTOR signaling in a xenograft mouse model. Together, our results demonstrate how UBTOR regulates cell growth and neoplasia via mTOR signaling.

Cell growth is a fundamental aspect of cell behavior in all organisms. The mTOR signaling pathways are essential for cell growth and clinically mis-regulation of the mTOR pathways are implicated in human diseases including tumor formation, obesity, epilepsy, autism and neurodegeneration. Here, we identify a novel gene, Ubtor as a functional player in regulating cell growth and mTOR signaling. Inhibiting Ubtor function promotes cell growth in neurons and cancer cells. Increasing Ubtor function reduces cancer cell growth. Functional analyses in human cells and the zebrafish model indicate Ubtor inhibits mTOR signaling by stabilizing the mTOR complex component DEPTOR, and ubtor gene disruption resulted in higher mTOR activity and aggravated cancer formation in the zebrafish. UBTOR depletion promotes tumor growth and mTOR signaling in xenograft-bearing mice. Thus our study provide evidence that Ubtor constitutes a novel negative feedback mechanism to control mTOR signaling and cell growth, and manipulations of Ubtor function may potentially be utilized to optimize mTOR signaling activities for treatments of cancers and other diseases.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.