A CO2‐mediated hydrogen storage energy cycle is a promising way to implement a hydrogen economy, but the exploration of efficient catalysts to achieve this process remains challenging. Herein, ...sub‐nanometer Pd–Mn clusters were encaged within silicalite‐1 (S‐1) zeolites by a ligand‐protected method under direct hydrothermal conditions. The obtained zeolite‐encaged metallic nanocatalysts exhibited extraordinary catalytic activity and durability in both CO2 hydrogenation into formate and formic acid (FA) dehydrogenation back to CO2 and hydrogen. Thanks to the formation of ultrasmall metal clusters and the synergic effect of bimetallic components, the PdMn0.6@S‐1 catalyst afforded a formate generation rate of 2151 molformate molPd−1 h−1 at 353 K, and an initial turnover frequency of 6860 molH2
molPd−1 h−1 for CO‐free FA decomposition at 333 K without any additive. Both values represent the top levels among state‐of‐the‐art heterogeneous catalysts under similar conditions. This work demonstrates that zeolite‐encaged metallic catalysts hold great promise to realize CO2‐mediated hydrogen energy cycles in the future that feature fast charge and release kinetics.
Sub‐nanometer Pd–Mn clusters were encaged within silicalite‐1 zeolites by a ligand‐protected method under direct hydrothermal conditions. The obtained zeolite‐encaged metallic nanocatalysts exhibited a record formate generation rate of 2151 molformate molPd−1 h−1 at 353 K, and an excellent initial turnover frequency of 6860 molH2
molPd−1 h−1 for CO‐free formic acid decomposition at 333 K without any additive.
Resistive random access memory (RRAM) is regarded as one of the most promising emerging memory technologies for next-generation embedded, standalone nonvolatile memory (NVM), and storage class memory ...(SCM) due to its speed, density, cost, and scalability. Considerable progress has been made in recent years on the manufacturability of RRAM, with low-density RRAM products now in production and the path to higher density parts becoming clearer. This review updates the learning on the fundamental materials and process integration needed for high-volume manufacturing and summarizes very recent progress on array level performance improvement methodology using novel techniques, and circuit level contributions for different applications. The device performance, array integration, and device/circuit codesign for memory systems are discussed. Novel applications besides embedded memory and standalone memory are addressed, including hardware security, neuromorphic computing, and nonvolatile logic systems.
Torularhodin is a β-carotene-like compound from Sporidiobolus pararoseus, and its protective effect against high-fat diet (HFD)-induced hepatic dyslipidemia and inflammation was investigated. ...Compared to mice of C57BL/6J fed on HFD, the addition of Torularhodin into the HFD (HFD-T) significantly reduced body weight, serum triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), and the inflammatory mediators of TNF-α, IL-6, IL-1β, and lipopolysaccharide (LPS). A significant increase of high-density lipoprotein cholesterol (HDL-c), which is beneficial to cholesterol clearance, was also observed in HFD-T group. Proteomic analysis showed HDL-C-c is highly correlated with proteins (e.g., CPT1A and CYP7A1) involved in lipid β-oxidation and bile acid synthesis, whereas the other phenotypic parameters (TC, TG, LDL, and inflammatory cytokines) are highly associated with proteins (e.g., SLC27A4) involved in lipid-uptake. The up-regulated anti-inflammation proteins FAS, BAX, ICAM1, OCLN, GSTP1, FAF1, LRP1, APEX1, ROCK1, MANF, STAT3, and INSR and down-regulated pro-inflammatory proteins OPTN, PTK2B, FADD, MIF, CASP3, YAP1, DNM1L, and NAMPT not only demonstrate the occurrence of HFD-induced hepatic inflammation, but also prove the anti-inflammatory property of Torularhodin. KEGG signaling pathway analysis revealed that the PPARα signaling pathway is likely fundamental to the health function of Torularhodin through up-regulating genes related to fatty acid β-oxidation, cholesterol excretion, HDL-Cc formation, and anti-inflammation. Torularhodin, as a new food resource, may act as a therapeutic agent to prevent hepatic dyslipidemia and related inflammation for improved health.
Scope
Salidroside (SA) is an active compound derived from Rhodiola rosea and is widely used in healthcare foods. However, the underlying mechanism and its specific role in regulating the gut ...microbial community during exercise (Ex) remains unknown.
Methods and results
Mice are subjected to a weight‐loaded swimming test (WST) Ex to determine how gut microbiota affects the antifatigue activity of SA. The SA‐treated group mice (100 mg kg−1.bw.) display a significant increase in swimming time compared to the control group (26.2 versus 10.5 min, p < 0.01), as well as an increase in respiratory enzymatic activities after swimming. The respiratory enzymatic activities are significantly higher in the SA‐treated group than in the RS (regular rest) group after swimming. The bacteria profiles in the Ex + SA group change significantly with higher species diversity and abundance. Receiver operating characteristic (ROC) curves of Alistipes, Rikenellaceae, Parabacteroides, Candidatus Arthromitus, and Lactobacillus indicate a high diagnostic utility to distinguish SA treatment. Microbial function analysis shows that SA may improve Ex‐induced fatigue by modulating energy metabolism‐related processes.
Conclusions
SA demonstrates antifatigue effects on various levels of regulating energy metabolism and microbial composition, providing insights into the underlying mechanisms of SA as a natural prebiotic.
Salidroside (SA) is an active compound derived from Rhodiola rosea, which could enhance the motor performance and alleviate host's exercise (Ex)‐induced injuries. The antifatigue effect of SA is probably associated with its specific role in regulating gut microbial composition and functions via bacterial metabolic pathways during Ex.
Associative memory is one of the significant characteristics of the biological brain. However, it has yet to be realized in a large memristor array due to the high requirements on the memristor ...device. In this work, the multilevel memristor cell is optimized by employing an electro‐thermal modulation layer. Memristor devices show both high resistance, cell‐to‐cell uniformity, and multilevel resistive switching behaviors with good reliability. A Hopfield neural network is experimentally demonstrated on a 1k memristor array that is capable of realizing the associative memory function for emotion image recovery. By using both asynchronous and synchronous refresh schemes, complete emotion images can be recalled from partial information.
In this work, a multilevel memristor cell is optimized by employing an electro‐thermal modulation layer. Memristor devices show both high resistance, cell‐to‐cell uniformity, and multilevel resistive switching behaviors with good reliability. A Hopfield neural network is experimentally demonstrated on a 1k memristor array that can realize the associative memory function for emotion images recovery.
Antibiotic resistance has become a global public health problem. Recently, various environmental pollutants have been reported to induce the proliferation of antibiotic resistance. However, the ...impact of multiple pollutants (e.g., heavy metals and antibiotics), which more frequently occur in practical environments, is poorly understood. Herein, one widely distributed heavy metal (Ag+) and one frequently detected antibiotic (tetracycline) were chosen to investigate their coexisting effect on the proliferation of antibiotic resistance in the activated sludge system. Results show that the co-occurrence of Ag+ and tetracycline at environmentally relevant concentrations exhibited no distinct inhibition in reactor performances. However, they inhibited the respiratory activity by 42%, destroyed the membrane structure by 218%, and increased membrane permeability by 29% compared with the blank control bioreactor. Moreover, the relative abundances of target antibiotic resistance genes (ARGs) (e.g., tetA, blaTEM-1, and sulII) in effluent after exposure of coexisting Ag+ and tetracycline were increased by 92–1983% compared with those in control reactor, which were 1.1–4.3 folds higher than the sum of the sole ones. These were possibly attributed to the enrichments of antibiotic-resistant bacteria. The results would illumine the coexisting effect of heavy metals and antibiotics on the dissemination of ARGs in activated sludge system.
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•Coexisting Ag+ and TC did not inhibit the bioreactor performance.•Coexisting Ag+ and TC caused more microbial damage.•Coexisting Ag+ and TC enriched ARGs in sludge and effluent.•Coexisting Ag+ and TC enriched heavy metal and antibiotic-resistant bacteria.
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•Successful synthesis of kilogram-scale Au1/CeO2 SACs with ball milling approach.•Au1/CeO2 SACs are highly active, selective, and extremely stable for PROX reaction.•The Au1/CeO2 SACs ...with different preparation scales show essentially identical catalyst structure and catalytic performance.•The results show wide applicability of ball milling method to fabricate a family of oxide-supported noble metal SACs.
Although CeO2-supported Au single atoms (Au1/CeO2) have great potential in preferential oxidation of CO (PROX) reaction, the large-scale synthesis of such single-atom catalysts (SACs) is still greatly challenging. Herein, we develop a dry ball milling method for the mass production of Au1/CeO2 SACs in large quantities (>1 kg). The as-prepared Au1/CeO2 SACs were demonstrated as highly active, selective, and stable catalysts for PROX at 120 °C with 100% CO conversion. The TOFs of Au1/CeO2 SACs for H2 oxidation at 120 °C (<0.01 s−1) were about two orders of magnitude lower than that for CO oxidation. Moreover, the four Au1/CeO2 SACs with different preparation scales showed essentially identical catalyst structure as well as catalytic performance. This approach can also be extended to prepare a family of oxide-supported noble metal SACs, which may pave a facile path for the mass production of oxide-supported SACs to meet industrialization production requirements.
G-quadruplex (G4) is a very interesting DNA structure, commonly associated with cancer and its treatment. With flexible binding ability, G4 has been extended as a significant component in biosensors. ...On account of its simple operation, high sensitivity and low cost, G4-based biosensors have attracted considerable interest for the detection of food contaminants. In this review, research published in recent 5 years is collated from a principle perspective, that is target recognition and signal transduction. Contaminants with G4 binding capacity are illustrated, emerging G4-based biosensors including colorimetric, electrochemical and fluorescent sensors are also elaborated. The current review indicates that G4 has provided an efficient and effective solution for the rapid detection of food contaminants. A distinctive feature of G4 as recognition unit is the simple composition, but the selectivity is still unsatisfactory. As signal reporter, G4/hemin DNAzyme has not only achieved amplified signals, but also enabled visualized detection, which offers great potential for on-site measurement. With improved selectivity and visualized signal, the combination of aptamer and G4 seems to be an ideal strategy. This promising combination should be developed for the real-time monitor of multiple contaminants in food matrix.
Resistive random access memory (RRAM) exhibits advantages, such as high speed, simple structure, and good compatibility with CMOS technology. However, an additional forming step is usually ...inevitable, which requires cell-by-cell verification and can be very time-consuming. This article proposes a novel dual-step page-forming method that can realize low-current forming and improve a bit error rate (BER). Based on this technique and corresponding circuit, a no-verify page-forming scheme is proposed and can achieve a fast-forming speed of 7.56 Mb/s. Moreover, the impact of parameters, such as forming voltage and forming time in the forming process on the BER, is discussed. In addition, to achieve lower BER and better reliability, a two-transistor-two-resistor (2T2R) cell structure is adopted, and both digital verify (DV) and analog verify (AV) methods are proposed. The proposed page-forming and two verify methods are experimentally validated on a 1-MB RRAM chip. An ultralow BER of 10−5/10−6 (DV/AV) without any error correction is achieved. Excellent endurance (>107 cycles for both AV and DV) and retention (>10 years at 25 °C for AV) are also demonstrated on the chip level. Overall, this work demonstrates a useful strategy to design high-reliability RRAM chip with excellent memory performance.
Resistive crossbars implement parallel vector-matrix multiplication (VMM) in analog fashion, and thus enable fast and energy-efficient neuromorphic systems. However, interconnect resistance and ...resistive switching devices form a complex resistance network with sneak paths. It could result in severe distortions on the output currents. When implementing neural networks, current distortions also cause significant accuracy loss. This article proposes an accurate and computationally efficient model of VMM in resistive crossbars, called diagonal matrix regression (DMR), and incorporates the model into the topology of neural networks as DMR layer (DMRL). Given an <inline-formula> <tex-math notation="LaTeX">{m}{\times }{n} </tex-math></inline-formula> crossbar, two diagonal matrices are calculated directly according to the resistance network in a time complexity of only <inline-formula> <tex-math notation="LaTeX">{O}({m}^{2}+{n}^{2}) </tex-math></inline-formula>. No hyper-parameter needs to be determined manually. Modeling of VMM is implemented in a time complexity of only <inline-formula> <tex-math notation="LaTeX">{O}({mn}) </tex-math></inline-formula>. DMRL is developed to replace the weight matrix of neural networks so that the effect of interconnect resistance and the sneak path problem are well handled during ex-situ training. Using this technique, for the task of MNIST and fashion-MNIST classification, the accuracy is dramatically restored.
