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Abstract Deep learning-based methods for generating functional proteins address the growing need for novel biocatalysts, allowing for precise tailoring of functionalities to meet specific requirements. This advancement leads to the development of highly efficient and specialized proteins with diverse applications across scientific, technological, and biomedical fields. This study establishes a pipeline for protein sequence generation with a conditional protein diffusion model, namely CPDiffusion, to create diverse sequences of proteins with enhanced functions. CPDiffusion accommodates protein-specific conditions, such as secondary structures and highly conserved amino acids. Without relying on extensive training data, CPDiffusion effectively captures highly conserved residues and sequence features for specific protein families. We applied CPDiffusion to generate artificial sequences of Argonaute (Ago) proteins based on the backbone structures of wild-type (WT) Kurthia massiliensis Ago (KmAgo) and Pyrococcus furiosus Ago (PfAgo), which are complex multi-domain programmable endonucleases. The generated sequences deviate by up to nearly 400 amino acids from their WT templates. Experimental tests demonstrated that the majority of the generated proteins for both KmAgo and PfAgo show unambiguous activity in DNA cleavage, with many of them exhibiting superior activity as compared to the WT. These findings underscore CPDiffusion’s remarkable success rate in generating novel sequences for proteins with complex structures and functions in a single step, leading to enhanced activity. This approach facilitates the design of enzymes with multi-domain molecular structures and intricate functions through in silico generation and screening, all accomplished without the need for supervision from labeled data.

Abstract Catalyst systems populated by high-density single atoms are crucial for improving catalytic activity and selectivity, which can potentially maximize the industrial prospects of heterogeneous single-atom catalysts (SACs). However, achieving high-loading SACs with metal contents above 10 wt% remains challenging. Here we describe a general negative pressure annealing strategy to fabricate ultrahigh-loading SACs with metal contents up to 27.3–44.8 wt% for 13 different metals on a typical carbon nitride matrix. Furthermore, our approach enables the synthesis of high-entropy single-atom catalysts (HESACs) that exhibit the coexistence of multiple metal single atoms with high metal contents. In-situ aberration-corrected HAADF-STEM (AC-STEM) combined with ex-situ X-ray absorption fine structure (XAFS) demonstrate that the negative pressure annealing treatment accelerates the removal of anionic ligand in metal precursors and boosts the bonding of metal species with N defective sites, enabling the formation of dense N-coordinated metal sites. Increasing metal loading on a platinum (Pt) SAC to 41.8 wt% significantly enhances the activity of propane oxidation towards liquid products, including acetone, methanol, and acetic acid et al. This work presents a straightforward and universal approach for achieving many low-cost and high-density SACs for efficient catalytic transformations.

Surface-enhanced Raman Spectroscopy (SERS) is a nondestructive technique for rapid detection of analytes even at the single-molecule level. However, highly sensitive and reliable SERS substrates are mostly fabricated with complex nanofabrication techniques, greatly restricting their practical applications. A convenient electrochemical method for transforming the surface of commercial gold wires/foils into silver-alloyed nanostructures is demonstrated in this report. Au substrates are treated with repetitive anodic and cathodic bias in an electrolyte of thiourea, in a one-pot one-step manner. X-rays absorption fine structure (XAFS) spectroscopy confirms that the AuAg alloy is induced at the surface. The unique AuAg alloyed surface nanostructures are particularly advantageous when served as SERS substrates, enabling a remarkably sensitive detection of Rhodamine B (a detection limit of 10−14 ​M, and uniform strong response throughout the substrates at 10−12 ​M).

The protein dynamical transition at ~200 K, where the biomolecule transforms from a harmonic, non-functional form to an anharmonic, functional state, has been thought to be slaved to the thermal activation of dynamics in its surface hydration water. Here, by selectively probing the dynamics of protein and hydration water using elastic neutron scattering and isotopic labeling, we found that the onset of anharmonicity in the two components around 200 K is decoupled. The one in protein is an intrinsic transition, whose characteristic temperature is independent of the instrumental resolution time, but varies with the biomolecular structure and the amount of hydration, while the one of water is merely a resolution effect.

Abstract The nitrate (NO3 −) electroreduction into ammonia (NH3) represents a promising approach for sustainable NH3 synthesis. However, the variation of adsorption configurations renders great difficulties in the simultaneous optimization of binding energy for the intermediates. Though the extensively reported Cu-based electrocatalysts benefit NO3 − adsorption, one of the key issues lies in the accumulation of nitrite (NO2 −) due to its weak adsorption, resulting in the rapid deactivation of catalysts and sluggish kinetics of subsequent hydrogenation steps. Here we report a tandem electrocatalyst by combining Cu single atoms catalysts with adjacent Co3O4 nanosheets to boost the electroreduction of NO3 − to NH3. The obtained tandem catalyst exhibits a yield rate for NH3 of 114.0 mg $${}_{{{{{{\rm{NH}}}}}}_3}$$ NH 3 h−1 cm−2, which exceeds the previous values for the reported Cu-based catalysts. Mechanism investigations unveil that the combination of Co3O4 regulates the adsorption configuration of NO2 − and strengthens the binding with NO2 −, thus accelerating the electroreduction of NO3 − to NH3.

Abstract Metal–organic frameworks have drawn attention as potential catalysts owing to their unique tunable surface chemistry and accessibility. However, their application in thermal catalysis has been limited because of their instability under harsh temperatures and pressures, such as the hydrogenation of CO2 to methanol. Herein, we use a controlled two-step method to synthesize finely dispersed Cu on a zeolitic imidazolate framework-8 (ZIF-8). This catalyst suffers a series of transformations during the CO2 hydrogenation to methanol, leading to ~14 nm Cu nanoparticles encapsulated on the Zn-based MOF that are highly active (2-fold higher methanol productivity than the commercial Cu–Zn–Al catalyst), very selective (>90%), and remarkably stable for over 150 h. In situ spectroscopy, density functional theory calculations, and kinetic results reveal the preferential adsorption sites, the preferential reaction pathways, and the reverse water gas shift reaction suppression over this catalyst. The developed material is robust, easy to synthesize, and active for CO2 utilization.

Abstract Seawater electrolysis offers a renewable, scalable, and economic means for green hydrogen production. However, anode corrosion by Cl- pose great challenges for its commercialization. Herein, different from conventional catalysts designed to repel Cl- adsorption, we develop an atomic Ir catalyst on cobalt iron layered double hydroxide (Ir/CoFe-LDH) to tailor Cl- adsorption and modulate the electronic structure of the Ir active center, thereby establishing a unique Ir-OH/Cl coordination for alkaline seawater electrolysis. Operando characterizations and theoretical calculations unveil the pivotal role of this coordination state to lower OER activation energy by a factor of 1.93. The Ir/CoFe-LDH exhibits a remarkable oxygen evolution reaction activity (202 mV overpotential and TOF = 7.46 O2 s−1) in 6 M NaOH+2.8 M NaCl, superior over Cl--free 6 M NaOH electrolyte (236 mV overpotential and TOF = 1.05 O2 s−1), with 100% catalytic selectivity and stability at high current densities (400-800 mA cm−2) for more than 1,000 h.

Abstract The rational design of efficient bifunctional single-atom electrocatalysts for industrial water splitting and the comprehensive understanding of its complex catalytic mechanisms remain challenging. Here, we report a Ni single atoms supported on oxygen-incorporated Mo2C via Ni-O-Mo bridge bonds, that gives high oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) bifunctional activity. By ex situ synchrotron X-ray absorption spectroscopy and electron microscopy, we found that after HER, the coordination number and bond lengths of Ni-O and Ni-Mo (Ni-O-Mo) were all altered, yet the Ni species still remain atomically dispersed. In contrast, after OER, the atomically dispersed Ni were agglomerated into very small clusters with new Ni-Ni (Ni-O-Ni) bonds appeared. Combining experimental results and DFT calculations, we infer the oxidation degree of Mo2C and the configuration of single-atom Ni are both vital for HER or OER. This study provides both a feasible strategy and model to rational design highly efficient electrocatalysts for water electrolysis.

Abstract Copper-based catalysts serve as the predominant methanol steam reforming material although several fundamental issues remain ambiguous such as the identity of active center and the aspects of reaction mechanism. Herein, we prepare Cu/Cu(Al)O x catalysts with amorphous alumina-stabilized Cu2O adjoining Cu nanoparticle to provide Cu0−Cu+ sites. The optimized catalyst exhibits 99.5% CH3OH conversion with a corresponding H2 production rate of 110.8 μmol s−1 gcat −1 with stability over 300 h at 240 °C. A binary function correlation between the CH3OH reaction rate and surface concentrations of Cu0 and Cu+ is established based on kinetic studies. Intrinsic active sites in the catalyst are investigated with in situ spectroscopy characterization and theoretical calculations. Namely, we find that important oxygen-containing intermediates (CH3O* and HCOO*) adsorb at Cu0−Cu+ sites with a moderate adsorption strength, which promotes electron transfer from the catalyst to surface species and significantly reduces the reaction barrier of the C−H bond cleavage in CH3O* and HCOO* intermediates.

Abstract Electrocatalytic acetylene semi-hydrogenation to ethylene powered by renewable electricity represents a sustainable pathway, but the inadequate current density and single-pass yield greatly impedes the production efficiency and industrial application. Herein, we develop a F-modified Cu catalyst that shows an industrial partial current density up to 0.76 A cm−2 with an ethylene Faradic efficiency surpass 90%, and the maximum single-pass yield reaches a notable 78.5%. Furthermore, the Cu-F showcase the capability to directly convert acetylene into polymer-grade ethylene in a tandem flow cell, almost no acetylene residual in the production. Combined characterizations and calculations reveal that the Cuδ+ (near fluorine) enhances the water dissociation, and the generated active hydrogen are immediately transferred to Cu0 (away from fluorine) and react with the locally adsorbed acetylene. Therefore, the hydrogen evolution reaction is surpassed and the overall acetylene semi-hydrogenation performance is boosted. Our findings provide new opportunity towards rational design of catalysts for large-scale electrosynthesis of ethylene and other important industrial raw.

Highlights Oxygen-coordinated single-atom Mn catalyst was fabricated via introducing oxygen functional groups rich bacterial cellulose as the adsorption regulator through a combined impregnation–pyrolysis–etching synthetic route. Mn–O–C as the electrocatalyst exhibits superior electrocatalytic activity toward ammonia synthesis with a maximum NH3 yield rate of 1476.9 ± 62.6 μg h −1 cm −2 at − 0.7 V (vs. RHE) and a faradaic efficiency of 89.0 ± 3.8% at − 0.5 V (vs. RHE) under ambient conditions. Electrocatalytic mechanism of Mn–(O–C2)4 site for nitrate reduction reaction is unveiled by a combination of in situ spectroscopy characterization and computational study.

The interaction between protein and water plays a pivotal role in shaping the structure, dynamics, and function of biomacromolecules. A comprehensive understanding of this intricate interplay necessitates a systematic evaluation of interaction strength and its consequential impact on the dynamics of proteins and water across diverse protein systems. Despite numerous works on understanding the dynamics of water and proteins and the coupling between them, there are still unanswered questions. Here, we combine neutron scattering and isotope labeling to probe the dynamics of proteins and their hydration water in a variety of protein systems. We consider proteins of different structures and varying thermostability as well as proteins within living cells with distinct growth temperatures. Simultaneous characterization of protein and hydration water dynamics across diverse systems was achieved. Moreover, we performed water sorption isothermal measurements on three representative proteins to correlate the observed dynamics with the strength of the interaction energies governing each system. The experimental results underscore that proteins manifesting stronger attractive interactions with water display diffusionlike dynamics with higher flexibility upon hydration, concomitant with a reduced mobility in hydration water. Significantly, our findings suggest that, in fact, it is the interaction between protein and its hydration water that facilitates the transfer of mobility from water to protein, with stronger interactions correlating to greater protein flexibility and slower hydration water diffusion.

Abstract Neurotoxicity of organophosphate compounds (OPs) can catastrophically cause nervous system injury by inhibiting acetylcholinesterase (AChE) expression. Although artificial systems have been developed for indirect neuroprotection, they are limited to dissociating P-O bonds for eliminating OPs. However, these systems have failed to overcome the deactivation of AChE. Herein, we report our finding that Al3+ is engineered onto the nodes of metal–organic framework to synthesize MOF-808-Al with enhanced Lewis acidity. The resultant MOF-808-Al efficiently mimics the catalytic behavior of AChE and has a self-defense ability to break the activity inhibition by OPs. Mechanism investigations elucidate that Al3+ Lewis acid sites with a strong polarization effect unite the highly electronegative –OH groups to form the enzyme-like catalytic center, resulting in superior substrate activation and nucleophilic attack ability with a 2.7-fold activity improvement. The multifunctional MOF-808-Al, which has satisfactory biosafety, is efficient in reducing neurotoxic effects and preventing neuronal tissue damage.

Abstract Electrooxidation of biomass platforms provides a sustainable route to produce valuable oxygenates, but the practical implementation is hampered by the severe carbon loss stemming from inherent instability of substrates and/or intermediates in alkaline electrolyte, especially under high concentration. Herein, based on the understanding of non-Faradaic degradation, we develop a single-pass continuous flow reactor (SPCFR) system with high ratio of electrode-area/electrolyte-volume, short duration time of substrates in the reactor, and separate feeding of substrate and alkaline solution, thus largely suppressing non-Faradaic degradation. By constructing a nine-stacked-modules SPCFR system, we achieve electrooxidation of glucose-to-formate and 5-hydroxymethylfurfural (HMF)-to-2,5-furandicarboxylic acid (FDCA) with high single-pass conversion efficiency (SPCE; 81.8% and 95.8%, respectively) and high selectivity (formate: 76.5%, FDCA: 96.9%) at high concentrations (formate: 562.8 mM, FDCA: 556.9 mM). Furthermore, we demonstrate continuous and kilogram-scale electrosynthesis of potassium diformate (0.7 kg) from wood and soybean oil, and FDCA (1.17 kg) from HMF. This work highlights the importance of understanding and suppressing non-Faradaic degradation, providing opportunities for scalable biomass upgrading using electrochemical technology.

Abstract The metal-support interaction (MSI) in heterogeneous catalysts plays a crucial role in reforming reaction to produce renewable hydrogen, but conventional objects are limited to single metal and support. Herein, we report a type of RhNi/TiO2 catalysts with tunable RhNi-TiO2 strong bimetal-support interaction (SBMSI) derived from structure topological transformation of RhNiTi-layered double hydroxides (RhNiTi-LDHs) precursors. The resulting 0.5RhNi/TiO2 catalyst (with 0.5 wt.% Rh) exhibits extraordinary catalytic performance toward ethanol steam reforming (ESR) reaction with a H2 yield of 61.7%, a H2 production rate of 12.2 L h−1 gcat −1 and a high operational stability (300 h), which is preponderant to the state-of-the-art catalysts. By virtue of synergistic catalysis of multifunctional interface structure (Rh-Ni δ−-O v -Ti3+; O v denotes oxygen vacancy), the generation of formate intermediate (the rate-determining step in ESR reaction) from steam reforming of CO and CH x is significantly promoted on 0.5RhNi/TiO2 catalyst, accounting for its ultra-high H2 production.

Amorphous metal catalysts often exhibit appealing catalytic properties, however, accurate control synthesis of amorphous nano-metal catalysts is a challenge. Here, the authors report a feasible strategy to prepare the amorphous Cu catalysts by supercritical CO2 treatment followed by electroreduction. The resulted catalyst shows high selectivity towards multi-carbon products for CO2 electroreduction.

A photocatalyst for CO2 reduction to C3H8 is prepared by implanting Cu single atoms on vacancy rich TiO2 single layers. Key reaction intermediates, *CHOCO and *CH2OCOCO, are stabilized on the catalyst which promotes C-C bond formation.

Abstract Despite the desirability of metal–organic frameworks (MOFs) as heterogeneous photocatalysts, current strategies available to enhance the performance of MOF photocatalysts are complicated and expensive. Herein, a simple strategy is presented for improving the activity of MOF photocatalysts by regulating the atomic interface structure of the metal active sites on the MOF. In this study, MOF (PCN‐222) is hybridized with cellulose acetate (CA@PCN‐222) through an optimized atomic interface strategy, which lowers the average valence state of Zr ions. The electronic metal‐support interaction mechanism of CA@PCN‐222 is revealed by evaluating the photocatalytic CO2 reduction reaction (CO2RR). The experimental results suggested that the electron migration efficiency at the atomic interface of the MOFs strongly coupled with cellulose is significantly improved. In particular, the CO2RR to formate activity of CA@PCN‐222 photocatalyst greatly increased from 778.2 to 2816.0 µmol g−1 compared with pristine PCN‐222 without cellulose acetate. The findings suggest that the strongly coupled metal–ligand moiety at the atomic interface of MOFs may play a synergistic role in heterogeneous catalysts.

Abstract Simultaneously optimizing elementary steps, such as water dissociation, hydroxyl transferring, and hydrogen combination, is crucial yet challenging for achieving efficient hydrogen evolution reaction (HER) in alkaline media. Herein, Ru single atom‐doped WO2 nanoparticles with atomically dispersed Ru–W pair sites (Ru–W/WO2‐800) are developed using a crystalline lattice‐confined strategy, aiming to gain efficient alkaline HER. It is found that Ru–W/WO2‐800 exhibits remarkable HER activity, characterized by a low overpotential (11 mV at 10 mA cm−2), notable mass activity (5863 mA mg−1 Ru at 50 mV), and robust stability (500 h at 250 mA cm−2). The highly efficient activity of Ru–W/WO2‐800 is attributed to the synergistic effect of Ru–W sites through ensemble catalysis. Specifically, the W sites expedite rapid hydroxyl transferring and water dissociation, while the Ru sites accelerate the hydrogen combination process, synergistically facilitating the HER activity. This study opens a promising pathway for tailoring the coordination environment of atomic‐scale catalysts to achieve efficient electro‐catalysis.

Previous studies have reconstructed ancestral metabolism using sequence-based approaches. This study uses a high-throughput version of AlphaFold2 to compare proteome-wide 3D structure predictions of two representative strains of ancient archaea and bacteria.

Considerable attention has been drawn to tune the geometric and electronic structure of interfacial catalysts via modulating strong metal-support interactions (SMSI). Here the authors report the remarkable catalytic performance of CO hydrogenation over an interfacial TiO2−x /Ni catalyst by means of SMSI.

The selective oxidation of glycerol to glyceric acid is an important value-added cascade catalytic process. Here the authors report a cascade synergistic catalysis strategy by atomic and low-coordinated cluster Pt on well-defined Cu-CuZrOx to simultaneously achieve high activity and selectivity.

ObjectiveThe multi-subject brain–computer interface (mBCI) is becoming a key tool for the analysis of group behaviors. It is necessary to adopt a neural recording system for collaborative brain signal acquisition, which is usually in the form of a fixed wire.ApproachIn this study, we designed a wireless group-synchronized neural recording system that supports real-time mBCI and event-related potential (ERP) analysis. This system uses a wireless synchronizer to broadcast events to multiple wearable EEG amplifiers. The simultaneously received broadcast signals are marked in data packets to achieve real-time event correlation analysis of multiple targets in a group.Main resultsTo evaluate the performance of the proposed real-time group-synchronized neural recording system, we conducted collaborative signal sampling on 10 wireless mBCI devices. The average signal correlation reached 99.8%, the amplitude of average noise was 0.87 μV, and the average common mode rejection ratio (CMRR) reached 109.02 dB. The minimum synchronization error is 237 μs. We also tested the system in real-time processing of the steady-state visual-evoked potential (SSVEP) ranging from 8 to 15.8 Hz. Under 40 target stimulators, with 2 s data length, the average information transfer rate (ITR) reached 150 ± 20 bits/min, and the highest reached 260 bits/min, which was comparable to the marketing leading EEG system (the average: 150 ± 15 bits/min; the highest: 280 bits/min). The accuracy of target recognition in 2 s was 98%, similar to that of the Synamps2 (99%), but a higher signal-to-noise ratio (SNR) of 5.08 dB was achieved. We designed a group EEG cognitive experiment; to verify, this system can be used in noisy settings.SignificanceThe evaluation results revealed that the proposed real-time group-synchronized neural recording system is a high-performance tool for real-time mBCI research. It is an enabler for a wide range of future applications in collaborative intelligence, cognitive neurology, and rehabilitation.

UiO-66-NH2, an important metal–organic framework, is usually synthesized by solvothermal method and the particle size is generally larger than 200 nm, which limits its catalytic applications in chemical reactions. It is very meaningful to produce UiO-66-NH2 nanoparticles with ultra-small size, but remains challenging. Herein, we synthesized UiO-66-NH2 nanoparticles in size of 8–15 nm that are immobilized on g-C3N4 nanosheets. Compared with the UiO-66-NH2 synthesized by the traditional solvothermal method (> 200 nm), the ultra-small UiO-66-NH2 nanoparticles immobilized on g-C3N4 have more unsaturated coordination positions and increased Lewis acidity. Owing to these combined advantages, the ultra-small UiO-66-NH2 nanoparticles exhibit greatly improved catalytic activity for Meerwein–Ponndorf–Verley reaction than larger UiO-66-NH2 particles.

It is challenging to break the activity–stability trade-off in Fe–N–C fuel cell catalysts. Here, the authors show that interactions between iron atoms and clusters accelerate reaction kinetics and suppress demetalation to improve fuel cell stability.

Abstract Understanding the dynamical evolution from metal ions to single atoms is of great importance to the rational development of synthesis strategies for single atom catalysts (SACs) against metal sintering during pyrolysis. Herein, an in situ observation is disclosed that the formation of SACs is ascertained as a two‐step process. There is initially metal sintering into nanoparticles (NPs) (500–600 °C), followed by the conversion of NPs into metal single atoms (Fe, Co, Ni, Cu SAs) at higher temperature (700–800 °C). Theoretical calculations together with control experiments based on Cu unveil that the ion‐to‐NP conversion can arise from the carbon reduction, and NP‐to‐SA conversion being steered by generating more thermodynamically stable Cu‐N4 configuration instead of Cu NPs. Based on the evidenced mechanism, a two‐step pyrolysis strategy to access Cu SACs is developed, which exhibits excellent ORR performance.

Naturally occurring oxides could react with zinc oxide (ZnO) nanoparticles (NPs) and then change its transformation and toxicity to ecological receptors. The reaction may be affected by a variety of environmental factors, yet the relevant processes and mechanisms are limitedly investigated. Natural prevalent ligands, as an important factor, can sorb on natural oxide minerals and change its surface property, finally affecting ZnO NP transformation. This study investigated the interactions of ZnO NPs with phosphorus ligands (i.e., phytate and orthophosphate) pre-sorbed γ-alumina (γ-Al2O3) via batch experiments and multi-technique analyses. A limited amount of aqueous Zn2+ is observed when the concentration of ZnO NPs is relatively low (

Abstract Efficient electrocatalytic reactions require a coordinated active center that may provide a properly reaction intermediates adsorption in water splitting. Herein, a Ni active center coordination reconstruction method achieved by multidimensional modulation of phase transition, iodine coordination, and vacancy defects is designed and implemented. This coordination reconstruction results in the successful synthesis of Ni5P4−xIx/Ni2P nanocorals that show outstanding bifunctional catalytic activity due to deep optimization of the adsorption energy. The overpotentials of hydrogen evolution reaction and oxygen evolution reaction at 10 mA cm−2 are 46 and 163 mV, respectively. Only 1.46 V is required to drive alkaline overall water splitting. Novel coordination environment is investigated by electron paramagnetic resonance spectroscopy and extended X‐ray absorption fine structure spectroscopy. A 4D integrated material design strategy of “thermodynamic stability‐electronic properties‐charge transfer‐adsorption energy” for water‐splitting catalysts is proposed. This coordination reconstruction concept and material design method provide new perspectives for the research of novel catalysts.

This study reports a fundamentally new and commercially promising chemical looping ammonia oxidation scheme using an inexpensive transition metal oxide, and provides mechanistic insight into the oxygen species governing ammonia oxidation.

Electrochemical alcohol oxidation offers a promising approach to produce valuable chemicals that can be paired with fuel-producing reactions. Here, authors utilize gold and cobalt oxyhydroxide nanomaterials to obtain industrially-relevant electrolyzer current densities for benzyl alcohol oxidation.

Nanozymes have become a new generation of antibiotics with exciting broad-spectrum antibacterial properties and negligible biological toxicity. However, their inherent low catalytic activity limits their antibacterial properties. Herein, Cu single-atom sites/N doped porous carbon (Cu SASs/NPC) is successfully constructed for photothermal-catalytic antibacterial treatment by a pyrolysis-etching-adsorption-pyrolysis (PEAP) strategy. Cu SASs/NPC have stronger peroxidase-like catalytic activity, glutathione (GSH)-depleting function, and photothermal property compared with non-Cu-doped NPC, indicating that Cu doping significantly improves the catalytic performance of nanozymes. Cu SASs/NPC can effectively induce peroxidase-like activity in the presence of H2O2, thereby generating a large amount of hydroxyl radicals (•OH), which have a certain killing effect on bacteria and make bacteria more susceptible to temperature. The introduction of near-infrared (NIR) light can generate hyperthermia to fight bacteria, and enhance the peroxidase-like catalytic activity, thereby generating additional •OH to destroy bacteria. Interestingly, Cu SASs/NPC can act as GSH peroxidase (GSH-Px)-like nanozymes, which can deplete GSH in bacteria, thereby significantly improving the sterilization effect. PTT-catalytic synergistic antibacterial strategy produces almost 100% antibacterial efficiency against Escherichia coli (E. coli) and methicillin-resistant Staphylococcus aureus (MRSA). In vivo experiments show a better PTT-catalytic synergistic therapeutic performance on MRSA-infected mouse wounds. Overall, our work highlights the wide antibacterial and anti-infective bio-applications of Cu single-atom-containing catalysts.

Abstract Direct electrocatalytic oxidation of benzene has been regarded as a promising approach for achieving high‐value phenol product, but remaining a huge challenge. Here an oxygen‐coordinated nickel single‐atom catalyst (Ni–O–C) is reported with bifunctional electrocatalytic activities toward the two‐electron oxygen reduction reaction (2e− ORR) to H2O2 and H2O2‐assisted benzene oxidation to phenol. The Ni–(O–C2)4 sites in Ni–O–C ar proven to be the catalytic active centers for bifunctional 2e− ORR and H2O2‐assisted benzene oxidation processes. As a result, Ni–O–C can afford a benzene conversion as high as 96.4 ± 3.6% with a phenol selectivity of 100% and a Faradaic efficiency (FE) of 80.2 ± 3.2% with the help of H2O2 in 0.1 m KOH electrolyte at 1.5 V (vs RHE). A proof of concept experiment with Ni–O–C concurrently as cathode and anode in a single electrochemical cell demonstrates a benzene conversion of 33.4 ± 2.2% with a phenol selectivity of 100% and a FE of 44.8 ± 3.0% at 10 mA cm−2.

Uncovering the dynamics of active sites in the working conditions is important yet challenging. Here the authors identify dynamic-coupling oxygen on atomically dispersed iridium sites during oxygen evolution reaction using in situ techniques.

Plastic upcycling to value-added products is of great interests. Here the authors investigate a nickel-cobalt phosphide electrocatalyst for electroreforming of polyethylene terephthalate plastic toward valuable potassium diformate, terephthalic acid, and H2 fuel.

Abstract Combining isolated atomic active sites with those in nanoparticles for synergizing complex multistep catalysis is being actively pursued in the design of new electrocatalyst systems. However, these novel systems have been rarely studied due to the challenges with synthesis and analysis. Herein, a synergistically catalytic performance is demonstrated with a 0.89 V (vs reversible hydrogen electrode) onset potential in the four‐step oxygen reduction reaction (ORR) by localizing tungsten single atoms around tungsten nitride nanoparticles confined into nitrogen‐doped carbon (W SAs/WNNC). Through density functional theory calculations, it is shown that each of the active centers in the synergistic entity feature a specific potential‐determining step in their respective reaction pathway that can be merged to optimize the intermediate steps involving scaling relations on individual active centers. Impressively, the W SAs/WNNC as the air cathode in all‐solid‐state Zn‐air and Al‐air batteries demonstrate competitive durability and reversibility, despite the acknowledged low activity of W‐based catalyst toward the ORR.

Efficient production of benzene from lignin is attractive and of great importance, but has not been realized. Here, the authors develop a strategy to transform lignin into benzene over a RuW/zeolite catalyst in water, and the yield of benzene can be as high as 18.8% on lignin weight basis.

Recently, virtual-reality (VR) has been an emerging technology, to this regard, it is widely employed by therapists to provide rich training tasks for the purpose of motor rehabilitation in clinics. Meanwhile, along with the progress of sensing technologies as means for the interaction with virtual environment, a large amount of data, such as motor trajectory, foot pressure or electromyography, is measured via VR-based motor training tasks and is considered as important clues for functional evaluations. However, very few study thoroughly applied the sensor-based data for motor assessment, instead, evaluation scales, such as TEMPA or Fugl-Meyer, were highly relied. In this study, a VR upper-limb motor training system was proposed for stroke rehabilitation. Clinical trials with 22 stroke patients were performed to exanimate the effectiveness of the propose VR system. Moreover, a variety of motor indicators derived via motion trajectory were proposed. Further, integrating multi-model data, such as motion trajectory, task performance and evaluation scales, machine-learning method was applied to develop evidence-based assessment models in order to evaluate upper-limb motor function. The results indicated that the proposed VR system was significantly effective for motor rehabilitation. Also, a few motor indicators were found significantly different between pre and post trials and were highly correlated with the evaluation scales. Finally, with the fusion of multi-model data, the accuracy rate of machine-learning assessment model was up to 92.72% which revealed its great potential for clinical use.

Design of artificial catalysts to mimic enzyme activity and selectivity is a challenge in the catalysis field. Here, the authors design a platinum catalyst with a porous cage ligand which shows enzyme-like properties, such as high hydrosilylation activity and substrate size selectivity, while being recyclable.

The development of spectral efficient solutions for internet of things (IoT) face challenges primarily due to the large-scale placement of an immense number of sensors and devices. Cognitive radio (CR) technology is considered as a potential solution to resolve the spectrum scarcity problems of IoT. Incorporation of CR in IoT encounters various challenges including fast response and efficient spectrum sensing even in low signal to noise ratio. In this study we integrate the basic functionalities of the both CR and IoT technology and present a five layered framework for CR enabled IoT. In addition to the framework we also proposed and develop a spectrum sensing algorithm for CR-based IoT architecture, meeting the efficiency and time sensitivity requirements. The proposed algorithm is more accurate, robust to noisy environment and four times faster than existing approaches. The developed algorithm is compared with existing blind spectrum sensing techniques in term of detection performance, optimization methods and computational complexity. Experimental evaluations with real wireless microphone signals demonstrate the effectiveness of the proposed scheme and show superiority over existing ones.

The spiking neural network (SNN) is a possible pathway for low-power and energy-efficient processing and computing exploiting spiking-driven and sparsity features of biological systems. This article proposes a sparsity-driven SNN learning algorithm, namely backpropagation with sparsity regularization (BPSR), aiming to achieve improved spiking and synaptic sparsity. Backpropagation incorporating spiking regularization is utilized to minimize the spiking firing rate with guaranteed accuracy. Backpropagation realizes the temporal information capture and extends to the spiking recurrent layer to support brain-like structure learning. The rewiring mechanism with synaptic regularization is suggested to further mitigate the redundancy of the network structure. Rewiring based on weight and gradient regulates the pruning and growth of synapses. Experimental results demonstrate that the network learned by BPSR has synaptic sparsity and is highly similar to the biological system. It not only balances the accuracy and firing rate, but also facilitates SNN learning by suppressing the information redundancy. We evaluate the proposed BPSR on the visual dataset MNIST, N-MNIST, and CIFAR10, and further test it on the sensor dataset MIT-BIH and gas sensor. Results bespeak that our algorithm achieves comparable or superior accuracy compared to related works, with sparse spikes and synapses.

Developing effective catalysts based on earth abundant elements is critical for electrochemical CO2 reduction. Here, the authors prepare a manganese single atom catalyst with high CO2 reduction performance, which can be attributed to the Mn-N3 site embedded in graphitic carbon nitride.

Engineering the coordination environment of single atom catalysts offers to opportunity to optimize electrocatalytic activity. In this work, the authors prepare an unsymmetrical Cu-S1N3 single atom site on porous carbon with high performance in the oxygen reduction reaction.

Abstract H9N2 avian influenza virus has spread worldwide, and vaccination with an inactivated virus is currently the major prevention method in China. To further understand the effect of the selection pressure from antibodies on the evolution of H9N2 avian influenza virus, F/98 (A/Chicken/Shanghai/F/98), which is the vaccine representative of H9N2 avian influenza virus in East China, was used for serial passaging for 20 generations in chickens with and without vaccination. After plaque purification from trachea and lung tissues, 390 quasispecies were obtained. The second-generation quasispecies under the selection pressure of vaccine antibodies had undergone 100% antigen variation, while after passaging to the fifth generation, only 30–40% of the quasispecies displayed antigen variation when there was no selection pressure of vaccine antibodies, implying that the selection pressure of vaccine antibodies promotes the antigen variation of F/98. We found for the first time that there were three mutation hotspots in the HA genes of the quasispecies under the selection pressure of vaccine antibodies, which were K131R, A168T, and N201D. Moreover, under the selection pressure of vaccine antibodies, 10 amino acids (67–76) of the NA protein of all quasispecies were deleted, and PB2 of the quasispecies had undergone a high-frequency R355K mutation. However, without selection pressure of vaccine antibodies, NP had undergone two high-frequency mutations, namely, V186I and L466I, and a high-frequency mutation of L77I appeared in the NS gene. This result shows that the vaccine antibody selection pressure could control and regulate gene variation of the F/98 virus. Compared to that of the parental virus F/98, the EID50 of the twentieth passaged virus under the selection pressure of vaccine antibodies did not change, while the EID50 of the twentieth passaged virus without selection pressure of vaccine antibodies was significantly enhanced by 794 times. Furthermore, the twentieth passaged virus with selection pressure from vaccine antibodies lost its lethal ability in embryonated chicken eggs, whereas the EID50 of the twentieth passaged virus without selection pressure of vaccine antibodies increased to 6.3 times that of the F/98 strain. All the above results show that the selection pressure of vaccine antibodies promotes the antigen variation of H9N2 avian influenza virus and plays a role in regulating and controlling gene mutation of H9N2 avian influenza virus.

Abstract Immobilizing metal atoms by multiple nitrogen atoms has triggered exceptional catalytic activity toward many critical electrochemical reactions due to their merits of highly unsaturated coordination and strong metal-substrate interaction. Herein, atomically dispersed Fe-NC material with precise sulfur modification to Fe periphery (termed as Fe-NSC) was synthesized, X-ray absorption near edge structure analysis confirmed the central Fe atom being stabilized in a specific configuration of Fe(N3)(N–C–S). By enabling precisely localized S doping, the electronic structure of Fe-N4 moiety could be mediated, leading to the beneficial adjustment of absorption/desorption properties of reactant/intermediate on Fe center. Density functional theory simulation suggested that more negative charge density would be localized over Fe-N4 moiety after S doping, allowing weakened binding capability to *OH intermediates and faster charge transfer from Fe center to O species. Electrochemical measurements revealed that the Fe-NSC sample exhibited significantly enhanced oxygen reduction reaction performance compared to the S-free Fe-NC material (termed as Fe-NC), showing an excellent onset potential of 1.09 V and half-wave potential of 0.92 V in 0.1 M KOH. Our work may enlighten relevant studies regarding to accessing improvement on the catalytic performance of atomically dispersed M-NC materials by managing precisely tuned local environments of M-Nx moiety.

Producing two-dimensional metal-organic frameworks (MOFs) with highly exposed active surfaces is important for catalysis. Here, authors prepare MOF nanosheets by using CO2 as a capping agent to control the oriented growth of MOFs.

In this study, we built a single photon avalanche diode (SPAD) receiver based underwater wireless optical communication (UWOC) system. The bit error rate (BER) and signal-to-noise ratio (SNR) performance of UWOC with different distances and data transmission rates were obtained. Based on the water attenuation coefficient of 0.12 m-1, a series of neutral density (ND) filters were exploited to attenuate the light output power from the blue laser diode (LD) to simulate the long distance UWOC. The maximum estimated distances of 144 m and 117 m with corresponding BERs of 1.89 × 10-3 and 5.31 × 10-4 at data transmission rates of 500 bps and 2 Mbps were acquired in UWOC system using on-off keying (OOK) modulation scheme, respectively. Furthermore, we compared the differences between free-space and underwater channels, and a divergence angle of ~1.02 mrad was measured experimentally at a distance of 50 m in the free space. The long UWOC distances obtained in this study partly benefit from high sensitivity SPAD, the small laser divergence angle and low light attenuation. This study provides an approach to achieve long distance UWOC using SPAD.

Precise time synchronization becomes a vital constituent due to the rigorous needs of several time-sensitive applications. The clock synchronization protocol is one of the fundamental factors that can define the quality of communication. Our study starts with a brief discussion on the application domain of precise time synchronization and comes with an in-depth study of the synchronization with the main focus on the IEEE 1588 Precision Time Protocol (PTP). We have compared the well-known synchronization techniques and conclude that the PTP is the most appropriate answer to robust clock synchronization though challenges are there that requires thoughtful efforts and modification in the current version. The working mechanism and main components of the PTP network are discussed. We have established a testbench using commercially available devices and development boards to evaluate the PTP performance under different configurations. Major sources of synchronization error and other aspects contributing to precision are examined. This paper discussed numerous approaches that could enhance the performance of the PTP protocol. Structures for PTP based wireless clock synchronization required by advanced applications has also been discussed. In the end, paper focuses on the main industrial application areas in which PTP plays an important role, including WLAN, optical data centers, Smart grid, IEC 61850, etc. We conclude the paper by identifying the future trends and research directions for PTP based clock synchronization.

Unstaffed retail shops have emerged recently and been noticeably changing our shopping styles. In terms of these shops, the design of vending machine is critical to user shopping experience. The conventional design typically uses weighing sensors incapable of sensing what the customer is taking. In the present study, a smart unstaffed retail shop scheme is proposed based on artificial intelligence and the internet of things, as an attempt to enhance the user shopping experience remarkably. To analyze multiple target features of commodities, the SSD ( $300\times 300$ ) algorithm is employed; the recognition accuracy is further enhanced by adding sub-prediction structure. Using the data set of 18, 000 images in different practical scenarios containing 20 different type of stock keeping units, the comparison experimental results reveal that the proposed SSD ( $300\times 300$ ) model outperforms than the original SSD ( $300\times 300$ ) in goods detection, the mean average precision of the developed method reaches 96.1% on the test dataset, revealing that the system can make up for the deficiency of conventional unmanned container. The practical test shows that the system can meet the requirements of new retail, which greatly increases the customer flow and transaction volume.

The industrial synthesis of ammonia using iron-based Haber-Bosch catalyst requires harsh reaction conditions. Here the authors show co-existence of dynamic and steady-state single atom active sites over Co-N-C catalyst to facilitate nitrogen activation for ammonia synthesis under mild conditions.