Atomic Cu Sites Engineering Enables Efficient CO2 Electroreduction to Methane with High CH4/C2H4 Ratio.

Electrochemical reduction of CO2 into high-value hydrocarbons and alcohols by using Cu-based catalysts is a promising and attractive technology for CO2 capture and utilization, resulting from their high catalytic activity and selectivity. The mobility and accessibility of active sites in Cu-based catalysts significantly hinder the development of efficient Cu-based catalysts for CO2 electrochemical reduction reaction (CO2RR). Herein, a facile and effective strategy is developed to engineer accessible and structural stable Cu sites by incorporating single atomic Cu into the nitrogen cavities of the host graphitic carbon nitride (g-C3N4) as the active sites for CO2-to-CH4 conversion in CO2RR. By regulating the coordination and density of Cu sites in g-C3N4, an optimal catalyst corresponding to a one Cu atom in one nitrogen cavity reaches the highest CH4 Faraday efficiency of 49.04% and produces the products with a high CH4/C2H4 ratio over 9. This work provides the first experimental study on g-C3N4-supported single Cu atom catalyst for efficient CH4 production from CO2RR and suggests a principle in designing highly stable and selective high-efficiency Cu-based catalysts for CO2RR by engineering Cu active sites in 2D materials with porous crystal structures.

A Novel Framework to Facilitate User Preferred Tuning for a Robotic Knee Prosthesis.

The tuning of robotic prosthesis control is essential to provide personalized assistance to individual prosthesis users. Emerging automatic tuning algorithms have shown promise to ease the device personalization procedure. However, very few automatic tuning algorithms consider the user preference as the tuning goal, which may limit the adoptability of the robotic prosthesis. In this study, we propose and evaluate a novel prosthesis control tuning framework for a robotic knee prosthesis, which could enable user preferred robot behavior in the device tuning process. The framework consists of 1) a User-Controlled Interface that allows the user to select their preferred knee kinematics in gait and 2) a reinforcement learning-based algorithm for tuning high-dimension prosthesis control parameters to meet the desired knee kinematics. We evaluated the performance of the framework along with usability of the developed user interface. In addition, we used the developed framework to investigate whether amputee users can exhibit a preference between different profiles during walking and whether they can differentiate between their preferred profile and other profiles when blinded. The results showed effectiveness of our developed framework in tuning 12 robotic knee prosthesis control parameters while meeting the user-selected knee kinematics. A blinded comparative study showed that users can accurately and consistently identify their preferred prosthetic control knee profile. Further, we preliminarily examined gait biomechanics of the prosthesis users when walking with different prosthesis control and did not find clear difference between walking with preferred prosthesis control and when walking with normative gait control parameters. This study may inform future translation of this novel prosthesis tuning framework for home or clinical use.

Altering Ligand Microenvironment of Atomically Dispersed CrN4 by Axial Ligand Sulfur for Enhanced Oxygen Reduction Reaction in Alkaline and Acidic Medium.

Because of the instability and Fenton reactivity of non-precious metal nitrogen-carbon based catalyst when processing the oxygen reduction reaction (ORR), seeking for electrocatalysts with highly efficient performance becomes very highly desired to speed up the commercialization of fuel cell. Herein, chromium (Cr)-N4  electrocatalyst containing extraterrestrial S formed axial S1 -Cr1 N4  bonds (S1 Cr1 N4 C) is achieved via an assembly polymerization and confined pyrolysis strategy. Benefiting from the adjusting  coordination configuration and electronic structure of the metal center through axial coordination, S1 Cr1 N4 C exhibits enhanced the intrinsic activity (half-wave potential (E1/2 ) is 0.90 V versus reversable hydrogen electrode, RHE) compared with that of CrN4 C and Pt/C catalysts. More notably, the catalyst is almost inert in catalyzing the Fenton reaction, and thus shows the high stability. Density functional theory (DFT) results further reveal that the existence of axial S atoms in S1 Cr1 N4 C moiety has the better ORR activity than Cr1 N4 C moieties. The axial S ligand in S1 Cr1 N4 C moiety can break the electron localization around the planar Cr1 N4  active center, which facilitated the rate-limiting reductive release of OH* and accelerated overall ORR process. The present work opens up a new avenue to modulate the axial ligand type of the single-atoms (SAs) active center to enhance intrinsic SAs performances.

Hierarchical Optimization for Control of Robotic Knee Prostheses Toward Improved Symmetry of Propulsive Impulse.

Automatically personalizing complex control of robotic prostheses to improve gait performance, such as gait symmetry, is challenging. Recently, human-in-the-loop (HIL) optimization and reinforcement learning (RL) have shown promise in achieving optimized control of wearable robots for each individual user. However, HIL optimization methods lack scalability for high-dimensional space, while RL has mostly focused on optimizing robot kinematic performance. Thus, we propose a novel hierarchical framework to personalize robotic knee prosthesis control and improve overall gait performance. Specifically, in this study the framework was implemented to simultaneously design target knee kinematics and tune 12 impedance control parameters for improved symmetry of propulsive impulse in walking. In our proposed framework, HIL optimization is used to identify an optimal target knee kinematics with respect to symmetry improvement, while RL is leveraged to yield an optimal policy for tuning impedance parameters in high-dimensional space to match the kinematics target. The proposed framework was validated on human subjects, walking with robotic knee prosthesis. The results showed that our design successfully shaped the target knee kinematics as well as configured 12 impedance control parameters to improve propulsive impulse symmetry of the human users. The knee kinematics that yielded best propulsion symmetry did not preserve the normative knee kinematics profile observed in non-disabled individuals, suggesting that restoration of normative joint biomechanics in walking does not necessarily optimize the gait performance of human-prosthesis systems. This new framework for prosthesis control personalization may be extended to other wearable devices or different gait performance optimization goals in the future.

Engineering Surface Oxophilicity of Copper for Electrochemical CO2 Reduction to Ethanol.

Copper-based materials are known for converting CO2 into deep reduction products via electrochemical reduction reaction (CO2 RR). As the major multicarbon products (C2+ ), ethanol (C2 H5 OH) and ethylene (C2 H4 ) are believed to share a common oxygenic intermediate according to theoretical studies, while the key factors that bifurcate C2 H5 OH and C2 H4 pathways on Cu-based catalysts are not fully understood. Here, a surface oxophilicity regulation strategy to enhance C2 H5 OH production in CO2 RR is proposed, demonstrated by a Cu-Sn bimetallic system. Compared with bare Cu catalyst, the Cu-Sn bimetallic catalysts show improved C2 H5 OH but suppressed C2 H4 selectivity. The experimental results and theoretical calculations demonstrate that the surface oxophilicity of Cu-Sn catalysts plays an important role in steering the protonation of the key oxygenic intermediate and guides the reaction pathways to C2 H5 OH. This study provides new insights into the electrocatalyst design for enhanced production of oxygenic products from CO2 RR by engineering the surface oxophilicity of copper-based catalysts.

Human-prosthesis cooperation: combining adaptive prosthesis control with visual feedback guided gait.

BACKGROUND: Personalizing prosthesis control is often structured as human-in-the-loop optimization. However, gait performance is influenced by both human control and intelligent prosthesis control. Hence, we need to consider both human and prosthesis control, and their cooperation, to achieve desired gait patterns. In this study, we developed a novel paradigm that engages human gait control via user-fed visual feedback (FB) of stance time to cooperate with automatic prosthesis control tuning. Three initial questions were studied: (1) does user control of gait timing (via visual FB) help the prosthesis tuning algorithm to converge faster? (2) in turn, does the prosthesis control influence the user's ability to reach and maintain the target stance time defined by the feedback? and (3) does the prosthesis control parameters tuned with extended stance time on prosthesis side allow the user to maintain this potentially beneficial behavior even after feedback is removed (short- and long-term retention)? METHODS: A reinforcement learning algorithm was used to achieve prosthesis control to meet normative knee kinematics in walking. A visual FB system cued the user to control prosthesis-side stance time to facilitate the prosthesis tuning goal. Seven individuals without amputation (AB) and four individuals with transfemoral amputation (TFA) walked with a powered knee prosthesis on a treadmill. Participants completed prosthesis auto-tuning with three visual feedback conditions: no FB, self-selected stance time FB (SS FB), and increased stance time FB (Inc FB). The retention of FB effects was studied by comparing the gait performance across three different prosthesis controls, tuned with different visual FB. RESULTS: (1) Human control of gait timing reduced the tuning duration in individuals without amputation, but not for individuals with TFA. (2) The change of prosthesis control did not influence users' ability to reach and maintain the visual FB goal. (3) All participants increased their prosthesis-side stance time with the feedback and maintain it right after feedback was removed. However, in the post-test, the prosthesis control parameters tuned with visual FB only supported a few participants with longer stance time and better stance time symmetry. CONCLUSIONS: The study provides novel insights on human-prosthesis interaction when cooperating in walking, which may guide the future successful adoption of this paradigm in prosthesis control personalization or human-in-the-loop optimization to improve the prosthesis user's gait performance.

Hypoxia-related LncRNAs signature predicts prognosis and is associated with immune infiltration and progress of head and neck squamous cell carcinoma.

Background: Disclosing prognostic information is necessary to enable good treatment selection and improve patient outcomes. Previous studies suggest that hypoxia is associated with an adverse prognosis in patients with HNSCC and that long non-coding RNAs (lncRNAs) show functions in hypoxia-associated cancer biology. Nevertheless, the understanding of lncRNAs in hypoxia related HNSCC progression remains confusing. Methods: Data were downloaded from TCGA and GEO database. Bioinformatic tools including R packages GEOquery, limma, pheatmap, ggplot2, clusterProfiler, survivalROC and survcomp and LASSO cox analysis were utilized. Si-RNA transfection, CCK8 and real-time quantified PCR were used in functional study. Results: GEO data (GSE182734) revealed that lncRNA regulation may be important in hypoxia related response of HNSCC cell lines. Further analysis in TCGA data identified 314 HRLs via coexpression analysis between differentially expressed lncRNAs and hypoxia-related mRNAs. 23 HRLs were selected to build the prognosis predicting model using lasso Cox regression analyses. Our model showed excellent performance in predicting survival outcomes among patients with HNSCC in both the training and validation sets. We also found that the risk scores were related to tumor stage and to tumor immune infiltration. Moreover, LINC01116 were selected as a functional study target. The knockdown of LINC01116 significantly inhibited the proliferation of HNSCC cells and effected the hypoxia induced immune and the NF-κB/AKT signaling. Conclusions: Data analysis of large cohorts and functional experimental validation in our study suggest that hypoxia related lncRNAs play an important role in the progression of HNSCC, and its expression model can be used for prognostic prediction.

Fusion of Human Gaze and Machine Vision for Predicting Intended Locomotion Mode.

Predicting the user's intended locomotion mode is critical for wearable robot control to assist the user's seamless transitions when walking on changing terrains. Although machine vision has recently proven to be a promising tool in identifying upcoming terrains in the travel path, existing approaches are limited to environment perception rather than human intent recognition that is essential for coordinated wearable robot operation. Hence, in this study, we aim to develop a novel system that fuses the human gaze (representing user intent) and machine vision (capturing environmental information) for accurate prediction of the user's locomotion mode. The system possesses multimodal visual information and recognizes user's locomotion intent in a complex scene, where multiple terrains are present. Additionally, based on the dynamic time warping algorithm, a fusion strategy was developed to align temporal predictions from individual modalities while producing flexible decisions on the timing of locomotion mode transition for wearable robot control. System performance was validated using experimental data collected from five participants, showing high accuracy (over 96% in average) of intent recognition and reliable decision-making on locomotion transition with adjustable lead time. The promising results demonstrate the potential of fusing human gaze and machine vision for locomotion intent recognition of lower limb wearable robots.

A Universal Single-Atom Coating Strategy Based on Tannic Acid Chemistry for Multifunctional Heterogeneous Catalysis.

Here, we report a universal single-atom coating (SAC) strategy by taking advantage of the rich chemistry of tannic acid (TA). TA units not only self-assemble into a cross-linked porous polyphenolic framework, but also can grip on different substates via multiple binding modes. Benefiting from the diverse chelating ability of TA, a series of mono-, and bi-metallic SACs can be formed on substrates of different materials (e. g., carbon, SiO2 , TiO2 , MoS2 ), dimensions (0D-3D) and sizes (50 nm-5 cm). By contrast, uniform SAC cannot be achieved using common approaches such as pyrolysis of metal-dopamine complexes or metal-organic frameworks. As a proof-of-concept demonstration, two Co SACs immobilized on graphene and TiO2 were prepared. The former one shows six-fold higher mass activity than Pt/C toward oxygen reduction. The latter one displays outstanding photocatalytic activity owing to the high activity of the single atoms and the formation of the single-atom coating-TiO2 heterojunction.

Reinforcement Learning Control of Robotic Knee With Human-in-the-Loop by Flexible Policy Iteration.

We are motivated by the real challenges presented in a human-robot system to develop new designs that are efficient at data level and with performance guarantees, such as stability and optimality at system level. Existing approximate/adaptive dynamic programming (ADP) results that consider system performance theoretically are not readily providing practically useful learning control algorithms for this problem, and reinforcement learning (RL) algorithms that address the issue of data efficiency usually do not have performance guarantees for the controlled system. This study fills these important voids by introducing innovative features to the policy iteration algorithm. We introduce flexible policy iteration (FPI), which can flexibly and organically integrate experience replay and supplemental values from prior experience into the RL controller. We show system-level performances, including convergence of the approximate value function, (sub)optimality of the solution, and stability of the system. We demonstrate the effectiveness of the FPI via realistic simulations of the human-robot system. It is noted that the problem we face in this study may be difficult to address by design methods based on classical control theory as it is nearly impossible to obtain a customized mathematical model of a human-robot system either online or offline. The results we have obtained also indicate the great potential of RL control to solving realistic and challenging problems with high-dimensional control inputs.

Taking Both Sides: Seeking Symbiosis Between Intelligent Prostheses and Human Motor Control during Locomotion.

Robotic lower-limb prostheses aim to replicate the power-generating capability of biological joints during locomotion to empower individuals with lower-limb loss. However, recent clinical trials have not demonstrated clear advantages of these devices over traditional passive devices. We believe this is partly because the current designs of robotic prothesis controllers and clinical methods for fitting and training individuals to use them do not ensure good coordination between the prosthesis and user. Accordingly, we advocate for new holistic approaches in which human motor control and intelligent prosthesis control function as one system (defined as human-prosthesis symbiosis). We hope engineers and clinicians will work closely to achieve this symbiosis, thereby improving the functionality and acceptance of robotic prostheses and users' quality of life.

Residual Chlorine Induced Cationic Active Species on a Porous Copper Electrocatalyst for Highly Stable Electrochemical CO2 Reduction to C2.

Electrochemical carbon dioxide (CO2 ) reduction reaction (CO2 RR) is an attractive approach to deal with the emission of CO2 and to produce valuable fuels and chemicals in a carbon-neutral way. Many efforts have been devoted to boost the activity and selectivity of high-value multicarbon products (C2+ ) on Cu-based electrocatalysts. However, Cu-based CO2 RR electrocatalysts suffer from poor catalytic stability mainly due to the structural degradation and loss of active species under CO2 RR condition. To date, most reported Cu-based electrocatalysts present stabilities over dozens of hours, which limits the advance of Cu-based electrocatalysts for CO2 RR. Herein, a porous chlorine-doped Cu electrocatalyst exhibits high C2+ Faradaic efficiency (FE) of 53.8 % at -1.00 V versus reversible hydrogen electrode (VRHE ). Importantly, the catalyst exhibited an outstanding catalytic stability in long-term electrocatalysis over 240 h. Experimental results show that the chlorine-induced stable cationic Cu0 /Cu+ species and the well-preserved structure with abundant active sites are critical to the high FE of C2+ in the long-term run of electrochemical CO2 reduction.

Cobalt-Based Metal-Organic Frameworks and Their Derivatives for Hydrogen Evolution Reaction.

Hydrogen has been considered as a promising alternative energy to replace fossil fuels. Electrochemical water splitting, as a green and renewable method for hydrogen production, has been drawing more and more attention. In order to improve hydrogen production efficiency and lower energy consumption, efficient catalysts are required to drive the hydrogen evolution reaction (HER). Cobalt (Co)-based metal-organic frameworks (MOFs) are porous materials with tunable structure, adjustable pores and large specific surface areas, which has attracted great attention in the field of electrocatalysis. In this review, we focus on the recent progress of Co-based metal-organic frameworks and their derivatives, including their compositions, morphologies, architectures and electrochemical performances. The challenges and development prospects related to Co-based metal-organic frameworks as HER electrocatalysts are also discussed, which might provide some insight in electrochemical water splitting for future development.

Heterogeneous Single-Atom Catalysts for Electrochemical CO2 Reduction Reaction.

The electrochemical CO2 reduction reaction (CO2 RR) is of great importance to tackle the rising CO2 concentration in the atmosphere. The CO2 RR can be driven by renewable energy sources, producing precious chemicals and fuels, with the implementation of this process largely relying on the development of low-cost and efficient electrocatalysts. Recently, a range of heterogeneous and potentially low-cost single-atom catalysts (SACs) containing non-precious metals coordinated to earth-abundant elements have emerged as promising candidates for the CO2 RR. Unfortunately, the real catalytically active centers and the key factors that govern the catalytic performance of these SACs remain ambiguous. Here, this ambiguity is addressed by developing a fundamental understanding of the CO2 RR-to-CO process on SACs, as CO accounts for the major product from CO2 RR on SACs. The reaction mechanism, the rate-determining steps, and the key factors that control the activity and selectivity are analyzed from both experimental and theoretical studies. Then, the synthesis, characterization, and the CO2 RR performance of SACs are discussed. Finally, the challenges and future pathways are highlighted in the hope of guiding the design of the SACs to promote and understand the CO2 RR on SACs.

Wearer-Prosthesis Interaction for Symmetrical Gait: A Study Enabled by Reinforcement Learning Prosthesis Control.

With advances in robotic prostheses, rese-archers attempt to improve amputee's gait performance (e.g., gait symmetry) beyond restoring normative knee kinematics/kinetics. Yet, little is known about how the prosthesis mechanics/control influence wearer-prosthesis' gait performance, such as gait symmetry, stability, etc. This study aimed to investigate the influence of robotic transfemoral prosthesis mechanics on human wearers' gait symmetry. The investigation was enabled by our previously designed reinforcement learning (RL) supplementary control, which simultaneously tuned 12 control parameters that determined the prosthesis mechanics throughout a gait cycle. The RL control design facilitated safe explorations of prosthesis mechanics with the human in the loop. Subjects were recruited and walked with a robotic transfemoral prosthesis on a treadmill while the RL controller tuned the control parameters. Stance time symmetry, step length symmetry, and bilateral anteroposterior (AP) impulses were measured. The data analysis showed that changes in robotic knee mechanics led to movement variations in both lower limbs and therefore gait temporal-spatial symmetry measures. Consistent across all the subjects, inter-limb AP impulse measurements explained gait symmetry: the stance time symmetry was significantly correlated with the net inter-limb AP impulse, and the step length symmetry was significantly correlated with braking and propulsive impulse symmetry. The results suggest that it is possible to personalize transfemoral prosthesis control for improved temporal-spatial gait symmetry. However, adjusting prosthesis mechanics alone was insufficient to maximize the gait symmetry. Rather, achieving gait symmetry may require coordination between the wearer's motor control of the intact limb and adaptive control of the prosthetic joints. The results also indicated that the RL-based prosthesis tuning system was a potential tool for studying wearer-prosthesis interactions.

Encapsulation of core-satellite silicon in carbon for rational balance of the void space and capacity.

The void space is widely used in anode materials for relieving the volume expansion during lithium insertion and extraction processes. Generally, the void is randomly generated or exceeded the expansion to ensure the structural stability, which thus sacrifices the capacity and energy density. In this research, a core-satellite architecture was constructed with an elaborate structural design to obtain a rational balance of the void space and capacity. Such well fabricated silicon@porous silicon@carbon (Si@pSi@C) core-satellite nanoparticles with a precise void space present a satisfactory capacity of 1002 mA h g-1 over 100 cycles at a current of 100 mA g-1. This delicate core-satellite architecture could promote the use of the structural design in high-energy density lithium-ion batteries.

Hollow-Carbon-Templated Few-Layered V5S8 Nanosheets Enabling Ultrafast Potassium Storage and Long-Term Cycling.

Due to the abundant potassium resource on the Earth's crust, researchers now have become interested in exploring high-performance potassium-ion batteries (KIBs). However, the large size of K+ would hinder the diffusion of K ions into electrode materials, thus leading to poor energy/power density and cycling performance during the depotassiation/potassiation process. So, few-layered V5S8 nanosheets wrapping a hollow carbon sphere fabricated via a facile hollow carbon template induced method could reversibly accommodate K storage and maintain the structure stability. Hence, the as-obtained V5S8@C electrode enables rapid and reversible storage of K+ with a high specific capacity of 645 mAh/g at 50 mA/g, a high rate capability, and long cycling stability, with 360 and 190 mAh/g achieved after 500 and 1000 cycles at 500 and 2000 mA/g, respectively. The excellent electrochemical performance is superior to the most existing electrode materials. The DFT calculations reveal that V5S8 nanosheets have high electrical conductivity and low energy barriers for K+ intercalation. Furthermore, the reaction mechanism of the V5S8@C electrode in KIBs is probed via the in operando synchrotron X-ray diffraction technique, and it indicates that the V5S8@C electrode undergoes a sequential intercalation (KV5S8) and conversion reactions (K2S3) reversibly during the potassiation process.

Mesoporous WO3 Nanofibers With Crystalline Framework for High-Performance Acetone Sensing.

Semiconducting metal oxides with abundant active sites are regarded as promising candidates for environmental monitoring and breath analysis because of their excellent gas sensing performance and stability. Herein, mesoporous WO3 nanofibers with a crystalline framework and uniform pore size is successfully synthesized in an aqueous phase using an electrospinning method, with ammonium metatungstate as the tungsten sources, and SiO2 nanoparticles and polyvinylpyrrolidone as the sacrificial templates. The obtained mesoporous WO3 nanofibers exhibit a controllable pore size of 26.3-42.2 nm, specific surface area of 24.1-34.4 m2g-1, and a pore volume of 0.15-0.24 cm3g-1. This unique hierarchical structure, with uniform mesopores and interconnected channels, could facilitate the diffusion and transportation of gas molecules in the framework. Gas sensors, based on mesoporous WO3 nanofibers, exhibit an excellent performance in acetone sensing with a low limit of detection (<1 ppm), short response-recovery time (24 s/27 s), a linear relationship in a broad range, and good selectivity.

Spatially Confined Tuning the Interfacial Synergistic Catalysis in Mesochannels toward Selective Catalytic Reduction.

Low-temperature selective catalytic reduction of nitrogen oxides (NO x) with NH3 (NH3-SCR) has been identified as a promising strategy to mitigate the pollution of NO x. The fine control of synergistic effect and the suppression of aggregation of the active component, however, are still the challenge because of the weak interaction between the active component and matrix. In this work, a series of Ce-promoted Mn-based heterogeneous catalysts supported on mesoporous silica (SBA-15) with different Mn contents were prepared by two separated impregnation processes. Low-temperature NH3-SCR activity demonstrates that the Mn content in the catalyst has a great influence on the activity of the NH3-SCR reaction. The 20% MnO x-CeO x/SBA-15 catalyst exhibited the best catalytic performance in a broad temperature window. Moreover, it exhibits enhanced resistance to SO2 and H2O and long-term durability during 72 h reaction. The highly dispersive active phase, the formation of solid solution, the high ratio of Ce3+, and the spatial confinement effect largely contribute to the outstanding activity and durability of the 20% MnO x-CeO x/SBA-15 catalyst. Finally, a monolithic catalyst fabricated by the 20% MnO x-CeO x/SBA-15 catalyst powder and cordierite substrate show promising industrial application.

Gaze Fixation Comparisons Between Amputees and Able-bodied Individuals in Approaching Stairs and Level-ground Transitions: A Pilot Study.

This paper aims to investigate the visual strategy of transtibial amputees while they are approaching the transition between level-ground and stairs and compare it with that of able-bodied individuals. To this end, we conducted a pilot study where two transtibial amputee subjects and two able-bodied subjects transitioned from level-ground to stairs and vice versa while wearing eye tracking glasses to record gaze fixations. To investigate how vision functioned to both populations for preparing locomotion on new terrains, gaze fixation behavior before the new terrains were analyzed and compared between two populations across all transition cases in the study. Our results presented that, unlike the able-bodied population, amputees had most of their fixations directed on the transition region prior to new terrains. Furthermore, amputees showed an increased need for visual information during transition regions before navigation on stairs than that before navigation onto level-ground. The insights about amputees' visual behavior gained by the study may lead the future development of technologies related to the intention prediction and the locomotion recognition for amputees.