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Executing deep neural networks (DNNs) on edge artificial intelligence (AI) devices enables various autonomous mobile computing applications. However, the memory budget of edge AI devices restricts the number and complexity of DNNs allowed in such applications. Existing solutions, such as model compression or cloud offloading, reduce the memory footprint of DNN inference at the cost of decreased model accuracy or autonomy. To avoid these drawbacks, we divide DNN into blocks and swap them in and out in order, such that large DNNs can execute within a small memory budget. Nevertheless, naive swapping on edge AI devices induces significant delays due to the redundant memory operations in the DNN development ecosystem for edge AI devices. To this end, we develop SwapNet, an efficient DNN block swapping middleware for edge AI devices. We systematically eliminate the unnecessary memory operations during block swapping while retaining compatible with the deep learning frameworks, GPU backends, and hardware architectures of edge AI devices. We further showcase the utility of SwapNet via a multi-DNN scheduling scheme. Evaluations on eleven DNN inference tasks in three applications demonstrate that SwapNet achieves almost the same latency as the case with sufficient memory even when DNNs demand $2.32\times \,\sim$ 2 . 32 × ∼ $5.81\times$ 5 . 81 × memory beyond the available budget. The design of SwapNet also provides novel and feasible insights for deploying large language models (LLMs) on edge AI devices in the future.

This paper addresses a significant problem in American Sign Language (ASL) translation systems that has been overlooked. Current designs collect excessive sensing data for each word and treat every sentence as new, requiring the collection of sensing data from scratch. This approach is time-consuming, taking hours to half a day to complete the data collection process for each user. As a result, it creates an unnecessary burden on end-users and hinders the widespread adoption of ASL systems. In this study, we identify the root cause of this issue and propose GASLA–a wearable sensor-based solution that automatically generates sentence-level sensing data from word-level data. An acceleration approach is further proposed to optimize the data generation speed. Moreover, due to the gap between the generated sentence data and directly collected sentence data, a template strategy is proposed to make the generated sentences more similar to the collected sentence. The generated data can be used to train ASL systems effectively while reducing overhead costs significantly. GASLA offers several benefits over current approaches: it reduces initial setup time and future new-sentence addition overhead; it requires only two samples per sentence compared to around ten samples in current systems; and it improves overall performance significantly.

RFID shows great potentials to build useful sensing applications. However, current RFID sensing can obtain mainly a single-dimensional sensing measurement from each reader-to-tag query, such as phase, RSS, etc. This is sufficient to fulfill the designs that are bound to the tag’s movement, e.g., the localization of tags. However, it imposes inevitable uncertainty on many sensing tasks relying on the features extracted from the RFID signals. These traditional sensing measurements limit the fidelity of RFID sensing fundamentally and prevent its broader usage in more sophisticated sensing scenarios. This paper presents RF-Wise to push the limit of RFID-based sensing, motivated by an insightful observation to customize RFID signals. RF-Wise can enrich the existing single-dimensional feature measure to a channel state information (CSI)-like measure with up to 150-dimensional samples across different frequencies concurrently. More importantly, RF-Wise is a software solution atop the standard EPC Gen2 protocol without using any extra hardware. It requires only one tag for sensing and works within the ISM band. RF-Wise, so far as we know, is the first system of such a kind. Extensive experiments show that RF-Wise does not impact underlying RFID communications, while by using the features extracted by RF-Wise, applications’ sensing performance can be improved remarkably. The source codes of RF-Wise are available at https://cui-zhao.github.io/RF-WISE/.

S vacancies-rich Ni3S2@Cu2S nanotube heterojunction arrays were fabricated, which has excellent HER, OER and overall splitting performance. The outstanding performance could be attributed to defects and unique nanotube arrays.

• A PHI-based homojunction photocatalyst was fabricated via an ionothermal route. • The regulated crystallinity induced the differentiated band structure of PHI. • Interface combination and N self-doping contributed to S-scheme charge transfer. • HLPCN exhibited excellent photocatalytic performance for H 2 evolution. Fabricating homojunction photocatalyst is a promising approach to accelerate the separation and transfer of photogenerated charge carriers, and to boost photocatalytic performance. Herein, a novel poly (heptazine imide) (PHI)-based S-scheme homojunction photocatalyst (U/T-LHPHI) is fabricated through an ionothermal synthesis route, which exhibits particular high and low crystallinity property, intimate interface combination, and locally N self-doping. The regulation of crystallinity contributes to the differentiated electronic structure in PHI, which leads to the establishment of internal electric field (IEF). The intense IEF and N doping level with electron extracting capacity synergistically promote the charge transfer from the high crystalline PHI (HPHI) to the low crystalline PHI (LPHI) following the S-scheme mechanism. Additionally, the strong interfacial interaction improves the interfacial charge transfer dynamics. As a consequence, photogenerated electrons with powerful reducing ability are maintained effectively. Upon light irradiation, the optimized U/T-LHPHI performs an H 2 evolution rate of 4880, 2416, and 2375 µmol g−1 h−1 in deionized water, simulated seawater, and real seawater, respectively, which exceed that of many carefully designed noble metal Pt containing photocatalyst. This work provides an important verification that the rational design and construction of homojunction photocatalysts could effectively enhance photocatalytic activity. [Display omitted] [ABSTRACT FROM AUTHOR]

Based on a defect-guided heteroepitaxial growth strategy, a ZnIn2S4/CoIn2S4heterostructure was developed, which delivered 39.69 and 6.08-folds of photocatalytic H2evolution activity enhancement compared to that of individual CoIn2S4and ZnIn2S4, respectively.

Multi-electron reaction with V2+/V3+, V3+/V4+, and V4+/V5+process is achieved in 0.5% W-V-S by W doping strategy for modulating valence of partial V as V2+and V3+. Meanwhile, the modulated flower-like microsphere morphology as well as rich vacancies by W doping maintains the stability in multi-electron reaction. Therefore, the fabricated 0.5% W-V-S delivers superior magnesium storage performance.

In this paper, Co9S8/Ni3S2nanoflakes (NFs) with sulfur deficiencies were grown in-situon N-doped graphene nanotubes (N-GNTs). They were successfully prepared through electrodeposition followed by hydrogenation treatment, which is able to act as a self-supported electrode for asymmetric supercapacitors (ASCs). Combining the defect-rich active materials with highly conductive skeletons, the hybrid electrode N-GNTs@sd-Co9S8/Ni3S2NFs show ultrahigh specific capacity of ∼304 mA h g−1and prominent rate capability (capacity retention ratio of ∼85% even at 100 A g−1), and deliver a long cycling lifespan of ∼1.9% capacitance loss after 10000 cycles. In addition, an ASC was constructed using the as-synthesized composite electrode as the positive electrode and active carbon (AC) as the negative electrode. The fabricated device shows a high energy density of ∼45.1 Wh kg−1at ∼3.4 kW kg−1and superior cycling stability. This work substantiates a smart strategy to fabricate novel composite electrode materials for next-generation supercapacitors by incorporating riched deficiencies into nanostructures.

As an essential component, roadside units (RSUs) play an indispensable role in realizing Vehicle-to-Everything (V2X) by seamlessly connecting various intelligent devices and vehicles. To facilitate the construction of V2X, much research has been done in designing effective RSU deployment strategies. However, most of these efforts are largely limited by design utility and deployment scalability. To address the limitations of previous works, this paper proposes a general RSU deployment framework, Greta, which can evaluate candidate deployment sites from different perspectives with rich input data, and satisfy different requirements on optimization metrics. To this end, we model the general RSU deployment problem as a customized reinforcement learning (RL) problem that intelligently explores the deployment environment to find a good deployment strategy. Specifically, we design an effective data profiling network to extract features from multi-modality input data. These extracted features are gradually weighted, fused, and encoded as part of the state representation of the RL model. We further design new reward functions considering various deployment metrics and propose an action space pruning scheme to speed up model training. We implement a prototype system of Greta and extensively evaluate its performance using real-world data. The results show Greta achieves remarkable performance gains compared to recent RSU deployment methods.

Co-Ru-based compounds were successfully synthesized on nitrogen-doped two-dimensional carbon nanosheets by a one-step pyrolysis process. The obtained catalyst has excellent HER, OER, and ORR properties.

The hot deformation behavior of 40Cr/Q345B bimetal during hot compression bonding was studied using the isothermal compression method. A true stress–strain curve of the bimetal was obtained and modified to eliminate the effects of friction. The results show that the flow stress increases with decreasing deformation temperature and increasing strain rate. By analyzing the relationship of stress, deformation temperature, and strain rate, the constitutive equation of 40Cr/Q345B bimetal was obtained. The hot processing maps of 40Cr/Q345B bimetal under different strains are drawn. Through microstructure characterization, 40Cr/Q345B bimetal formed metallurgical bonding under the deformation process of this study. Combined with the hot processing map, microstructure, prior austenite grain, and microhardness distribution, it is proposed that the optimal deformation parameters of 40Cr/Q345B bimetal is 1050–1150°C and 0.02–0.4 s−1.

Scintillation-based X-ray imaging can provide convenient visual observation of absorption contrast by standard digital cameras, which is critical in a variety of science and engineering disciplines. More efficient scintillators and electronic postprocessing derived from neural networks are usually used to improve the quality of obtained images from the perspective of optical imaging and machine vision, respectively. Here, we propose to overcome the intrinsic separation of optical transmission process and electronic calculation process, integrating the imaging and postprocessing into one fused optical–electronic convolutional autoencoder network by affixing a designable optical convolutional metasurface to the scintillator. In this way, the convolutional autoencoder was directly connected to down-conversion process, and the optical information loss and training cost can be decreased simultaneously. We demonstrate that feature-specific enhancement of incoherent images is realized, which can apply to multi-class samples without additional data precollection. Hard X-ray experimental validations reveal the enhancement of textural features and regional features achieved by adjusting the optical metasurface, indicating a signal-to-noise ratio improvement of up to 11.2 dB. We anticipate that our framework will advance the fundamental understanding of X-ray imaging and prove to be useful for number recognition and bioimaging applications.

Control over polymerization thermodynamics and kinetics enables the generation of polymers with on-demand properties. This is exemplified by the ring-opening polymerization of tetraethylene glycol carbonate (4EGMC) using an alkali cation (M+)-based binary catalytic system at ambient temperature. By introducing a guanidine catalyst [(1,5,7-triazabicyclo[4.4.0]dec-5-ene), TBD], the alkali cation-assisted ring-opening polymerization of macrocyclic carbonate was ca.120–270 times faster than the reaction without an alkali cation, M+(0.16–0.36 min–1with M+vs 0.001 min–1without M+). Moreover, the interaction between 4EGMC and M+led to an increase in the ring strain, supported by both bench experiments and computational simulations. This interaction altered the driving force of polymerization from the change of entropy to enthalpy, which revealed the pivotal role of alkali cations in regulating the ring-opening polymerization of macrocyclic carbonate.

Molybdenum phosphide (MoP) has received increasing attention for the hydrogen evolution reaction (HER) due to its Pt-like electronic structure and high electrical conductivity. In this work, a flake-like Ru-doped MoP with phosphorus vacancy (Ru-MoP-PV) electrocatalyst is synthesized for the first time by a simple and rapid room-temperature microwave approach within 30 s. The created abundant phosphorus vacancies provide rich active sites and favor rapid electron transfer. The introduced Ru also enhances the catalytic activity of the synthesized electrocatalyst efficiently. Then, the designed Ru-MoP-PVpossesses low overpotentials for HER with 79, 100, and 161 mV in 1.0 M KOH, 0.5 M H2SO4, and 1.0 M phosphate-buffered saline to obtain 10 mA cm–2. The Ru-MoP-PVand NiFe-layered double hydroxide are used as the cathode and the anode, respectively, to drive water splitting and just need a low cell voltage of 1.6 V to achieve 10 mA cm–2. This work provides a feasible way for the rapid production of metal phosphides for energy conversion and storage applications.

Correlating atomic configurations—specifically, degree of disorder (DOD)—of an amorphous solid with properties is a long-standing riddle in materials science and condensed matter physics, owing to difficulties in determining precise atomic positions in 3D structures1–5. To this end, 2D systems provide insight to the puzzle by allowing straightforward imaging of all atoms6,7. Direct imaging of amorphous monolayer carbon (AMC) grown by laser-assisted depositions has resolved atomic configurations, supporting the modern crystallite view of vitreous solids over random network theory8. Nevertheless, a causal link between atomic-scale structures and macroscopic properties remains elusive. Here we report facile tuning of DOD and electrical conductivity in AMC films by varying growth temperatures. Specifically, the pyrolysis threshold temperature is the key to growing variable-range-hopping conductive AMC with medium-range order (MRO), whereas increasing the temperature by 25 °C results in AMC losing MRO and becoming electrically insulating, with an increase in sheet resistance of 109times. Beyond visualizing highly distorted nanocrystallites embedded in a continuous random network, atomic-resolution electron microscopy shows the absence/presence of MRO and temperature-dependent densities of nanocrystallites, two order parameters proposed to fully describe DOD. Numerical calculations establish the conductivity diagram as a function of these two parameters, directly linking microstructures to electrical properties. Our work represents an important step towards understanding the structure–property relationship of amorphous materials at the fundamental level and paves the way to electronic devices using 2D amorphous materials.

Appropriately modulating the contents of the pre-embedded lithium (Li) ions can induce controllable Se vacancies into the Ni3Se2products, effectively endowing a relatively high-rate and large-capacity for the cathode.

The intercalation of foreign ions has been demonstrated to be one of the effective methods to improve the electrochemical performance of Ti3C2TxMXene. However, whether different intercalated ions have diverse impacts on the MXene structure and electrochemical properties is not well understood. Herein, we comprehensively investigated the structural features and electrochemical performances of a series of ions, including Li+, Na+, K+, Cs+, Zn2+, Mg2+, SO42−, and OH−intercalated MXenes. Different ions are observed to exhibit variations in the intercalation effect because of the differences in their sizes, charge numbers, and chemical features. Among the investigated intercalation agents, CsOH composed of monovalent Cs+with a large size and strong base anion OH−exhibits a superior intercalation effect, where a large interlayer space accommodating a large amount of free water, a high oxidation state of Ti and a preferred surface with more O-containing functional groups for redox reaction is created, intensifying the pseudocapacitive H+intercalation. Therefore, CsOH-treated MXene exhibits a significant enhancement in gravimetric capacitance (i.e., approximately 725% of the original) and more than 100% capacitance retention over 20,000 cycles. This paper provides a guideline for the rational design and construction of high-capacitance MXene and MXene-based hybrid electrodes in aqueous electrolytes.

Developing multifunctional electrocatalysts toward energy-related reactions could reduce the cost and improve the utilization efficiency of raw materials. Herein, defective CoP decorated with ultrafine Pt nanoparticles (Pt/d-CoP/NPC) with multifunctional electrocatalytic performances is prepared viafacile pyrolysis and following chemical reduction process. The as-synthesized Pt/d-CoP/NPC owns high half-wave potential of 0.82 V for oxygen reduction reaction with excellent stability in 0.1 mol/L KOH. Density functional theory calculations demonstrate that the adsorption energy of *OO at Pt/d-CoP/NPC is stronger compared to Pt, yielding higher catalytic activity for ORR. Moreover, the resultant electrocatalyst possesses excellent catalytic activities with low overpotentials toward hydrogen evolution reaction (33 mV in 1 mol/L KOH, 6 mV in 0.5 mol/L H2SO4and 70 mV in 1 mol/L PBS) and oxygen evolution reaction (320 mV) at 10 mA/cm2. Water-splitting and rechargeable Zn-air batteries assembled with the as-synthesized Pt/d-CoP/NPC as electrodes exhibit outstanding activity and long-range stability. Remarkably, sustainable energies and homemade Zn-air battery can efficiently drive the Pt/d-CoP/NPC electrolyzer with sumless hydrogen bubbles generated, verifying the potential applications for renewable energy storage.

Mobile phones nowadays are equipped with at least dual microphones. We find when a user is typing on a phone, the sounds generated from the vibration caused by finger’s tapping on the screen surface can be captured by both microphones, and these recorded sounds alone are informative enough to localize the user’s keystrokes. This ability can be leveraged to enable useful application designs, while it also raises a crucial privacy risk that the private information typed by users on mobile phones has a great potential to be leaked through such a recognition ability. In this paper, we address two key design issues and demonstrate, more importantly alarm people, that this risk is possible, which could be related to many of us when we use our mobile phones. We implement our proposed techniques in a prototype system and conduct extensive experiments. The evaluation results indicate promising successful rates for more than 4000 keystrokes from different users on various types of mobile phones.

The low capacity and rate capability of the battery-type supercapacitor anode prevent its widespread application. In this paper, we construct a semicoherent heterojunction of Fe2O3/FeSe2as an advanced battery-type supercapacitor anode to overcome the bottleneck. A series of characterization and first-principles calculations confirm that the special heterointerface manipulation automatically generates a stronger inherent electric field, thereby enhancing the electron transport rate and the OH−adsorption capacity. In addition, it facilitates additional redox reactions between the active materials and OH−and makes the reaction system easier to execute. Taking advantage of these benefits, the prepared anode has a high specific capacity of 199.2 mA h g−1(1 A g−1) and retains 90.2% of its initial capacity after 5000 cycles at 105.8 mA h g−1(10 A g−1). In addition, an asymmetric supercapacitor device is fabricated with the prepared Fe2O3/FeSe2as the anode, which provides a maximum energy density of 52.55 W h kg−1at 0.8 kW kg−1and a capacity retention of 91.2% even after 15,000 cycles. In our work, a novel strategy for the optimal design of a battery-type supercapacitor anode with a large capacity and superior rate capability is conceived, significantly advancing the widespread application of transition metal compounds in energy storage systems.

• CB/Co@C nanocomposites composed of sustainable carbon black and anchored Co@C nanoparticles have been successfully synthesized. • As a novel lightweight electromagnetic wave absorber, the optimal RL min and EAB of -53.989 dB and 6.0 GHz were achieved at thin thickness. • A reasonable absorption mechanism was proposed according to various loss mechanism induced by different components. Recently, developing carbon-based hybrid materials loaded with magnetic components has been generally regarded as a promising and practically feasible strategy when it comes to constructing lightweight electromagnetic wave absorbers. In the current work, reclaimed carbon black (CB) nanopowder was firstly produced by simple burning of wheat straw, which was then employed as sustainable carbon-based host materials (carrier) and successfully decorated Co@C nanoparticles via a simple thermal reduction process. Remarkably, both the as-fabricated nanocomposites and corresponding electromagnetic wave absorption performances could be effectively tuned by tailoring the dosage of the Co@C nanoparticles. The minimum reflection loss (RL min) of –53.989 dB was achieved for CB/Co@C-2# at 2.28 mm thickness, meanwhile, CB/Co@C-3# was featured by a wide effective absorption band (EAB) of 6 GHz (6.72–12.72 GHz) at a 2.73 mm matching thickness, which covered the entire X band, suggesting that the CB/Co@C nanocomposites were an attractive candidate for electromagnetic wave absorber. According to the synergistic influence of dielectric loss and magnetic loss from CB and Co@C, respectively, as well as the properly matched impedance, a reasonable electromagnetic wave attenuation mechanism was illustrated. It is noteworthy that the preparation process of CB is a facile, recycled, and low-cost strategy for achieving nanoscale carbon-based absorbing materials, moreover, the CB/Co@C nanocomposites provide a reference for constructing lightweight dielectric-magnetic products with superb electromagnetic wave absorption performances. [ABSTRACT FROM AUTHOR]

The sulfur/copper integrated cathode design enables new and cheap Mg batteries with high-area capacity. Significant performance enhancement is achieved and the cuprous-ion defects-assisted conversion reaction pathway with fast electrode kinetics is also unambiguously proved.

The rambutan-like Mn-CoO nanosphere exhibits ultra-high HER and OER activity under both acidic and alkaline conditions and excellent antibacterial properties in vitro of biomedicine.

Rechargeable magnesium batteries are particularly advantageous for renewable energy storage systems. However, the inhomogeneous Mg electrodeposits greatly shorten their cycle life under practical conditions. Herein, the epitaxial electrocrystallization of Mg on a three-dimensional magnesiophilic host is implemented viathe synergy of a magnesiophilic interface, lattice matching, and electrostatic confinement effects. The vertically aligned nickel hydroxide nanosheet arrays grown on carbon cloth (abbreviated as “Ni(OH)2@CC”) have been delicately designed, which satisfy the essential prerequisite of a low lattice geometrical misfit with Mg (about 2.8%) to realize epitaxial electrocrystallization. Simultaneously, the ionic crystal nature of Ni(OH)2displays a periodic and hillock-like electrostatic potential field over its exposed facets, which can precisely capture and confine the reduced Mg0species onto the local electron-enriched sites at the atomic level. The Ni(OH)2@CC substrate undergoes sequential Mg-ion intercalation, underpotential deposition, and electrocrystallization processes, during which the uniform, lamellar Mg electrodeposits with a locked crystallographic orientation are formed. Under practical conditions (10 mA cm–2and 10 mAh cm–2), the Ni(OH)2@CC substrate exhibits stable Mg stripping/plating cycle performances over 600 h, 2 orders of magnitude longer than those of the pristine copper foil and carbon cloth substrates.

Particulate oxidative potential may comprise a key health-relevant parameter of particulate matter (PM) toxicity. To identify biological perturbations associated with particulate oxidative potential and examine the underlying molecular mechanisms, we recruited 54 participants from two dormitories near and far from a congested highway in Atlanta, GA. Fine particulate matter oxidative potential (“FPMOP”) levels at the dormitories were measured using dithiothreitol assay. Plasma and saliva samples were collected from participants four times for longitudinal high-resolution metabolic profiling. We conducted metabolome-wide association studies to identify metabolic signals with FPMOP. Leukotriene metabolism and galactose metabolism were top pathways associated with ≥5 FPMOP-related indicators in plasma, while vitamin E metabolism and leukotriene metabolism were found associated with most FPMOP indicators in saliva. We observed different patterns of perturbed pathways significantly associated with water-soluble and -insoluble FPMOPs, respectively. We confirmed five metabolites directly associated with FPMOP, including hypoxanthine, histidine, pyruvate, lactate/glyceraldehyde, and azelaic acid, which were implications of perturbations in acute inflammation, nucleic acid damage and repair, and energy perturbation. The unique metabolic signals were specific to FPMOP, but not PM mass, providing initial indication that FPMOP might constitute a more sensitive, health-relevant measure for elucidating etiologies related to PM2.5exposures.

When compared with pure water, hydrogen produced by seawater electrolysis has a better practical application potential. By replacing the oxygen evolution reaction (OER) and competitive chlorine evolution reaction (ClER) with the thermodynamically favorable anodic hydrazine oxidation reaction (HzOR) in alkaline seawater, energy-saving hydrogen production can be achieved. In this study, Fe/Co dual-doped Ni2P and MIL-FeCoNi heterostructures (FeCo-Ni2P@MIL-FeCoNi) arrays with simultaneous cation doping and hetero-engineering provide excellent bifunctional electrocatalytic performance for HzOR and hydrogen evolution reaction (HER) in alkaline seawater electrolyte. Overall hydrazine splitting (OHzS) in seawater is impressive, with a low cell voltage of only 400 mV required to reach 1000 mA cm−2and stable operation for 1000 h to maintain above 500 mA cm−2. As a proof-of-concept, the OHzS system can save 3.03 kW h when producing 1.0 L of H2when compared with the N2H4-free seawater system, resulting in energy-saving H2production. Density functional theory calculations show that the combination of Co-doping and the fabrication of FeCo-Ni2P and MIL-FeCoNi heterointerfaces can result in a low water dissociation barrier, optimized hydrogen adsorption free energy toward HER, and favorable adsorbed dehydrogenation kinetics for HzOR. This processing route paves the way for a practical approach to the efficient utilization of hydrogen, which is abundant in the ocean energy field, to achieve a carbon-neutral hydrogen economy.

In the omics era, saliva, a filtrate of blood, may serve as an alternative, noninvasive biospecimen to blood, although its use for specific metabolomic applications has not been fully evaluated. We demonstrated that the saliva metabolome may provide sensitive measures of traffic-related air pollution (TRAP) and associated biological responses via high-resolution, longitudinal metabolomics profiling. We collected 167 pairs of saliva and plasma samples from a cohort of 53 college student participants and measured corresponding indoor and outdoor concentrations of six air pollutants for the dormitories where the students lived. Grand correlation between common metabolic features in saliva and plasma was moderate to high, indicating a relatively consistent association between saliva and blood metabolites across subjects. Although saliva was less associated with TRAP compared to plasma, 25 biological pathways associated with TRAP were detected via saliva and accounted for 69% of those detected via plasma. Given the slightly higher feature reproducibility found in saliva, these findings provide some indication that the saliva metabolome offers a sensitive and practical alternative to blood for characterizing individual biological responses to environmental exposures.

Oxygen-vacancy-rich SiC@MoO3nanocomposite with strong reflection loss (− 50.49 dB at 1.27 mm thickness) and broadband absorption band (8.72 GHz at 2.68 mm thickness) were constructed via in situ etching strategy.The presence of oxygen vacancy leads to an increased conductive loss and defect-induced dipole polarization, which plays significant role in attenuating the incident electromagnetic wave.

Graphical abstract:

MoS2is a promising electrocatalyst because of its natural abundance and outstanding electrochemical stability. However, the poor conductivity and low activity limit its catalytic performance; furthermore, MoS2is unable to satisfy the requirements of most industrial applications. In this study, to obtain a P-doped MoS2catalyst with S vacancy defects, P is inserted into the MoS2matrix viaa solid phase ion exchange at room temperature. The optimal P-doping amount is 11.4 wt%, and the resultant catalyst delivers excellent electrocatalytic properties for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) with the corresponding overpotentials of 93 and 316 mV at 10 mA cm−2in an alkaline solution; these values surpass the overpotentials of most previously reported MoS2-based materials. Theoretical calculations and results demonstrate that the synergistic effect of the doped P, which forms active centers in the basal plane of MoS2, and S vacancy defects caused by P doping intensifies the intrinsic electronic conductivity and electrocatalytic activity of the catalyst. Density functional theory calculations demonstrate that P optimizes the free energy of the MoS2matrix for hydrogen adsorption, thereby considerably increasing the intrinsic activity of the doped catalyst for the HER compared with that observed from pristine MoS2. The enhanced catalytic activity of P-doped MoS2for the OER is attributed to the ability of the doped P which facilitates the adsorption of hydroxyl and hydroperoxy intermediates and reduces the reaction energy barrier. This study provides a new environmentally friendly and convenient solid-phase ion exchange method to improve the electrocatalytic capability of two-dimensional transition-metal dichalcogenides in large-scale applications.