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Rechargeable Li-O2 batteries have captured increasing attention owing to their ultra-high theoretical specific energy. However, this promising system is confronted with the large overpotential, limited discharge capacity and low cyclic life. Herein, three two-dimensional (2D) molybdenum-based compounds of MoN, MoO3 and MoS2 are used as cathode catalysts in Li-O2 batteries. The catalytic performance and electronic structures of these catalysts are compared comprehensively. Electrochemical test results reveal the superior battery performance of MoN cathodes, which deliver the highest specific discharge capacity of approximately 7400 mAh g−1 and the lowest discharge/charge overpotential of 0.19/0.72 V. Density functional theory (DFT) calculations demonstrate the metallic property of MoN whereas MoO3 and MoS2 are poor conductive. Besides, interface properties between MoN and Li2O2 products as well as reaction pathways of the Li-O2 battery with MoN cathode are also investigated detailedly by DFT calculations, explaining the excellent catalytic properties of MoN at the atomic level. The present work provides intrinsic insights into designing high-performance cathode catalysts for Li-O2 batteries with fine-tuned morphology and electronic characteristics.

Conductive metal-organic frameworks (MOFs) have a wide range of applications in supercapacitors, electrocatalysts, and fuel cells, while gas-driven conductive MOFs have not yet been synthesized so far. Herein, we report a gas-driven conductive MOF (A) constructed from calix[4]resorcinarene macrocycle and Co(II) cations, which shows the conductivity enhancement by about eight orders of magnitude through NO2 adsorption. The conductivities of MOF A before and after the adsorption of NO2 were calculated to be about 1.3 × 10-11 and 8.4 × 10-4 S/cm, respectively. MOF A realizes the conversion from an insulator to a conductor by adsorbing NO2. When NO2 is evacuated, MOF A quickly changes from a conductor back to an insulator in 42 s. In the crystal structure of NO2-adsorbed MOF (termed as A-NO2), NO2 molecule connects Co(II) and uncoordinated carboxylate groups through hydrogen-bonding interactions to form a conductive pathway, greatly reducing the electron transmission distance between each two metal clusters. In addition, NO2 molecule and H3O+ may also form a conductive pathway by hydrogen-bonding interactions. This work presents an interesting macrocycle-based MOF with a NO2-driven on/off conductivity switch, proving the possibility for designing advanced gas-driven conductive systems.

A physics-based compact model of reliability degradation in analog resistive random access memory (RRAM) is developed. The model captures the stochastic degradation behaviors of retention, bit yield, and endurance during analog resistive switching. The model is verified with statistical data measured from analog RRAM arrays. Based on this compact model, a device-to-system simulation framework for the computation-in-memory (CIM) system is developed. This simulation framework is a silicon-verified versatile simulator that supports both inference and training, and fully considers the device nonideal effects and circuit constraints. Based on the reliability evaluation results, optimization guidelines to suppress the impact of device reliability degradation are proposed. This work provides a useful device–system codesign tool for developing large-scale CIM systems with high performance.

One sub-MAGIC population was genotyped using SLAF-seq, and QTLs and candidate genes for agronomic traits were identified in Upland cotton. The agronomic traits of Upland cotton have serious impacts on cotton production, as well as economic benefits. To discover the genetic basis of important agronomic traits in Upland cotton, a subset MAGIC (multi-parent advanced generation inter-cross) population containing 372 lines (SMLs) was selected from an 8-way MAGIC population with 960 lines. The 372 lines and 8 parents were phenotyped in six environments and deeply genotyped by SLAF-seq with 60,495 polymorphic SNPs. The genetic diversity indexes of all SNPs were 0.324 and 0.362 for the parents and MAGIC lines, respectively. The LD decay distance of the SMLs was 600 kb (r2 = 0.1). Genome-wide association mapping was performed using 60,495 SNPs and the phenotypic data of the SMLs, and 177 SNPs were identified to be significantly associated with 9 stable agronomic traits in multiple environments. The identified SNPs were divided into 117 QTLs (quantitative trait loci) by LD decay distance, explaining 5.44% to 31.64% of the phenotypic variation. Among the 117 QTLs, 3 QTLs were stable in multiple environments, and 11 QTL regions were proven to have pleiotropism associated with multiple traits. Within QTL regions, 154 genes were preferentially expressed in correlated tissues, and 8 genes with known functions were identified as priori candidate genes. Two genes, GhACT1 and GhGASL3, reported to have clear functions, were, respectively, located in qFE-A05-4 and qFE-D04-3, two stable QTLs for FE. This study revealed the genetic basis of important agronomic traits of Upland cotton, and the results will facilitate molecular breeding in cotton.

Hydroliquefaction behavior of preasphaltenes, derived from direct coal liquefaction, was carried out in a 30 mL autoclave with FeS + S catalyst and tetralin at initial hydrogen of 5.0 MPa, residence time of 0–60 min and reaction temperature of 380–440°C in order to optimize the conditions of direct coal liquefaction and improve oil yield. The products distribution and kinetic parameters of preasphaltenes catalytic hydroliquefaction were investigated. A new kinetic model was established to simulate the preasphalteneshydroliquefaction catalyzed by FeS + S catalyst using lump kinetic model. It was found that preasphaltenes were hydroliquefaction into asphaltenes and char directly, and then asphaltenes were hydrocracked into oil + gas products. Regressive reactions of preasphaltenes to char and asphaltenes to preasphaltenes occurred at higher temperatures. Higher temperature and longer time were favorable for increasing the conversion of preasphaltenes and the oil + gas yield. The hydroliquefaction of preasphaltenes under 440°C and 60 min reached 79.45% with 34.7% of oil + gas yield. The hydroliquefaction conversions calculated from the model agreed well with the experimental data, and the activation energies ranged within 50–245 kJ/mol.

On-site protein analysis is crucial for disease diagnosis in community and family medicine in which microfluidic paper-based analytical devices (μPADs) have attracted growing attention. However, the practical applications of μPADs in protein analysis for physiological samples with high complexity is still limited. Herein, we developed a three-dimensional (3D) paper-based isoelectric focusing (IEF) platform, which is composed of power supply, reservoirs, and separation channel and made by the origami and stacking method, to simultaneously separate and enrich proteins in both low-salt and high-salt samples. Under the optimized experimental conditions, standard proteins (bovine hemoglobin (BHb) and phycocyanin (Phy)) were separated within 18 min under a 36 V power supply and obtained a 10-fold enrichment using the 3D paper-based IEF platform. Then, the capability of the 3D paper-based IEF platform for direct pretreatment of high-salt samples using a 12 V battery as power supply was measured through separating three standard proteins in saline (0.9% NaCl) with separation resolution (SR) > 1.29. Through further coupling with colorimetric and lateral flow strip measurements, the 3D paper-based IEF platform was applied to directly pretreat and quantitatively analyze microalbuminuria and C-reactive proteins in clinical urine and serum samples with analytical results with relative deviations of

Low stability of photoanodes in electrolytes, especially in alkaline electrolytes, greatly limits their practical applications. Therefore, it is highly meaningful to develop a strategy to stabilize photoanodes under strongly alkaline conditions. Herein, a metal-free poly(p-phenylene pyromellitimide) film is coated onto a BiVO4 photoanode as a bifunctional catalyst layer and protective layer by in situ thermal polymerization. Structural characterization shows that the polymer film can effectively protect the BiVO4 semiconductor. Photoelectrochemical studies verify that the polymer film can improve the efficiency of the surface-reaching hole reaction and promote the separation of surface carriers. Thus, the polymer-coated photoanode shows a superior photoelectrochemical activity, which is 2.5 times higher than that of the pristine photoanode. Meanwhile, the polymer-coated photoanode also exhibits excellent stability in neutral and alkaline electrolytes. The photocurrent remains above 70% even after a six-hour reaction in a strongly alkaline electrolyte. This work provides a simple solution to stabilize semiconductor photoanodes under alkaline conditions for efficient photoelectrochemical applications.

BackgroundTartary buckwheat (Fagopyrum tataricum) is a nutritionally balanced and flavonoid-rich crop plant that has been in cultivation for 4000 years and is now grown globally. Despite its nutraceutical and agricultural value, the characterization of its genetics and its domestication history is limited.ResultsHere, we report a comprehensive database of Tartary buckwheat genomic variation based on whole-genome resequencing of 510 germplasms. Our analysis suggests that two independent domestication events occurred in southwestern and northern China, resulting in diverse characteristics of modern Tartary buckwheat varieties. Genome-wide association studies for important agricultural traits identify several candidate genes, includingFtUFGT3andFtAP2YT1that significantly correlate with flavonoid accumulation and grain weight, respectively.ConclusionsWe describe the domestication history of Tartary buckwheat and provide a detailed resource of genomic variation to allow for genomic-assisted breeding in the improvement of elite cultivars.

In recent years, two-dimensional (2D) lead-free double perovskites have been attracting much attention because of their unique performance in photovoltaic solar cells and photocatalysis. Nonetheless, how thickness affects the photoelectric properties of lead-free double perovskite remains unclear. In this work, by means of density functional theory (DFT) with a spin orbit coupling (SOC) effect, we have investigated the electronic and optical properties systemically, including band structures, carrier mobility, optical absorption spectra, exciton-binding energies, band edges alignment and molecule adsorption performance of Cs2AgBiBr6 with different thicknesses. The calculated results revealed the thickness-induced band gap and optical performance for Cs2AgBiBr6. It shows a low band gap and outstanding optical absorption of visible and ultraviolet light. When the thickness is reduced to a monolayer, Cs2AgBiBr6 moves from an indirect band gap to a direct band gap. Moreover, the carrier mobility of Cs2AgBiBr6 is excellent and the exciton-binding energy increases with the decreased thickness. Importantly, an analysis of molecule adsorption and band edge alignment indicates that Cs2AgBiBr6 is prone to H2O adsorption and H2 desorption theoretically, which is conducive to the photocatalytic water splitting for hydrogen generation and other photovatalytic reactions. Our work suggests that Cs2AgBiBr6 is a potential candidate as a solar cell or a photocatalyst, and we provide theoretical explorations into reducing the layers of lead-free double perovskite materials to 2D atomic thickness for a better photocatalytic application, which can serve as guidelines for the design of excellent photocatalysts.

CO2 conversion has attracted widespread attention because CO2 is a major issue in global warming. In this work, a hybrid metal–organic framework (MOF) film was successfully prepared by embedding PC61BM ([6,6]-phenyl C61 butyric acid methyl ester) into a CuTCPP (TCPP: meso-tetra(4-carboxyphenyl)porphine) film through a solid conversion process. The as-prepared PC61BM/CuTCPP film exhibits a three-dimensional architecture composed of two-dimensional MOF nanosheets, having not only sufficient paths for mass transfer but also active sites exposed directly to substrates. The charge migration and separation in the heterojunction between PC61BM and CuTCPP under light irradiation can dramatically improve the CO2 conversion performance of the hybrid film. The CO2 conversion proceeds rapidly even at room temperature and 1 atm with the PC61BM@CuTCPP film as the catalyst, representing one of the best photocatalysis efficacies so far among MOF-based catalysts, with the conversion up to 92.4% and a turn-over-frequency of 36.0 h−1. This work provides an insight into designing high-performance MOF-based catalysts for CO2 conversion.

Soft and wearable electronics have transformed healthcare monitoring, leading to the public awareness of physical fitness and unprecedented prosperity of personalized health management by unlocking insightful healthcare information to end-users in real-time and at anywhere. Thus, it has been greatly encouraging people to leave the locker room to sweat, and monitor their health for a continual period at exactly the same time. However, longstanding limitations on temperature stability, hydrated stability, and mechanical stability have limited the application of these electronic devices. Luckily, a new generation of technologies is coming online that is bringing soft electronics to mainstream applications. This review highlights innovations in materials and structure design that have begun to enable the function of soft electronic devices in conditions of varying temperature, humidity, and mechanical deformations, even in extreme conditions, and discusses ongoing challenges and opportunities for further developing soft and wearable electronics for health monitoring in varying environment.

Power dissipation is a fundamental issue for future chip-based electronics. As promising channel materials, two-dimensional semiconductors show excellent capabilities of scaling dimensions and reducing off-state currents. However, field-effect transistors based on two-dimensional materials are still confronted with the fundamental thermionic limitation of the subthreshold swing of 60 mV decade−1 at room temperature. Here, we present an atomic threshold-switching field-effect transistor constructed by integrating a metal filamentary threshold switch with a two-dimensional MoS2 channel, and obtain abrupt steepness in the turn-on characteristics and 4.5 mV decade−1 subthreshold swing (over five decades). This is achieved by using the negative differential resistance effect from the threshold switch to induce an internal voltage amplification across the MoS2 channel. Notably, in such devices, the simultaneous achievement of efficient electrostatics, very small sub-thermionic subthreshold swings, and ultralow leakage currents, would be highly desirable for next-generation energy-efficient integrated circuits and ultralow-power applications., Here, the authors demonstrate an atomic threshold-switching field-effect transistor constructed by integrating a metal filamentary switch with a two-dimensional MoS2 channel, and obtain abrupt steepness in the turn-on characteristics and 4.5 mV/dec subthreshold swing over five decades.

Nondestructive testing for natural microcracks is a critical challenge in assessing the surface and subsurface integrity of material. This paper proposes a shuttle-shaped sensing model with wide open inspection based on eddy current pulsed thermography (ECPT) system for natural microcrack detection on the specimens with complex geometry. To decrease the noise interference caused by uneven heating, the proposed model induces a unidirectional and uniform electromagnetic field in the region of interest. It significantly enhances thermal contrast and signal-to-noise ratio between non-defective and defective areas as well as improving the detectability and adaptability to different subjects. Besides, the direction of the infrared camera with respect to the specimen is set parallel to the specimen, which benefits the collection of the thermal signal. Experiments for several conductive cracks are implemented to verify the detectability of the proposed model.

The hybrid lithium oxygen batteries (LOBs) have been limited by the sluggish electrochemical catalytic performance towards both oxygen reduction (ORR) and oxygen evolution reaction (OER). Previous research has utilizing the light illumination to promote the charge process in non-aqueous electrolyte. However, the organic electrolyte has been blamed for the poor electrochemical stability and volatilization during illumination. For the first time, photo-enhanced aqueous LOBs have been promoted, where the reaction mechanism of OER is familiar with photo electrochemical (PEC) water-oxidation. The α-Fe2O3 nanorods and BiVO4 nanoplates are synthesized by the hydrothermal method combined with heat treatment, showing good photo-electrocatalytic property. Herein, the α-Fe2O3 electrode exhibits a superior longtime stability than the BiVO4 nanoplates, which suffer from the severe photo-corrosion. The photo-assisted hybrid Li–O2 battery based on α-Fe2O3 electrode is realized with a discharge potential of 2.56 ​V. Compared with the traditional hybrid LOBs, the charge potential is reduced from 3.96 ​V to 3.15 ​V. This work indicates that most n-type semiconductors used in PEC water-oxidation can have positive effect on the charge process in hybrid LOBs.

Bio-organic–chemical fertilizer (BCF) has great potential to enhance agricultural production, protect environment, and improve sustainability. However, current BCFs are used only in a limited scope mainly due to the low activity of beneficial bacteria. It is significant to develop new BCFs with high beneficial bacteria activity for sustainable agricultural production. In this study, a novel slow-release bio-organic–chemical fertilizer (SBCF) was prepared from activated lignite, bacillus AMCC100153 (B153) (beneficial bacteria for tomato), and slow-release fertilizer (CSF) with suitable pH and low dissolubility salt content (to protect the bacterial activity). The pH and EC of different types of SBCFs with different compositions were determined and compared with those of BCFs derived from common chemical fertilizers (BCCF). The B153 activities were measured and compared with the optimum formula of SBCF. The bacillus colonization rules of SBCF and BCCF in tomato pot soil were explored by the Real-time qPCR. SBCF had higher bacillus activity than the corresponding BCCF. Pot experiments also showed that the bacillus formed colonization rapidly on tomato roots and secreted substances to promote root growth. The HPLC analysis found that the promoting substances were auxin and zeatin. Compared with no fertilizer control (CK) and the BCCF treatments, the SBCF treatment increased tomato yields by 73.08% and 29.04%, respectively. Findings of this work suggest that SBCF with high biological activity and growth promoting effect has great potential in agriculture production system in the future.

Several studies have documented the multifaceted impacts of climate change and variability on agricultural and environmental sustainability, and social and economic development. Climate change and variability contribute to increased warmer conditions, increased frequency of heavy rain that accounts for an increasing proportion of total rainfall, extreme weather characterized by spatially variable cycles of drought and wetness, increased frequency of tropical storms/hurricanes, increased frequency of storm surges, and accelerated rate of sea-level rise (SLR). As SLR continues, it is expected that salinity due to saltwater intrusion (SWI) will impact soil health and agricultural production. As such, the significant threats of salinity necessitate more work to be done to better understand its impact on soil health and associated functional ecosystem processes. This is of even greater importance in areas such as South Florida where the surface and groundwater resources are hydrologically connected due to the shallow and highly permeable limestone soils. A better understanding of the impacts of salinity due to SWI on soil health is critical to design effective mitigation strategies. Healthy soil has multifaceted benefits to enhance agricultural productivity, i.e. regulates the flow of water; serves as a source and sink of nutrients; minimizes greenhouse gas emissions and provides optimal biological and chemical conditions for the transformation of nutrients into plant-available forms. Improved understanding of the processes and impacts of SWI on soil health will assist in guiding management decisions and policies to mitigate the impacts of SWI and salinity on agricultural soils. This review paper provides a comprehensive overview of the impacts of SWI and soil salinity on agricultural soil health and water quality. HIGHLIGHTS Climate change poses a serious threat to agricultural land use and soil health.; Soil salinity affects soil–water–plant relationships.; Soil amendments (e.g., biochar, hydrogel, organic mulch, and gypsum) can be used to improve soil health.; Climate change impacts are multifaceted and integrated mitigation strategies should be adopted.; Salt water intrusion could result in increased nutrient solubility and transformation, which could lead to increased nutrient loading to freshwater resources.

Electromagnetic Acoustic Transducer (EMAT) has become one of the fastest-growing solutions for pipeline weld inspection over the past decade due to its non-contact advantage. One primary problem of EMAT is that it has relatively lower energy transition efficiency compared to widely used piezoelectric transducers, coupled with the effect of lift-off and the non-uniformity issue of welding material, the Signal-to-Noise Ratio (SNR) can be significantly restricted. This brings great difficulty in interpreting the EMAT signal measured from pipeline girth welds. To overcome this challenge, this paper presents a deep learning-based ultrasonic pattern recognition method to identify the pipeline girth weld cracking automatically. The proposed method utilizes a deep Convolution Neural Network (CNN) integrated with a pre-trained Support Vector Machine (SVM) classifier to extract the high-level features from the time-frequency representation of A-scan signals measured by bulk-wave EMAT and classify these signals into defective or non-defective groups. To validate the proposed method, a set of experiments is carried out to classify A-scan signals measured from the girth welds of an ex-service type 813-X70 gas pipeline. A comparative investigation is also undertaken to demonstrate the superiority of the proposed method against the conventional ultrasonic pattern recognition methods for evaluation.

Thermography is one of advanced non-destructive test and evaluation for imaging defects. This paper proposes pulsed air-flow thermography for sample surface crack detection and evaluation. The proposed approach combines the advantages of both convection heat transfer of air-flow and solid heat conduction. By controlling the pulse width, the heat waves of different frequencies can be modulated to penetrate materials with different thermal conductivity. And the cleaning degree of specimen surface can be improved by high-speed air-flow convection. The theoretical model and experimental facilities of air-flow thermography are presented. Meanwhile, the offline detection of rail surface defects and the dynamic test of the defects on the outer cylindrical surface of the turn-plate are completed. The offline experiments are conducted to identify the characteristics of the proposed method for the detection of artificial and natural cracks. And the dynamic experimental results show that the defects on the outer cylindrical surface of the turn-plate can be identified when the linear velocity at the edge of the turn-plate is 1.356km/h and 6.782km/h. The results demonstrate the proposed method on testing and evaluation for rail surface cracks is effective at the low speed.

Realizing the reduction of N2 to NH3 at low temperature and pressure is always the unremitting pursuit of scientists and then electrochemical nitrogen reduction reaction offers an intriguing alternative. Here, we develop a feasible way, gamma irradiation, for constructing defective structure on the surface of WO3 nanosheets, which is clearly observed at the atomic scale by high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). The abundant oxygen vacancies ensure WO3 nanosheets with a Faradaic efficiency of 23% at −0.3 V vs. RHE. Moreover, we start from the regulation of the surface state to suppress proton availability towards hydrogen evolution reaction (HER) on the active site and thus boost the selectivity of nitrogen reduction.

A memristor1 has been proposed as an artificial synapse for emerging neuromorphic computing applications2,3. To train a neural network in memristor arrays, changes in weight values in the form of device conductance should be distinct and uniform3. An electrochemical metallization (ECM) memory4,5, typically based on silicon (Si), has demonstrated a good analogue switching capability6,7 owing to the high mobility of metal ions in the Si switching medium8. However, the large stochasticity of the ion movement results in switching variability. Here we demonstrate a Si memristor with alloyed conduction channels that shows a stable and controllable device operation, which enables the large-scale implementation of crossbar arrays. The conduction channel is formed by conventional silver (Ag) as a primary mobile metal alloyed with silicidable copper (Cu) that stabilizes switching. In an optimal alloying ratio, Cu effectively regulates the Ag movement, which contributes to a substantial improvement in the spatial/temporal switching uniformity, a stable data retention over a large conductance range and a substantially enhanced programmed symmetry in analogue conductance states. This alloyed memristor allows the fabrication of large-scale crossbar arrays that feature a high device yield and accurate analogue programming capability. Thus, our discovery of an alloyed memristor is a key step paving the way beyond von Neumann computing.

Resistive random access memory (RRAM) has been extensively studied as a promising candidate for neuromorphic computing. So far, high-precision multibit programing of RRAM for neuromorphic systems is done cell-by-cell, which can be very time-consuming. This brief demonstrates a row-by-row parallel program-verify scheme on a fabricated 160-Kb RRAM array using the incremental gate voltage programing (IGVP) method. Statistical analysis indicates that the optimal conductance tuning step size can accelerate the programing process and improve the success rate. Also, for the first time, the fundamental relations between programing success rate, critical path, and parallel efficiency for parallel program-verify methodology on the RRAM array are systematically studied. Moreover, a software-comparable recognition accuracy with only

The parallelism and analog computing features of neuromorphic systems bring great challenges in developing a compact model of analog resistive random access memory (RRAM). In this article, we develop a physics-based compact model for analog RRAM devices and crossbar array. Nonideal effects of analog RRAM device, such as variability, ${I}$ – ${V}$ nonlinearity, programming nonlinearity and asymmetry, and tuning voltage sensitivity, are modeled and verified with the statistical data measured from RRAM array. Modeling of parallel-vector-matrix-multiplication and weight update process on RRAM crossbars with interconnect resistance enables fast and accurate estimation of the training accuracy. Benchmarks of neural networks under different hardware conditions validate the functionality of the proposed model. This model can provide valuable design guidelines for a practical neuromorphic system with high performance and computing accuracy.

Binarized neural network (BNN) enables resistive switching random access memory (RRAM) with high nonlinearity and nonsymmetry to realize online training, using an RRAM & comparator structure. In this work, a new hardware implementation approach is proposed to improve the efficiency of BNN. In the approach, an 1T1R array-based propagation module is introduced and designed to realize the computing acceleration of fully parallel vector–matrix multiplication (VMM) in both forward and backward propagations. Using the 1T1R-based propagation module, high computing efficiency is achieved in both training and inference tasks, improving by $50\times $ and $177\times $ , respectively. To solve the computation error caused by device variation, a novel operation scheme with low gate voltage is proposed. With the operation scheme, the RRAM variation is dramatically suppressed by 74.8% for cycle-to-cycle and 59.9% for device-to-device. It enables high-accuracy VMM calculation and, therefore, achieves 94.7% accuracy with a typical BNN, showing only 0.7% degradation from the ideal variation-free case.

Design of non-noble metal-based nanocatalysts supported on N-doped porous carbon is very important for electrocatalytic applications. Herein, we propose a new transition metal nitrides (TMNs) catalyst through an in-situ synthesis, in which WN and Ni nanoparticles (NPs) are uniformly anchored in N-doped ordered porous carbon (WN–Ni/NPC). N-doped porous carbon with high surface area favors electrolyte infiltration and reactants diffusion, and its three-dimensional (3D) conductive network offers fast electron transport. Moreover, doping of N element together with uniformly distributed NPs further enhance the catalytic activity towards oxygen reduction reaction (ORR). Benefiting from the above superiorities and synergistic effect between the WN and Ni NPs, the WN–Ni/NPC shows good catalytic performance for ORR in alkaline media. The present synthetic method is highly valuable for designing N-doped porous carbon supported TMNs-based catalysts.

Biochar functionalized with electroactive components is gaining increasing attention owing to its versatile redox roles and tuneable structural configurations. In this review, we summarise and highlight the electrochemical properties of biochar with various theoretical, methodological, and experimental approaches, and offer new perspectives on electrochemical carbocatalysis of biochar to guide future environmental applications. Electrochemical carbocatalysis is for the first time correlated with the synergistic effects among reactive-active moieties, metal contents, defective sites, heteroatom doping, and conductive graphitic surfaces within a manoeuvrable biochar framework for environmental interactions involving biochar. It is worth noting that milder redox reactions including the formation of surface-confined reactive complexes, singlet oxygenation, and direct electron transfer can be properly introduced with specific protocols, thus minimizing undesirable carbon oxidation and enhancing reaction sustainability. Overall, this review presents future research directions on the mechanistic aspects of electroactive components on biochar to facilitate its applications in sustainable carbocatalysis and green chemistry.

A pair of tri-band multiple-input-multiple-output (MIMO) antennas with high isolation is investigated in this paper. The proposed antenna consists of two monopole antenna elements with an edge to edge spacing of 4 mm ( $0.03~\lambda _{0}$ at 2.3 GHz). The monopole antenna element chose the bending line structure that can operate in tri-band and realize miniaturization. To achieve compact dimension and high isolation, symmetrical distribution layout is adopted to decouple the low frequency band, the U-shaped neutralization line (NL) contacting with two microstrip lines, and it can to improve the isolation in high frequency band, and the inverted U-shaped NL contacting with two radiation patch can decoupling in the middle frequency band. And then study the envelope correlation coefficient is lower, and the radiation pattern in operation bands is quasi-omnidirectional. It indicates that the antenna has obtained a satisfactory diversity performance within the whole operation bands which can be a good candidate for some portable MIMO applications.

Physically unclonable function (PUF) and true random number generator (TRNG) are critical primitives to provide lightweight hardware protection. As area is tightly restricted in IoT applications, merging PUF and TRNG is a novel trend to achieve higher area efficiency. In this work, a novel tri-functional module is proposed and experimental demonstrated using RRAM for the first time. A two-phase forming process is designed to generate and store PUF ID utilizing the impact of different forming conditions on the switching window. As PUF ID is stored by the switching window, instead of a fixed resistance, PUF cells can be written to low resistance state and high resistance state as usual, and can be used as memory and TRNG. The inter-Hamming distance of the generated PUF IDs approaches 0.5, and with the majority voting readout strategy, low BER can be achieved in a wide range of temperatures from -40°C to 125°C. TRNG produces the true random numbers based on the parity of the number of pulses consumed in a write-zero process. The generated random numbers are uniform and uncorrelated after XORed, and the statistical randomness is verified by NIST SP800-22 tests.

Although good performance has been reported in shallow neural networks, the application of memristor synapses towards realistic deep neural networks has met more stringent requirements on the synapse properties, particularly the high precision and linearity of the synaptic analog weight tuning. In this study, a LiAlOX memristor synapse was fabricated and optimized to address these demands. By delicately tuning the initial conductance states, 120-level continuously adjustable conductance states were obtained and the nonlinearity factor was substantially reduced from 8.96 to 0.83. The significant enhancements were attributed to the reduced Schottky barrier height (SBH) between the filament tip and the electrode, which was estimated from the measured I-V curves. Furthermore, a deep neural network for realistic action recognition task was constructed, and the recognition accuracy was found to be increased from 15.1% to 91.4% on the Weizmann video dataset by adopting the above-described device optimization method.

Urbanization and industrialization significantly impact water quality, and detecting the specific factors which influence water quality change would greatly improve urban water environment management. In this study, an improved entropy-weighted matter-element method is used to assess the variations of water quality in two regions with different levels of urbanization in the Yangtze River Delta. Redundancy analysis was used to detect the effects of different industries on water quality. Results show that (1) an improved entropy weight-based matter-element method measures weights of pollutants and water quality levels more reliably and accurately; (2) the improvement rate of water quality in highly urbanized regions is 42.9% during 2005-2014 which is 17.2% higher than that in regions with low urbanization; (3) a decreasing concentration of total phosphorus is the main reason for changes of water quality in both regions, with decreasing concentrations of permanganate index and ammonium nitrogen having a strong influence on changes of water quality in the highly urbanized regions; (4) the decreasing proportion of fishery and heavy industries and the increasing proportion of the tertiary industries significantly influence water quality in highly urbanized regions while the decreasing proportion of animal husbandry is the most important factor influencing the changes of water quality in lowly urbanized regions.

Biochar, a low-cost porous carbonaceous adsorbent, has low adsorption capacity for anion contaminants. The objective of this study was to improve biochar's ability to adsorb phosphorus (P) through polyethyleneimine (PEI) modification to form an amine-functionalized biochar. Biochars prepared by pyrolysis of bamboo biomass, before and after PEI modification, were characterized using the Fourier transformed infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM), elemental analysis, and batch sorption experiments. The effects of pH, coexisting anions, and ionic strength on P adsorption by PEI-modified biochar were also investigated. Results indicated that PEI was successfully grafted onto biochar which resulted an increase in surface amine group and in P adsorption. The peak of P adsorption occurred at pH of three and adsorption of P was decreased with increasing of ionic strength and when coexisting ions, such as HCO3-, SO42-, NO3-, and Cl-, were coexisted. The electrostatic interaction between P and surface functional groups of PEI-modified biochar served as the primary mechanism controlling the adsorption process. These results indicate that chemically functionalized biochar with amine groups can enhance P adsorption.

Per- and polyfluoroalkyl substances (PFASs) are commonly used in many consumer and industrial products. However, their resulting widespread release into aqueous environments and their potential tox...

Crops grow poorly in saline-sodic soils, and the productivity of these soils can be dramatically improved with proper amendments. Current research mainly focuses on either organic or inorganic soil amendments, whereas few studies address options of combining organic and inorganic amendments. The objective of this study was to develop new organic and inorganic soil amendments which can lower the soil pH, replace sodium, and improve soil structure. Polyhalite (PL), microporous potassium-silicon-calcium mineral fertilizer (MF), furfural residue (FR), and fulvic acid (FA) were mixed with four different ratios to produce organic and inorganic soil amendments: PLFR, PLFA, MFFR, and MFFA. And their optimum mixing ratios were determined by comparing the potassium, calcium concentrations, and pH of filtrate after dissolution. Then, a leaching experiment was conducted by packing mixtures (mass ratio of soil to amendment = 219:1, equivalent to 13 t/hm2) of the saline-sodic soil with each one of these amendments plus two contrasts, gypsum (GP), and no amendment (CK). And the remediation effect was compared by pH, EC, ESP, texture, organic recombination degree of clay, saturated hydraulic conductivity, water-stable aggregates fraction, and enzyme (urease, alkaline phosphatase, and catalase) activities of soil. After four times leaching experiment, soil treated with PLFR had lower pH and 25.86% lower exchangeable sodium than untreated soils. The water-stable small macroaggregate fractions and saturated hydraulic conductivity of the MFFR-treated soils were significantly increased by 133% and 31%, respectively. Also, the total soil and heavy fraction organic carbons of the soils treated with MFFR in addition to its alkaline phosphatase activity were all significantly higher than the other treatments. The results revealed that MFFR has more potential as a soil amendment to improve soil structure and quality and thus help in the development and use of saline-sodic lands for agriculture.

One test rig with three blades and two Under-Platform Dampers (UPDs) is established to better understand the dynamical behavior of blades with UPDs. A pre-loaded spring is used to simulate the centrifugal load acting on the damper, thereby achieving continuous adjustment of the pressing load. UPDs with different forms, sizes and materials are carefully designed as experimental control groups. Noncontact measurement via a laser Doppler velocimeter is employed and contact excitation which is performed by an electromagnetic exciter is adopted to directly obtain the magnitude of the excitation load by a force sensor mounted on the excitation rod. Particular attention is paid to the influence of the contact status of the contact surfaces, e.g. the pressure-sensitive paper is used to measure the effective contact area of the UPDs. The experimental variables are selected as the centrifugal force, the amplitude of the excitation force, the damper mass, the effective contact area, and the damper material. The Frequency Response Function (FRF) of the blade under different experimental parameters is obtained by slow frequency sweep under sinusoidal excitation to study the influence of each parameter on the dynamic characteristics of the blade and the mechanism analysis is carried out combined with the experimental results. Keywords: Effective contact area, Forced response, Friction, Test rig, Turbo machinery, Underplatform dampers

To raise the superconducting-transition temperature (T c ) has been the driving force for the long-sustained effort in superconductivity research. Recent progress in hydrides with T c s up to 287 K under pressure of 267 GPa has heralded a new era of room temperature superconductivity (RTS) with immense technological promise. Indeed, RTS will lift the temperature barrier for the ubiquitous application of superconductivity. Unfortunately, formidable pressure is required to attain such high T c s. The most effective relief to this impasse is to remove the pressure needed while retaining the pressure-induced T c without pressure. Here, we show such a possibility in the pure and doped high-temperature superconductor (HTS) FeSe by retaining, at ambient pressure via pressure quenching (PQ), its T c up to 37 K (quadrupling that of a pristine FeSe at ambient) and other pressure-induced phases. We have also observed that some phases remain stable without pressure at up to 300 K and for at least 7 d. The observations are in qualitative agreement with our ab initio simulations using the solid-state nudged elastic band (SSNEB) method. We strongly believe that the PQ technique developed here can be adapted to the RTS hydrides and other materials of value with minimal effort.

Coronavirus Disease 2019 (COVID−19) elicited by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS−CoV−2) is calling for novel targeted drugs. Since the viral entry into host cells depends on specific interactions between the receptor−binding domain (RBD) of the viral Spike protein and the membrane−bound monocarboxypeptidase angiotensin converting enzyme 2 (ACE2), the development of high affinity RBD binders to compete with human ACE2 represents a promising strategy for the design of therapeutics to prevent viral entry. Here, we report the discovery of such a binder and its improvement via a combination of computational and experimental approaches. The binder micasin, a known fungal defensin from the dermatophytic fungus Microsporum canis with antibacterial activity, can dock to the crevice formed by the receptor−binding motif (RBM) of RBD via an extensive shape complementarity interface (855.9 Å2 in area) with numerous hydrophobic and hydrogen−bonding interactions. Using microscale thermophoresis (MST) technique, we confirmed that micasin and its C−terminal γ−core derivative with multiple predicted interacting residues exhibited a low micromolar affinity to RBD. Expanding the interface area of micasin through a single point mutation to 970.5 Å2 accompanying an enhanced hydrogen bond network significantly improved its binding affinity by six−fold. Our work highlights the naturally occurring fungal defensins as an emerging resource that may be suitable for the development into antiviral agents for COVID−19.

In the multirotation computational imaging system (MRCI), the rotation angle of the cylindrical lens is vital to the reconstruction results from the experimental data. However, the rotation angles of the cylindrical lens are hard to be measured directly and precisely. High-precision angle evaluation methods are urgently needed to improve the recovered images. This paper proposes an angle estimation scheme based on principal component analysis (PCA), which can calculate the rotation angle of the cylindrical lens efficiently and accurately. Its accuracy is an order of magnitude higher than that of the existing methods. The proposed method is also stable for the image reconstruction when testing complex samples and under defocusing case.

Alginate-based composites have been extensively studied for applications in energy and environmental sectors due to their biocompatible, nontoxic, and cost-effective properties. This review is designed to provide an overview of the synthesis and application of alginate-based composites. In addition to an overview of current understanding of alginate biopolymer, gelation process, and cross-linking mechanisms, this work focuses on adsorption mechanisms and performance of different alginate-based composites for the removal of various pollutants including dyes, heavy metals, and antibiotics in water and wastewater. While encapsulation in alginate gel beads confers protective benefits to engineered nanoparticles, carbonaceous materials, cells and microbes, alginate-based composites typically exhibit enhanced adsorption performance. The physical and chemical properties of alginate-based composites determine the effectiveness under different application conditions. A series of alginate-based composites and their physicochemical and sorptive properties have been summarized. This critical review not only summarizes recent advances in alginate-based composites but also presents a perspective of future work for their environmental applications.

Novel biochar was prepared by ball milling using bamboo as raw material. The aim of this study was to find a good alternative way to improve the potentials of biochar for ammonium adsorption from aqueous solution. The sorption performance of ball-milled bamboo biochar (BMBB) was compared with that of bamboo biochar (BB) using batch adsorption experiments. Different adsorption kinetics models proved that the pseudo-second order was the best kinetic model for explanation of the adsorption kinetics characteristics, indicative of the energetically heterogeneous solid surface of the biochar. The Langmuir model could fit the isothermal adsorption data of BMBB well. The maximum adsorption capacity of BMBB (22.9 mg g−1) was much higher than that of BB (7.0 mg g−1). This study offers a relatively cost-effective and efficient methodology for the improvement in the adsorption capacity of biochar for ammonium nitrogen.

In this work, an evaluation methodology is proposed to study the impacts of state instability and retention failure of filamentary analog resistive random access memory (FA-RRAM) on the performance of deep neural networks (DNNs). Based on the methodology, an analytic model for the statistical state instability and retention behaviors is applied to evaluate the impacts of the reliability of FA-RRAM on an 11-layer FA-RRAM-based DNN for CIFAR-10 recognition. Simulations indicate that the recognition accuracy of the 11-layer DNN decreases rapidly with the increase of the baking time (t = 104s, 16.3% accuracy loss at 125 °C) due to the overlapping among neighboring resistance levels. To mitigate the accuracy loss caused by state instability and retention failure, the optimization method including the optimized synapse cell and the refresh operation scheme is developed. With the optimization method, the robustness of the FA-RRAM-based DNN is enhanced significantly in which no accuracy loss is observed even after 107s (at 125 °C, ${5} \times {10}^{{3}}$ s/refresh).

To deeply remove nitrogen (N) and phosphorus (P) from constructed wetlands (CWs), the authors found that CWs can be combined with the use of photovoltaic energy for best results. Thus, electrolysis-integrated, biochar-amended, horizontal (subsurface)-flow-constructed wetlands (E-BHFCWs) were combined with free-water, surface-constructed wetlands (FWSCWs) to remove N and P from secondary effluent water of a wastewater treatment plant (WWTP). Photovoltaic energy was used for electrolysis to intensify the removal of nitrate nitrogen (NO3−-N), ammonium nitrogen (NH3-N), and phosphate phosphorus (PO43−-P) in E-BHFCWs. In addition, FWSCWs were constructed to further remove NO3−-N, NH3-N, PO43−-P and iron ions in effluent of E-BHFCWs and to enhance DO concentration. For the E-BHFCWs combined with FWSCWs, the removal rates of NO3−-N, NH3-N, and PO43−-P were 73.28%, 53.11% and 67.58% respectively. The removal amounts of NO3−-N, NH3-N, and PO43−-P were about 211.08 kg N/a, 64.81 kg N/a and 10.46 kg P/a by E-BHFCWs. Photovoltaic electrolysis in E-BHFCWs was able to enhance NO3−-N removal through electrochemical reduction by iron cathodes, enriched hydrogenotrophic bacteria in the substrate, and by modified biochar substrate in situ with iron ions. Meanwhile, NH3-N was mainly removed by modified biochar adsorption, nitrifying microbes, and plant uptake. The removal rate of PO43−-P was also enhanced due to the formation of ferric ions by the anodization of sacrificial iron anodes, causing chemical precipitation, physical adsorption, and flocculation of PO43−-P. Thus, E-BHFCWs combined with FWSCWs are capable of effectively promoting removals of NO3−-N, NH3-N, and PO43−–P and provide a new insight into a new energy flow that can enhance N and P removals of CWs.

Active noise control (ANC) is used to reduce undesirable noise, particularly at low frequencies. There are many algorithms based on the least mean square (LMS) algorithm, such as the filtered-x LMS (FxLMS) algorithm, which have been widely used for ANC systems. However, the LMS algorithm cannot balance convergence speed and steady-state error due to the fixed step size and tap length. Accordingly, in this article, two improved LMS algorithms, namely, the iterative variable step-size LMS (IVS-LMS) and the variable tap-length LMS (VT-LMS), are proposed for active vehicle interior noise control. The interior noises of a sample vehicle are measured and thereby their frequency characteristics. Results show that the sound energy of noise is concentrated within a low-frequency range below 1000 Hz. The classical LMS, IVS-LMS and VT-LMS algorithms are applied to the measured noise signals. Results further suggest that the IVS-LMS and VT-LMS algorithms can better improve algorithmic performance for convergence speed and steady-state error compared with the classical LMS. The proposed algorithms could potentially be incorporated into other LMS-based algorithms (like the FxLMS) used in ANC systems for improving the ride comfort of a vehicle.

Bismuth oxyhalide (BiOX)-based heterostructures have attracted much attention due to their promotion effect on photocatalytic performance. Nonetheless, there is a lack of theoretical understanding on the relationship between the BiOX-induced interface and the enhancement of photocatalytic activity. In the present work, density functional theory (DFT) calculations were conducted to investigate the energy band structure, charge transfer and optic properties of layered MoS 2 /BiOX (X = Cl, Br, I) van der Waals (vdW) heterojunctions. All the MoS 2 /BiOX heterojunctions have lower band gaps, smaller effective mass and better light absorption ability than BiOX monolayers. Moreover, electrons transfer from MoS 2 to BiOX, and MoS 2 /BiOX heterojunctions show typical type-II band arrangement. Importantly, MoS 2 /BiOI presents significant performance in the carrier mobility and light absorption ability among the three heterostructures, which can facilitate effective separation of photo-generated electron-hole pairs and enhance photocatalytic activity. It is disclosed that the band edges MoS 2 /BiOX are suitable for the photocatalytic decomposition of water into oxygen. It is especially so for MoS 2 /BiOI which can affect full photocatalytic water splitting. The results clarify why the combination of MoS 2 and BiOX for the generation of MoS 2 /BiOX vdW heterojunctions could result in excellent photocatalytic activity, and disclose why MoS 2 /BiOI is the best among the three for photocatalytic water splitting.

Long-term wellbeing monitoring is an underlying theme in many local and national policies and procedures outlined by governments and health care services. Natural, efficacious, and trustworthy monitoring by using wearable sensors is necessary for researchers to find and establish the interrelationships of Affective Computing (AC), Body Sensor Networks (BSNs), Social Signal Processing (SSP) and Physical Mental Health (PMH). Specially, Giancarlo Fortino, et al. have an outstanding contribution for applying BSNs on health monitoring. This paper investigated how technology can help to objectively monitor an individual’s wellbeing in a naturalistic environment. For this purpose, we designed and implemented a wearable device with the integration of multi-sensors which consist of audio sensing, behavior monitoring, environment and physiological sensing. In order to avoid privacy issues, four audio-wellbeing features are embedded into a wearable hardware platform to automatically evaluate speech information without preserving raw audio data. In addition, four weeks of long-term monitoring experiment studies have been conducted in conjunction with a series of wellbeing questionnaires in a group of students. The relationships between physical and mental health were investigated objectively by utilizing data from speech, behavioral activities and ambient factors in a completely natural daily situation.

Nonvolatile and cascadable stateful logic operations are experimentally demonstrated within a 1 k-bit one-transistor-one-resistor (1T1R) resistive random access memory (RRAM) array, where NAND gates serve as the building blocks. A robust dual-gate-voltage operation scheme is proposed. The effects of the transistor ON logic operation and the robustness to device parameter variations are discussed. The parallel 4-bit bitwise XOR operation is experimentally implemented in the 1T1R array by cascading NAND gates. This letter presents a feasible approach to in-memory computing for large-scale circuits.

The design and fabrication of robust and inexpensive bifunctional catalysts for oxygen evolution reaction and hydrogen evolution reaction are very necessary for producing hydrogen by water electrolysis. Herein, we propose a bi-functional CoP@N-doped porous carbon nanoplate (CoP@NPCP) electrocatalyst, in which CoP nanoparticles with graphitized carbon capsule layers are uniformly anchored on the N-doped carbon nanoplates. Benefiting from structural advantages and componential superiorities, the CoP@NPCP exhibits remarkable electrocatalytic activity and superior durability for both oxygen evolution reaction and hydrogen evolution reaction in the alkaline medium. The present synthetic strategy is very feasible for the design of the metallic phosphide nanoparticles encapsulated in N-doped porous carbon nanoplates.

In the present work, we investigate the graphic carbon nitride (g-CN) film as photoanode to catalyze the photoelectrochemical (PEC) water oxidation and study the influence of NiCo layered double hydroxides (NiCo-LDH) layer on the performance. The g-CN film with good quality and intimate contact with substrate was in-situ prepared via solvothermal process and subsequent calcination. NiCo-LDH is further decorated on the g-CN film through cathodic electrochemical deposition to work as co-catalyst. The g-CN/NiCo-LDH composite with optimized NiCo-LDH loading amount exhibits a photocurrent of 11.8 μA cm−2 at 0.6 V vs. SCE, which is 2.8 times of bare g-CN. Characterizations and performance tests demonstrate that NiCo-LDH promoted reaction kinetics and charge separation. The results provide an effective strategy to improve the photoelectrochemical water oxidation performance of g-CN through NiCo-LDH co-catalyst. This work to investigate the photoelectrochemical water oxidation is of great significance toward explore the overall water splitting on the g-CN film.

Owing to their attractive application potentials in both non-volatile memory and unconventional computing, memristive devices have drawn substantial research attention in the last decade. However, major roadblocks still remain in device performance, especially concerning relatively large parameter variability and limited cycling endurance. The response of the active region in the device within and between switching cycles plays the dominating role, yet the microscopic details remain elusive. This Review summarizes recent progress in scientific understanding of the physical origins of the non-idealities and propose a synergistic approach based on in situ characterization and device modeling to investigate switching mechanism. At last, the Review offers an outlook for commercialization viability of memristive technology., Memristor as the fourth basic element of electric circuits has drawn substantial attention for developing future computing technologies. Sun et al. report the progress and the challenges facing researchers on understanding memristive switching, and advocate continuous studies using a synergistic approach.

Deep defect detection for ferromagnetic materials is a challenging task for Eddy Current testing (ECT) due to the skin effect of the low penetration depth. Pulsed Eddy Current testing (PECT) is a potential and effective method for detecting deep subsurface defects as it can obtain multiple depth information owing to its wide spectrum range. A novel weak coupling sensing structure of pulsed eddy current is proposed. In particular, the structure improves the ratio of the indirect coupling energy by reducing the direct coupling energy between the excitation and the detection coils. It obviously improves the ability to detect deep subsurface defects of ferromagnetic materials. The principle of penetration and the analysis of its equivalent circuit are presented. In addition, both experiments and simulations on different defects detection have been studied. The results have confirmed that all types of defects can be detected and it has shown the relatively monotonic linear relationships and reliability.

The promising characteristics of nanoscale zero-valent iron (nZVI) have not been fully exploited owing to intrinsic limitations. Carbon-enriched biochar (BC) has been widely used to overcome the limitations of nZVI and improve its reaction with environmental pollutants. This work reviews the preparation of nZVI/BC nanocomposites; the effects of BC as a supporting matrix on the nZVI crystallite size, dispersion, and oxidation and electron transfer capacity; and its interaction mechanisms with contaminants. The literature review suggests that the properties and preparation conditions of BC (e.g., pore structure, functional groups, feedstock composition, and pyrogenic temperature) play important roles in the manipulation of nZVI properties. This review discusses the interactions of nZVI/BC composites with heavy metals, nitrates, and organic compounds in soil and water. Overall, BC contributes to the removal of contaminants because it can attenuate contaminants on the surface of nZVI/BC; it also enhances electron transfer from nZVI to target contaminants owing to its good electrical conductivity and improves the crystallite size and dispersion of nZVI. This review is intended to provide insights into methods of optimizing nZVI/BC synthesis and maximizing the efficiency of nZVI in environmental cleanup.

Doping of nitrogen (N) on carbon materials often requires complicated synthetic steps or specific machinery. In this study, N-doped biochar was successfully synthesized by simply ball milling pristine biochar with ammonium hydroxide. The content and species of N in the resulting N-doped biochars were carefully characterized, the formation mechanisms of N-related groups were illustrated, and their applications in CO2 uptake and reactive red removal were evaluated. Most of N introduced to biochar was loaded on its surface in forms of NH2 and C N, resulting from the dehydration of COOH and OH. Biochars produced at 450 °C were doped with more N on the surface (XPS, 2.41%–2.65%) than those produced at 600 °C (XPS, 1.18%–1.82%) because the content of O-containing functional groups in biochar decreases with increasing pyrolysis temperature. The basic properties of N-related groups enhanced the sorption performance of biochar to both acidic CO2 and anionic reactive red. For example, the CO2 uptake of the N-doped, 450 °C hickory biochar was 31.6%–55.2% higher than the corresponding pristine and ball-milled biochars. The maximum sorption capacity of the N-doped, 600 °C bagasse biochar to reactive red was about 3.66–16.2 times of the corresponding biochars without N doping. This paper provides an alternative and facile approach to prepare N-doped biochar that can be extended to other carbon materials to meet the specific needs in different applications, especially adsorption.