Acetaminophen (APAP), a widely used analgesic and antipyretic, poses significant health risks upon prolonged or excessive exposure, necessitating sensitive and reliable detection methods. Herein, we fabricated an electrochemical sensing platform for APAP detection based on a novel rice husk biochar (RHB)/MXene-AuNPs composite. The composite synergistically integrates RHB's (derived from agricultural waste) sustainable porous architecture, MXene's excellent conductivity and AuNPs' abundant catalytic sites, enabling efficient APAP oxidation. The sensing platform achieves a linear quantification range of 0.03-8.88 & micro;M with an ultrasensitive detection limit of 21.4 nM (S/N = 3). It also exhibits robust stability (RSD < 1% after 110 cycles), high reproducibility (2.32% RSD across electrodes), and excellent selectivity against 50-fold excess interferents. Validation using commercial 999 Cold and Flu Granules yields recoveries of 96.2-101.7%, confirming its accuracy. This work pioneers a sustainable sensing strategy by transforming rice husk waste into a high-value electrode material, offering a robust, precise, and eco-friendly approach for APAP quantification in pharmaceutical and clinical applications.

Violet phosphorus is a phosphorus allotrope, whereas violet phosphorene (VP) refers to its few-layer or monolayer two-dimensional form obtained through exfoliation. Owing to its tunable bandgap, high carrier mobility, intrinsically anisotropic charge-transport characteristics, abundant surface-active sites, and superior environmental stability relative to black phosphorene, VP and its derivatives have emerged as highly promising metal-free semiconducting materials for next-generation sensing technologies. Recent advances have enabled not only the high-yield synthesis of high-quality bulk violet phosphorus crystals and the liquid-phase exfoliation of ultrathin VP nanosheets with nanoscale thickness, but also the rational construction of VP-based heterostructures and nanocomposites that achieve ppb-level gas detection, nanomolar electrochemical sensing, and femtomolar biosensing. This comprehensive review critically summarizes the current progress and remaining challenges in the synthesis, structural engineering, and sensing application of VP-based nanomaterials, while highlighting emerging research directions, including machine learning-assisted preparation of VP nanocomposites and the rational design of multifunctional and multimodal sensing platforms. Through a critical assessment of current advancements and unresolved scientific challenges, this review aims to provide a comprehensive theoretical framework and strategic guidance for the development of next-generation VP-based sensing materials, thereby accelerating their practical implementation and fostering transformative advances across diverse sensing technologies.

Soil acidification and potentially toxic metal (PTM) co-contamination threaten agroecosystems in southern China, yet conventional remediation strategies struggle to address both issues simultaneously. Here, we engineered a thermally activated serpentine (600 °C, TSRP) as a dual-functional adsorbent for concurrent PTM immobilization and soil pH regulation. Structural characterization revealed that thermal treatment transformed serpentine into mesoporous forsterite (Mg2SiO4) with a surface area of 46.08 m2 g−1 and abundant Si-O− sites. Batch adsorption experiments demonstrated exceptional removal efficiencies: 99.94% for Cd2+, 99.26% for Pb2+, and 86.75% for Cu2+ under optimized conditions with 0.5 g L−1 TSRP. Mechanistic studies identified four synergistic pathways: (1) Mg2+-Cd2+/Pb2+ ion exchange, (2) hydroxide/carbonate precipitation, (3) pore adsorption, and (4) complexation with silico-oxygen groups. In multi-metal systems, Pb2+ exhibited preferential adsorption due to higher electronegativity, while Cu2+ leveraged pore accessibility post-saturation. Field validation in acidified paddy soils (2% TSRP application) elevated soil pH from 5.43 to 7.89 and reduced bioavailable Cd, Pb, and Cu by 24.2%—35.4% over 180 days. This work advances serpentine waste valorization into a sustainable, scalable adsorbent for co-contaminated agroecosystems, bridging structural engineering, mechanistic insights, and real-world remediation efficacy.

Widespread copper (Cu2+) pollution from mining and industrial activities demands effective, low-cost remediation solutions. This study developed a novel adsorbent fabricated through a simple one-step co-pyrolysis of magnesium-rich serpentine jade waste (SJ) and rice straw biochar (BC) at an optimal SJ:BC mass ratio of 1:5, denoted as SJBC. The composite achieved a maximum Cu2+ adsorption capacity of 131.91 mg g-1, significantly surpassing that of pristine BC (46.67 mg g-1) and thermally treated SJ (100.75 mg g-1). Comprehensive characterization using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS) confirmed the successful integration of SJ into the carbon matrix, resulting in enhanced surface roughness, increased oxygen-containing functional groups, and the formation of active MgO sites. Adsorption isotherms were best fitted by the Freundlich model, while kinetics followed the Elovich model, indicating a chemisorption-dominated process on a heterogeneous surface. The removal mechanism involved synergistic effects of Mg2+-facilitated ion exchange, surface precipitation of Cu(OH)2, complexation with oxygen functional groups, and potential Cu2+-π interactions. The composite exhibited excellent pH adaptability, maintaining high removal efficiency (>95%) in the environmentally relevant pH range of 4-6, and demonstrated effective performance in real copper-laden wastewater. This work presents a sustainable strategy for dual waste valorization, transforming industrial and agricultural residues into a high-performance, low-cost material for copper remediation in water, with promising potential for soil stabilization applications.

Recalcitrant pollutants, such as pesticides, antibiotics, and heavy metal ions (HMIs) in agricultural wastewater, pose serious threats to environmental safety and human health. Conventional treatment technologies often suffer from low efficiency, high energy consumption, and risks of secondary pollution. Transition metal oxide (TMO) photocatalysts have garnered significant attention for the treatment of advanced agricultural wastewater owing to their excellent physicochemical stability, tunable electronic structures, and potential for solar energy utilization. This review systematically summarizes recent research progress on TMO photocatalysts for this application, elucidating the mechanisms involved in the photocatalytic degradation of organic pollutants and reduction of HMIs. The structural characteristics and photocatalytic properties of single-metal oxides, multi-metal oxides, and heterojunction composites are comprehensively examined. From a goal-oriented perspective, key modification strategies including enhanced visible-light harvesting, optimized charge carrier dynamics, surface active site engineering, and improved pollutant affinity are critically discussed. Furthermore, the effects of pollutant properties, wastewater complexity, and operational conditions on photocatalytic performance are systematically analyzed. Finally, future perspectives encompassing customized material design, stability enhancement, and practical implementation are proposed, with the integration of emerging approaches such as nanozymes, materials genomics, and artificial intelligence. This review aims to provide theoretical insights and technical guidance for the efficient and sustainable treatment of agricultural wastewater.

In this study, we synthesized Fe, N, S co-doped hierarchically porous carbon (Fe-CSK-PCP) with a high specific surface area of 1826.34 m2/g and a pore volume of 1.14 cm3/g. This material was prepared using discarded lotus seedpods as a carbon source, potassium hydroxide (KOH) as an activator, potassium ferricyanide as both an activator and graphitization promoter, thiourea as a source of N and S dopants, and cetyltrimethylammonium bromide (CTAB) as a pore-enlarging agent. Platinum nanoparticles (PtNPs) were subsequently loaded onto the Fe-CSK-PCP surface via wet impregnation. The enhanced porosity, increased pore size, and heteroatom doping of the Fe-CSK-PCP support have significantly promoted the loading content and dispersion of PtNPs, consequently creating an abundance of active sites. Meanwhile, the hierarchical pore structure has improved the diffusion of analyte and the desorption of oxidation product. Therefore, the fabricated PtNPs/Fe-CSK-PCP sensor exhibited exceptional fouling resistance and electrocatalytic performance in indole-3-acetic acid (IAA) detection, demonstrating a high sensitivity (2.32 mu A/mu M) and a low detection limit (21.67 nM, S/N = 3) over a wide linear range (0.3-20 mu M). This sensor was successfully applied to determine IAA in apple juice samples with satisfactory recoveries.

Ustilaginoidea oryzae, the ascomycete fungus responsible for Rice False Smut (RFS), devastates global rice yields via rice panicles infection, threatening food security. To address the critical need for early pathogen detection, we developed an ultrasensitive electrochemical genosensor utilizing a gold-palladium bimetallic nanoparticle (Au-PdNPs) decorated violet phosphorene/boron nitride (VP/BN) nanohybrid. The VP/BN support, synthesized via sonication-assisted liquid-phase exfoliation, enabled the uniform anchoring of Au-PdNPs through chemical reduction, creating an enhanced conductive interface. Thiolated DNA probes immobilized on Au-PdNPs via Au-S bonds enabled specific recognition of U. oryzae DNA through hybridization. This design achieved exceptional sensitivity with a broad linear range (0.1 mu M to 10 pM) and ultralow detection limit (3.67 pM), surpassing some traditional detection methods reported at present in speed and cost-efficiency. The genosensor exhibited high specificity against non-target sequences and delivered 96.6-98 % recovery in spiked rice samples, validating its effectiveness in practical applications. By integrating nanomaterials with electrochemical amplification, this work paves the way for field-deployable portable U. oryzae diagnostics in the future, offering a transformative strategy to mitigate economic and agricultural impacts.

The irrational use of tetracycline (TC) in animal husbandry leads to harmful residues in food products, necessitating robust detection methods. This study develops a dual-mode sensor using a nitrogen-doped porous carbon/iron-based nanocrystal material (Fe-NPC), derived from NH2-MIL-88B, for highly sensitive and selective TC detection. The Fe-NPC material integrates dual functions, serving as an excellent electrode modifier for an electrochemical sensor and as a high-efficiency nanozyme for a colorimetric assay. For electrochemical detection, a molecularly imprinted polymers (MIPs) were constructed on the Fe-NPC-modified electrode, achieving a wide linear range of 0.01-80 mu M with a limit of detection (LOD) of 3 nM. For colorimetric detection, TC inhibits the peroxidase-like activity of Fe-NPC in catalyzing the 3,3 ',5,5 '-tetramethylbenzidine (TMB)-H2O2 reaction, providing exceptional sensitivity with a linear range of 0.001-0.225 mu M and LODs of 0.17 nM (UV-Vis) and 0.82 nM (smartphone RGB analysis). Both modes demonstrated high stability and accurate detection in real milk and meat samples, with recoveries from 96.2% to 104.0%, validated by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This work presents a reliable and versatile platform for monitoring TC residues in complex food matrices.

A highly sensitive and selective molecularly imprinted electrochemical sensor was developed for the detection of sulfachloropyrazine sodium (SPZ), assisted by machine learening (ML) optimization. The sensing platform was fabricated using novel Bi-rich BiOBr/BC@AuNPs nanocomposite, where the synergistic combination of Bi-rich BiOBr, conductive biochar, and gold nanoparticles markedly enhanced electron transfer and provided abundant electroactive sites. Critical imprinting parameters, including the functional monomer-to-template ratio, electropolymerization cycles, elution time, and incubation time, were optimized using a central composite design coupled with ML algorithms like support vector regression. Under optimal conditions, the sensor displayed a wide linear range of 0.031-61.34 ng/mL, with a low detection limit of 0.0025 ng/mL and a quantification limit of 0.0077 ng/mL. The sensor exhibited excellent selectivity, effectively distinguishing SPZ from structurally analogous sulfonamide. Successful application to spiked chicken, milk, and honey samples yielded satisfactory recoveries and reproducibility, confirming its strong potential for practical food safety.

The irrational use of tetracycline (TC) in livestock production has led to the contamination of animal-derived food with TC residues, posing significant risks to human health. To address this issue, we developed a molecularly imprinted electrochemical sensor for highly sensitive and selective detection of TC using a composite of both bimetallic organic framework and carboxyl multi-walled carbon nanotubes (ZnCo-MOF/COOH-MWCNTs). This synergistic material combines the high surface area of ZnCo-MOF for enhanced adsorption and the conductivity of COOH-MWCNT for signal amplification, significantly improving the sensor's performance. Electro-polymerization of the molecularly imprinted polymers (MIPs) on the electrode surface further amplifies the signal response and enables selective recognition of TC through complementary cavities. The developed sensor achieved a wide linear detection range (0.1 - 100 mu M) and an ultralow detection limit of 0.067 mu M. The proposed method demonstrated recoveries of 96.4 % - 107.1 % with RSDs < 2.3 % when applied to detect TC in milk, egg, and pork samples, validated by high-performance liquid chromatography (HPLC). This work provides a reliable and rapid method for monitoring TC residues in food, advancing food safety regulation and public health protection.

The simultaneous electrochemical detection of catechol (CC) and hydroquinone (HQ) isomers is hindered by overlapping voltammetric signals, creating a persistent sensitivity-selectivity-accuracy paradox. Herein, we present a synergistic sensing platform integrating BC-Co@NC nanoarchitectures (engineered via topotactic carbonization to form 3D hierarchical pores with atomically dispersed Co-N-4 sites) and a first- and second-derivative voltammetry cascade (FS-DVC) optimized by Savitzky-Golay algorithm. This dual-engine strategy achieves 152 mV interpeak separation, ultra-low limits of detection (0.09 nM for CC, 0.12 nM for HQ), a linear range spanning four orders of magnitude (0.3-500 mu M), and robust performance in environmental matrices (95.2-99.1% recoveries in agricultural water/soil). This work establishes a new paradigm for electrochemical isomer discrimination through the synergistic fusion of tailored material design and advanced signal mathematics.

Recent advancements in two-dimensional materials have highlighted black phosphorene (BP) as a promising candidate for optical and electrical applications. However, its practical utility is hindered by ambient instability and limited conductivity. This study aims to solve these problems with a surface passivation strategy. Silver nanoparticles (AgNPs) and rice husk biochar (RHB) are combined to prepare a BP-based nanocomposite (RHBBP-AgNPs). AgNPs effectively occupy oxidation sites on BP's surface, mitigating degradation while enhancing conductivity with RHB synergy. The morphology, microstructure and chemical composition of RHB-BP-AgNPs nanocomposite was comprehensively characterized by diversified techniques. The RHB-BP-AgNPs exhibited exceptional ambient stability (>16 days) and superior electrocatalytic activity, enabling its application as a sensing platform for baicalin detection. The sensor demonstrated a wide linear response (0.007-8.0 mu M), a low detection limit (5.45 nM), and high selectivity against interferents. Validation in real pharmaceutical samples yielded satisfactory recovery rates of 95.4-104.6 % with RSD from 1.27 to 2.13, underscoring practical reliability. This work not only presents a robust strategy to stabilize and functionalize BP but also advances rapid, sensitive detection methodologies for bioactive compounds in traditional medicine, bridging material innovation with analytical applications.

Copper ions (Cu2+) in rice, primarily introduced via fertilizers, significantly impact the quality of rice plants. To address the need for precise detection, this study introduces a dual-mode intelligent sensor based on a phytic acid (PA)-functionalized hydrophilic porous composite (DSC/Mg0.43Mn0.57O@MgMn-MOF@PA). The composite is synthesized through a facile synergistic strategy combining PA-mediated etching and surface functionalization of bimetallic oxide-loaded biochar (DSC/MgxMnxO) modified with a metal-organic framework (MOF). PA etching enhances the aqueous stability of the inherently unstable MgMn-MOF, while the effective integration of durian shell biochar (DSC), MgxMnxO and MgMn-MOF synergistically improves the conductivity and electrocatalytic activity. The composite demonstrates exceptional performance for Cu2+ detection with a broad linear range from 1 ng/L to 300 mu g/L with an ultralow limit of detection (LOD) of 0.26 ng/L. The incorporation of both MgxMnxO and MgMn-MOF confers like-enzyme activity, enabling a colorimetric assay via catalytic oxidation of TMB into blue ox-TMB. This colorimetric mode offers a linear range from 50 mu g/L to 5 mg/L for Cu2+ with a LOD of 15.41 mu g/L. The dual-mode sensor exhibits high specificity for Cu2+, even in the presence of interfering metal ions, and successfully monitoring Cu2+ levels in rice paddies. On basis of dual-mode detection platform, a deep learning approach with one-dimensional convolutional neural network (1-D CNN) algorithm is employed to validate both reliability and accuracy. This work advances the design of hydrophilic, defect-rich MOF derived from bimetallic oxide-loaded biochar and establishes a robust reference for intelligent, dual-modal heavy metal detection in agricultural systems.

MicroRNA-319a plays an important role in the stress physiology of rice. The preparation of violet phosphorene (VP) and its modification for both development and application of chemo/bio-sensors have become a hot topic in the interdisciplinary field. Herein, we develop a highly-stable gold-palladium bimetallic nanoparticles decorated VP with polyamidoamine dendrimer as the substrate, and gold nanoparticles bifunctionalized both horseradish peroxidase and single-stranded DNA as signal amplifcation probe for ultrasensitive sensing of microRNA-319a. The hybridization chain reaction and the interaction mechanism of classic competitive recognition between aptamers and targets are used to achieve the enrichment of signal amplification probe. The random forest and gradient boosting machine as machine learning models are used to optimize the preparation of electrode materials and the intelligent analysis of test results. The prepared smartphone biosensor detected microRNA-319a in the linear range of 0.5 fM - 10 pM with a low limit of detection of 0.12 fM under optimal conditions. The developed method is successfully applied to detect the change of microRNA-319a content in rice leaves after ethyl methanesulfonate treatment of rice seeds. This research will offer a reference for the preparation of bimetallic nanoparticles decorated graphene-like materials for both the development and application of chemo/bio-sensors in crop stress physiology with ML assistance.

The illegal use of β-agonists like clenbuterol (CLB) and ractopamine (RAC) as livestock growth promoters poses severe threats to human health. To address this, we developed a novel electrochemical sensor based on violet phosphorene (VP) and carboxylated multi-walled carbon nanotubes (COOH-MWCNTs) with Nafion-isopropanol mixed solution for simultaneous voltammetric detection of CLB and RAC in beef. The sensing platform was optimized through response surface methodology coupled with particle swarm optimization, enabling multi-objective parameter (VP concentration, COOH-MWCNTs concentration, and pH value) refinement that enhanced sensitivity while minimizing experimental trials. This design leveraged the synergistic properties of VP (high carrier mobility) and COOH-MWCNTs (electrocatalytic activity), yielding a sensor with ultra-low detection limits of 5.8 nM for CLB and 6.4 nM for RAC, excellent selectivity with negligible interference from biological matrices, and high stability. Support vector machine (SVM) nonlinear models achieved robust quantification (R2 > 0.9948 and RPD > 7.09 for both analytes), validated by high recoveries (98.4–103.1

The base-free oxidation of lignin into valuable aromatic chemicals is a promising pathway for biomass valorization. Developing efficient LaBO3-based catalysts and elucidating the structure-activity relationship of B-site metal substitution is the key to improving the yield/selectivity of aromatic chemicals. In view of this, a series of LaFeO3-based catalysts with different strengths of oxygen vacancies and acid-base sites were tailored by replacing high valence Fe ions with low valence Ni ions to varying degrees. Afterwards, these catalysts performance were tested for the wet aerobic oxidation of corncob alkali lignin (CAL) in individual alcohol or alcoholwater co-solvent system. Extraordinary catalytic performance was achieved when the Ni substitution degree was 0.8 in iPrOH-H2O (v/v = 1:1) co-solvent system, affording a 14.52 % yield of six aromatic aldehydes and acids. Electron paramagnetic resonance (EPR) measurements and radical quenching experiments confirmed the involvement of center dot O2- and center dot OH radicals in CAL catalytic oxidation system. Mechanism studies pronounced that the oxidative dehydrogenation of C alpha H-OH by center dot O2- that originated from O2 adsorbed on oxygen vacancies of catalyst was the initially step. Subsequently, the formed C alpha HO* was adsorbed on Fe delta+ acidic active sites with strong oxygen affinity, while activating the cleavage of C alpha-C beta, C beta-O-4 and C beta-C gamma linkages. Moreover, the existence of synergistic effect between Fe and Ni cations, where Fe4+ species obtaining electrons from Ni2+ species and transformed into Fe3+ species, resulting in an increase in oxygen vacancy concentration, thereby promoting the production of aromatic aldehydes and acids. This work provided fundamental guidance for a deeper understanding of the relationship between surface properties and activity to design efficient perovskite-based catalysts for lignin valorization.

Sulfadimidine (SM2), a potentially carcinogenic sulfonamides, poses a threat to food safety. In this study, a portable electrochemical sensing platform integrated with a smartphone is developed for on-site sulfadimidine (SM2) detection. The electrode utilizes a flexible three-electrode system based on laser-induced porous graphene (LIPG), fabricated via CO₂ laser etching of polyimide (PI) film. The platform is wirelessly connected to a portable electrochemical workstation and smartphone via Bluetooth. Laser parameters, including power and etching depth, are optimized to improve electrochemical performance. The optimized LIPG electrode exhibits significantly improved sensitivity—2.87 and 10.87-fold higher than screen-printed carbon electrode (SPCE) and glassy carbon electrode (GCE), respectively—along with excellent stability (RSD < 0.46

Understanding the key characteristics that affect energy storage performance of supercapacitors and investigating the marginal effects of key variables on supercapacitors are crucial. In this study, eight machine learning models optimize by Bayesian optimization algorithm were developed to predict the performance of biomass carbon-based electrochemical double-layer capacitors (EDLCs). Three model interpretation tools were employed to comprehend decision-making process and causal relationships between key input characteristics and capacitance. The categorical boosting model provided the best prediction, with a coefficient of determination of 0.9783. Shapley additive explanations method of feature importance analysis revealed that current density, pore volume of micropore (Vmicro), pore volume (PV), specific surface area (SSA), ID/IG, and nitrogen content were the primary factors influencing supercapacitors. Partial dependency plots and individual conditional expectation indicated the specific capacitance does not increase significantly with the increase of SSA, when SSA is >1250 m2/g. Blindly pursuing a larger specific surface area may not be able to increase the specific capacitance as desired. Additionally, the values of Vmicro, PV, ID/IG and nitrogen content were suggested to improve the energy storage performance. This study shows that the outstanding performance of interpretable machine learning framework has the potential to expedite the rational design of biomass carbon-based supercapacitors.

Mycophenolic acid (MPA), a prevalent mycotoxin, presents significant analytical challenges in complex silage matrices due to limited selectivity and pronounced electrochemical baseline drift. To address this, we developed an intelligent molecularly imprinted sensor (Fe3O4-MGO/MIP/GCE) for the sensitive and selective detection of MPA. This sensing platform incorporates Fe3O4 modified magnetic graphene oxide (Fe3O4-MGO) as a highly conductive nanocomposite substrate, with pyrrole-3-carboxylic acid (Py3C) serving as a dual-functional monomer. Py3C was electropolymerized in the presence of MPA to form recognition sites that also function as signal transducers. Furthermore, to overcome signal instability and subjective interpretation, we integrated a machine learning-assisted approach using a small-window moving average algorithm for automated baseline correction, coupled with interval partial least squares (iPLS) for precise peak identification. This data-driven strategy eliminates manual intervention, enhances signal fidelity, and improves analytical robustness in complex environments. The sensor demonstrated a wide linear range from 7.5 nmol L-1 to 5 μmol L-1, with a low detection limit of 2.1 nmol L-1 (S/N = 3). Recovery rates in real silage samples ranged from 91.5 % to 102.4 %, confirming high accuracy and strong anti-interference capability. This work successfully merges biomimetic molecular recognition with intelligent signal processing, offering a reliable and objective platform for the on-site monitoring of mycotoxins in agricultural systems.

A nanosensing platform was designed based on environmentally friendly cobalt phosphate-doped biochar (CoCPBC) derived from bamboo leaves for derivative voltammetric determination of hydroquinone (HQ) in water and soil samples. Highly ambient-stable CoCPBC is prepared by hydrothermal synthesis containing cobalt nitrate, phosphoric acid (H3PO4), cetyltrimethylammonium ammonium bromide (CTAB), and bamboo leaves. Benefiting from the high effective area, the CoCPBC displays more active sites for HQ recognition and simultaneously improving the conductivity of biochar. The CoCPBC electrode shows excellent stability with retaining 99.34