Improved performance of a fiber-optic hydrogen sensor based on a controllable optical heating technology.

A novel, to the best of our knowledge, and compact fiber-optic hydrogen sensor based on light intensity demodulation and controllable optical heating technology is proposed and experimentally investigated. This system employs three photodetectors for optic signal transformation. The first PD is used to receive a little fraction of the amplified spontaneous emission (ASE) for calibration, and the second PD is utilized to detect optic signal reflected by a single mode fiber deposited with WO3-Pd2Pt-Pt composite film. The last PD is utilized to receive the optical power reflected by the short fiber Bragg grating (SFBG) with a central wavelength located in a steep wavelength range (the intensity decreases approximately linearly with the increase of the wavelength) of the ASE light source. A 980 nm laser and proportion integration differentiation (PID) controller were employed to ensure the hydrogen sensitive film working at an operating temperature of 60°C. This sensing system can display a quick response time of 0.4 s toward 10,000 ppm hydrogen in air. In addition, the detection limit of 5 ppm in air can be achieved with this sensing system. The stability of this sensor can be greatly enhanced with a controllable optical heating system, which can greatly promote its potential application in various fields.

Approaching Ultimate Synthesis Reaction Rate of Ni-Rich Layered Cathodes for Lithium-Ion Batteries.

Nickel-rich layered oxide LiNixCoyMnzO2 (NCM, x + y + z = 1) is the most promising cathode material for high-energy lithium-ion batteries. However, conventional synthesis methods are limited by the slow heating rate, sluggish reaction dynamics, high energy consumption, and long reaction time. To overcome these challenges, we first employed a high-temperature shock (HTS) strategy for fast synthesis of the NCM, and the approaching ultimate reaction rate of solid phase transition is deeply investigated for the first time. In the HTS process, ultrafast average reaction rate of phase transition from Ni0.6Co0.2Mn0.2(OH)2 to Li- containing oxides is 66.7 (% s-1), that is, taking only 1.5 s. An ultrahigh heating rate leads to fast reaction kinetics, which induces the rapid phase transition of NCM cathodes. The HTS-synthesized nickel-rich layered oxides perform good cycling performances (94% for NCM523, 94% for NCM622, and 80% for NCM811 after 200 cycles at 4.3 V). These findings might also assist to pave the way for preparing effectively Ni-rich layered oxides for lithium-ion batteries.

Coupling Antisite Defect and Lattice Tensile Stimulates Facile Isotropic Li-Ion Diffusion.

Despite widely used as a commercial cathode, the anisotropic 1D channel hopping of lithium ions along the [010] direction in LiFePO4 prevents its application in fast charging conditions. Herein, an ultrafast nonequilibrium high-temperature shock technology is employed to controllably introduce the Li-Fe antisite defects and tensile strain into the lattice of LiFePO4. This design makes the study of the effect of the strain field on the performance further extended from the theoretical calculation to the experimental perspective. The existence of Li-Fe antisite defects makes it feasible for Li+ to move from the 4a site of the edge-sharing octahedra across the ab plane to 4c site of corner-sharing octahedra, producing a new diffusion channel different from [010]. Meanwhile, the presence of a tensile strain field reduces the energy barrier of the new 2D diffusion path. In the combination of electrochemical experiments and first-principles calculations, the unique multiscale coupling structure of Li-Fe antisite defects and lattice strain promotes isotropic 2D interchannel Li+ hopping, leading to excellent fast charging performance and cycling stability (high-capacity retention of 84.4% after 2000 cycles at 10 C). The new mechanism of Li+ diffusion kinetics accelerated by multiscale coupling can guide the design of high-rate electrodes.

In Situ Symbiosis of Cerium Oxide Nanophase for Enhancing the Oxygen Electrocatalysis Performance of Single-Atom Fe─N─C Catalyst with Prolonged Stability for Zinc-Air Batteries.

The Fenton reaction, induced by the H2O2 formed during the oxygen reduction reaction (ORR) process leads to significant dissolution of Fe, resulting in unsatisfactory stability of the iron-nitrogen-doped carbon catalysts (Fe-NC). In this study, a strategy is proposed to improve the ORR catalytic activity while eliminating the effect of H2O2 by introducing CeO2 nanoparticles. Transmission electron microscopy and subsequent characterizations reveal that CeO2 nanoparticles are uniformly distributed on the carbon substrate, with atomically dispersed Fe single-atom catalysts (SACs) adjacent to them. CeO2@Fe-NC achieves a half-wave potential of 0.89 V and a limiting current density of 6.2 mA cm-2, which significantly outperforms Fe-NC and commercial Pt/C. CeO2@Fe-NC also shows a half-wave potential loss of only 1% after 10 000 CV cycles, which is better than that of Fe-NC (7%). Further, H2O2 elimination experiments show that the introduction of CeO2 significantly accelerate the decomposition of H2O2. In situ Raman spectroscopy results suggest that CeO2@Fe-NC significantly facilitates the formation of ORR intermediates compared with Fe-NC. The Zn-air batteries utilizing CeO2@Fe-NC cathodes exhibit satisfactory peak power density and open-circuit voltage. Furthermore, theoretical calculations show that the introduction of CeO2 enhances the ORR activity of Fe-NC SAC. This study provides insights for optimizing SAC-based electrocatalysts with high activity and stability.

High-Pressure-Field Induced Synthesis of Ultrafine-Sized High-Entropy Compounds with Excellent Sodium-Ion Storage.

Emerging high entropy compounds (HECs) have attracted huge attention in electrochemical energy-related applications. The features of ultrafine size and carbon incorporation show great potential to boost the ion-storage kinetics of HECs. However, they are rarely reported because high-temperature calcination tends to result in larger crystallites, phase separation, and carbon reduction. Herein, using the NaCl self-assembly template method, by introducing a high-pressure field in the calcination process, the atom diffusion and phase separation are inhibited for the general formation of HECs, and the HEC aggregation is inhibited for obtaining ultrafine size. The general preparation of ultrafine-sized (<10 nm) HECs (nitrides, oxides, sulfides, and phosphates) anchored on porous carbon composites is realized. They are demonstrated by combining advanced characterization technologies with theoretical computations. Ultrafine-sized high entropy sulfides-MnFeCoCuSnMo/porous carbon (HES-MnFeCoCuSnMo/PC) as representative anodes exhibit excellent sodium-ion storage kinetics and capacities (a high rating capacity of 278 mAh g-1 at 10 A g-1 for full cell and a high cycling capacity of 281 mAh g-1 at 20 A g-1 after 6000 cycles for half cell) due to the combining advantages of high entropy effect, ultrafine size, and PC incorporation. Our work provides a new opportunity for designing and fabricating ultrafine-sized HECs.

Study on Preparation and Humidity-Control Capabilities of Vermiculite/Poly(sodium Acrylate-acrylamide) Humidity Controlling Composite.

This paper focuses on the preparation and evaluation of a novel humidity-control material, vermiculite/(sodium polyacrylate(AA)-acrylamide(AM)), using inverse suspension polymerization. Acrylic acid and acrylamide were introduced into the interlayer of modified vermiculite during the polymerization process, leading to the formation of a strong association with the modified vermiculite. The addition of vermiculite increased the specific surface area and pore volume of the composites. To investigate the moisture absorption and desorption properties of the composites, an orthogonal experiment and single-factor experiment were conducted to analyze the impacts of vermiculite content, neutralization degree, and the mass ratio of AA to AM. According to the control experiment, the addition of vermiculite was found to enhance the pore structure and surface morphology of the composite material, surpassing both vermiculite and PAA-AM copolymer in terms of humidity control capacity and rate. The optimal preparation conditions were identified as follows: vermiculite mass fraction of 4 wt%, a neutralization degree of 90%, and mAA:mAM = 4:1. The moisture absorption rate and moisture release rate of the composite material prepared under these conditions are 1.285 g/g and 1.172 g/g. The humidity control process of the composite material is governed by pseudo second-order kinetics, which encompasses the complete adsorption process. These results indicate that the vermiculite/PAA-AM composite humidity control material has excellent humidity control performance and is a simple and efficient humidity control method.

Exploring sparsity in graph transformers.

Graph Transformers (GTs) have achieved impressive results on various graph-related tasks. However, the huge computational cost of GTs hinders their deployment and application, especially in resource-constrained environments. Therefore, in this paper, we explore the feasibility of sparsifying GTs, a significant yet under-explored topic. We first discuss the redundancy of GTs based on the characteristics of existing GT models, and then propose a comprehensive Graph Transformer SParsification (GTSP) framework that helps to reduce the computational complexity of GTs from four dimensions: the input graph data, attention heads, model layers, and model weights. Specifically, GTSP designs differentiable masks for each individual compressible component, enabling effective end-to-end pruning. We examine our GTSP through extensive experiments on prominent GTs, including GraphTrans, Graphormer, and GraphGPS. The experimental results demonstrate that GTSP effectively reduces computational costs, with only marginal decreases in accuracy or, in some instances, even improvements. For example, GTSP results in a 30% reduction in Floating Point Operations while contributing to a 1.8% increase in Area Under the Curve accuracy on the OGBG-HIV dataset. Furthermore, we provide several insights on the characteristics of attention heads and the behavior of attention mechanisms, all of which have immense potential to inspire future research endeavors in this domain. Our code is available at https://github.com/LiuChuang0059/GTSP.

Accelerating the Phase Formation Kinetics of Alluaudite Sodium Iron Sulfate Cathodes via Ultrafast Thermal Shock.

Alluaudite sodium iron sulfate (NFS) exhibits great potential for use in sodium-ion battery cathodes due to its elevated operating potential and abundant element reserves. However, conventional solid-state methods demonstrate a low heating/cooling rate and sluggish reaction kinetics, requiring a long thermal treatment to effectively fabricate NFS cathodes. Herein, we propose a thermal shock (TS) strategy to synthesize alluaudite sodium iron sulfate cathodes using either hydrous or anhydrous raw materials. The analysis of the phase formation process reveals that TS treatment can significantly facilitate the removal of crystal water and decomposition of the intermediate phase Na2Fe(SO4)2 in the hydrous precursor. In the case of the anhydrous precursor, the kinetics of the combination reaction between Na2SO4 and FeSO4 can be also accelerated by TS treatment. Consequently, pure NFS phase formation can be completed after a substantially shorter time of post-sintering, thereby saving significant time and energy. The TS-treated NFS cathode derived from hydrous precursor exhibits higher retention after 200 cycles at 1C and better rate capability than the counterpart prepared by conventional long-term tube furnace sintering, demonstrating the great potential of this novel strategy.

Towards a better negative sampling strategy for dynamic graphs.

As dynamic graphs have become indispensable in numerous fields due to their capacity to represent evolving relationships over time, there has been a concomitant increase in the development of Temporal Graph Neural Networks (TGNNs). When training TGNNs for dynamic graph link prediction, the commonly used negative sampling method often produces starkly contrasting samples, which can lead the model to overfit these pronounced differences and compromise its ability to generalize effectively to new data. To address this challenge, we introduce an innovative negative sampling approach named Enhanced Negative Sampling (ENS). This strategy takes into account two pervasive traits observed in dynamic graphs: (1) Historical dependence, indicating that nodes frequently reestablish connections they held in the past, and (2) Temporal proximity preference, which posits that nodes are more inclined to connect with those they have recently interacted with. Specifically, our technique employs a designed scheduling function to strategically control the progression of difficulty of the negative samples throughout the training. This ensures that the training progresses in a balanced manner, becoming incrementally challenging, and thereby enhancing TGNNs' proficiency in predicting links within dynamic graphs. In our empirical evaluation across multiple datasets, we discerned that our ENS, when integrated as a modular component, notably augments the performance of four SOTA baselines. Additionally, we further investigated the applicability of ENS in handling dynamic graphs of varied attributes. Our code is available at https://github.com/qqaazxddrr/ENS.

Optimizing potassium polysulfides for high performance potassium-sulfur batteries.

Potassium-sulfur batteries attract tremendous attention as high-energy and low-cost energy storage system, but achieving high utilization and long-term cycling of sulfur remains challenging. Here we show a strategy of optimizing potassium polysulfides for building high-performance potassium-sulfur batteries. We design the composite of tungsten single atom and tungsten carbide possessing potassium polysulfide migration/conversion bi-functionality by theoretical screening. We create two ligand environments for tungsten in the metal-organic framework, which respectively transmute into tungsten single atom and tungsten carbide nanocrystals during pyrolysis. Tungsten carbide provide catalytic sites for potassium polysulfides conversion, while tungsten single atoms facilitate sulfides migration thereby significantly alleviating the insulating sulfides accumulation and the associated catalytic poisoning. Resultantly, highly efficient potassium-sulfur electrochemistry is achieved under high-rate and long-cycling conditions. The batteries deliver 89.8% sulfur utilization (1504 mAh g-1), superior rate capability (1059 mAh g-1 at 1675 mA g-1) and long lifespan of 200 cycles at 25 °C. These advances enlighten direction for future KSBs development.

Stabilization of LiCoO2 Cathodes in High Voltage Lithium Metal Batteries Through 2-(Trifluoromethyl)Benzamide (2-TFMBA) Electrolyte Additives.

Increasing the charging cutoff voltage of LiCoO2 to 4.6 V is significant for enhancing battery density. However, the practical application of Li‖LiCoO2 batteries with a 4.6 V cutoff voltage faces significant impediments due to the detrimental changes under high voltage. This study presents a novel bifunctional electrolyte additive, 2-(trifluoromethyl)benzamide (2-TFMBA), which is employed to establish a stable and dense cathode-electrolyte interface (CEI). Characterization results reveal that an optimized CEI is achieved through the synergistic effects of the amide groups and trifluoromethyl groups within 2-TFMBA. The resulting CEI not only enhances the structural stability of LiCoO2 but also serves as a high-speed lithium-ion conduction channel, which expedites the insertion and extraction of lithium ions. The Li‖LiCoO2 batteries with 0.5 wt% 2-TFMBA achieves an 84.7% capacity retention rate after enduring 300 cycles at a current rate of 1 C, under a cut-off voltage of 4.6 V. This study provides valuable strategic insights into the stabilization of cathode materials in high-voltage batteries.

Overexpression of Homeobox A1 Relieves Ovalbumin-Induced Asthma in Mice and Is Associated with Blocking of the NF-κB Signaling Pathway.

Homeobox A1 (HOXA1) is a protein coding gene involved in regulating immunity signaling. This study aims to explore the function and mechanism of HOXA1 in asthma. An asthma mouse model was established via ovalbumin (OVA) induction. Airway hyperresponsiveness was evaluated by the value of pause enhancement (Penh). Inflammatory cells in bronchoalveolar lavage fluid (BALF) were detected by Trypan blue and Wright staining. The pathological morphology of lung tissues was assessed by H&E staining. The IgE and inflammatory biomarkers (IL-1ß, IL-6, IL-17, and TNF-α) in BALF and lung tissues were measured by ELISA. Western blot was performed to detect the expression of NF-κB pathway-related proteins. HOXA1 was down-regulated in OVA-induced asthmatic mice. Overexpression of HOXA1 decreased Penh and relieved pathological injury of lung tissues in OVA-induced mice. Overexpression of HOXA1 also reduced the numbers of total cells, leukocytes, eosinophils, neutrophils, macrophages, and lymphocytes, as well as the levels of IgE, IL-1ß, IL-6, IL-17, and TNF-α in BALF of OVA-induced mice. The inflammatory biomarkers were also decreased in lung tissues by HOXA1 overexpression. In addition, HOXA1 overexpression blocked the NF-κB signaling pathway in OVA-induced mice. Overexpression of HOXA1 relieved OVA-induced asthma in female mice, which is associated with the blocking of the NF-κB signaling pathway.

Dynamic real-time forecasting technique for reclaimed water volumes in urban river environmental management.

In recent years, the utilization of wastewater recycling as an alternative water source has gained significant traction in addressing urban water shortages. Accurate prediction of wastewater quantity is paramount for effective urban river water resource management. There is an urgent need to develop advanced forecasting technologies to further enhance the accuracy and efficiency of water quantity predictions. Decomposition ensemble models have shown excellent predictive capabilities but are challenged by boundary effects when decomposing the original data sequence. To address this, a rolling forecast decomposition ensemble scheme was developed. It involves using a machine learning (ML) model for prediction and progressively integrating prediction outcomes into the original sequence using complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Long short-term memory (LSTM) is then applied for sub-signal prediction and ensemble. The ML-CEEMDAN-LSTM model was introduced for wastewater quantity prediction, compared with non-decomposed ML models, CEEMDAN-based LSTM models, and ML-CEEMDAN-based LSTM models. Three ML algorithms-linear regression (LR), gradient boosting regression (GBR), and LSTM-were examined, using real-time prediction data and historical monitoring data, with historical data selected using the decision tree method. The study used daily water volumes data from two reclaimed water plants, CH and WQ, in Beijing. The results indicate that (1) ML models varied in their selection of real-time factors, with LR performing best among ML models during testing; (2) the ML-CEEMDAN-LSTM model consistently outperformed ML models; (3) the ML-CEEMDAN-LSTM hybrid model performed better than the CEEMDAN-LSTM model across different seasons. This study offers a reliable and accurate approach for reclaimed water volumes forecasting, critical for effective water environment management.

Rapid High-Temperature Liquid Shock Synthesis of High-Entropy Alloys for Hydrogen Evolution Reaction.

High-entropy-alloy nanoparticles (HEA-NPs) show great potential as electrocatalysts for water splitting, fuel cells, CO2 conversion, etc. However, fine-tuning the surface, morphology, structure, and crystal phase of HEA remains a great challenge. Here, the high-temperature liquid shock (HTLS) technique is applied to produce HEA-NPs, e.g., PtCoNiRuIr HEA-NPs, with tunable elemental components, ultrafine particle size, controlled crystal phases, and lattice strains. HTLS directly applied Joule heating on the liquid mixture of metal precursors, capping agents, and reducing agents, which is feasible for controlling the morphology and structure such as the atomic arrangement of the resulting products, thereby facilitating the rationally designed nanocatalysts. Impressively, the as-obtained PtCoNiRuIr HEA-NPs delivered superior activity and long-term stability for the hydrogen evolution reaction (HER), with low overpotentials at 10 mA cm-2 and 1 A cm-2 of only 18 and 408 mV, respectively, and 10000 CV stable cycles in 0.5 M H2SO4. Furthermore, in the near future, by combining the HTLS method with artificial intelligence (AI) and theoretical calculations, it is promising to provide an advanced platform for the high-throughput synthesis of HEA nanocatalysts with optimized performance for various energy applications, which is of great significance for achieving a carbon-neutral society with an effective and environmentally friendly energy system.

In situ Implanting 3D Carbon Network Reinforced Zinc Composite by Powder Metallurgy for Highly Reversible Zn-based Battery Anodes.

Aqueous Zn-based batteries have emerged as compelling candidates for grid-scale energy storage, owing to their intrinsic safety, remarkable theoretical energy density and cost-effectiveness. Nonetheless, the dendrite formation, side reactions, and corrosion on anode have overshadowed their practical applications. Herein, we present an in situ grown carbon network reinforcing Zn matrix anode prepared by powder metallurgy. This carbon network provides an uninterrupted internal electron transport pathway and optimize the surface electric field distribution, thereby enabling highly reversible Zn deposition. Consequently, symmetrical cells demonstrate impressive stability, running for over 880 h with a low voltage hysteresis (≈32 mV). Furthermore, this Zn matrix composite anode exhibits enhanced performance in both the aqueous Zn-ion and the Zn-air batteries. Notably, Zn//MnO2 cells display superior rate capabilities, while Zn-air batteries deliver high power density and impressive Zn utilization rate (84.9 %). This work provides a new idea of powder metallurgy method for modified Zn anodes, showcasing potential for large-scale production.

Review of Carbon Support Coordination Environments for Single Metal Atom Electrocatalysts (SACS).

This topical review focuses on the distinct role of carbon support coordination environment of single-atom catalysts (SACs) for electrocatalysis. The article begins with an overview of atomic coordination configurations in SACs, including a discussion of the advanced characterization techniques and simulation used for understanding the active sites. A summary of key electrocatalysis applications is then provided. These processes are oxygen reduction reaction (ORR), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), nitrogen reduction reaction (NRR), and carbon dioxide reduction reaction (CO2 RR). The review then shifts to modulation of the metal atom-carbon coordination environments, focusing on nitrogen and other non-metal coordination through modulation at the first coordination shell and modulation in the second and higher coordination shells. Representative case studies are provided, starting with the classic four-nitrogen-coordinated single metal atom (MN4 ) based SACs. Bimetallic coordination models including homo-paired and hetero-paired active sites are also discussed, being categorized as emerging approaches. The theme of the discussions is the correlation between synthesis methods for selective doping, the carbon structure-electron configuration changes associated with the doping, the analytical techniques used to ascertain these changes, and the resultant electrocatalysis performance. Critical unanswered questions as well as promising underexplored research directions are identified.

The volume and structural covariance network of thalamic nuclei in patients with Wilson's disease: an investigation of the association with neurological impairment.

OBJECTIVE: This study aimed to examine the volumes of thalamic nuclei and the intrinsic thalamic network in patients with Wilson's disease (WDs), and to explore the correlation between these volumes and the severity of neurological symptoms. METHODS: A total of 61 WDs and 33 healthy controls (HCs) were included in the study. The volumes of 25 bilateral thalamic nuclei were measured using structural imaging analysis with Freesurfer, and the intrinsic thalamic network was evaluated through structural covariance network (SCN) analysis. RESULTS: The results indicated that multiple thalamic nuclei were smaller in WDs compared to HCs, including mediodorsal medial magnocellular (MDm), anterior ventral (AV), central median (CeM), centromedian (CM), lateral geniculate (LGN), limitans-suprageniculate (L-Sg), reuniens-medial ventral (MV), paracentral (Pc), parafascicular (Pf), paratenial (Pt), pulvinar anterior (PuA), pulvinar inferior (PuI), pulvinar medial (PuM), ventral anterior (VA), ventral anterior magnocellular (VAmc), ventral lateral anterior (VLa), ventral lateral posterior (VLp), ventromedial (VM), ventral posterolateral (VPL), and right middle dorsal intralaminar (MDI). The study also found a negative correlation between the UWDRS scores and the volume of the right MDm. The intrinsic thalamic network analysis showed abnormal topological properties in WDs, including increased mean local efficiency, modularity, normalized clustering coefficient, small-world index, and characteristic path length, and a corresponding decrease in mean node betweenness centrality. WDs with cerebral involvement had a lower modularity compared to HCs. CONCLUSIONS: The findings suggest that the majority of thalamic nuclei in WDs exhibit significant volume reduction, and the atrophy of the right MDm is closely related to the severity of neurological symptoms. The intrinsic thalamic network in WDs demonstrated abnormal topological properties, indicating a close relationship with neurological impairment.

Room-Temperature Salt Template Synthesis of Nitrogen-Doped 3D Porous Carbon for Fast Metal-Ion Storage.

The water-soluble salt-template technique holds great promise for fabricating 3D porous materials. However, an equipment-free and pore-size controllable synthetic approach employing salt-template precursors at room temperature has remained unexplored. Herein, we introduce a green room-temperature antisolvent precipitation strategy for creating salt-template self-assembly precursors to universally produce 3D porous materials with controllable pore size. Through a combination of theoretical simulations and advanced characterization techniques, we unveil the antisolvent precipitation mechanism and provide guidelines for selecting raw materials and controlling the size of precipitated salt. Following the calcination and washing steps, we achieve large-scale and universal production of 3D porous materials and the recycling of the salt templates and antisolvents. The optimized nitrogen-doped 3D porous carbon (N-3DPC) materials demonstrate distinctive structural benefits, facilitating a high capacity for potassium-ion storage along with exceptional reversibility. This is further supported by in situ electrochemical impedance spectra, in situ Raman spectroscopy, and theoretical calculations. The anode shows a high rate capacity of 181 mAh g-1 at 4 A g-1 in the full cell. This study addresses the knowledge gap concerning the room-temperature synthesis of salt-template self-assembly precursors for the large-scale production of porous materials, thereby expanding their potential applications for electrochemical energy conversion and storage.

Cell wall-localized Bt protein endows rice high resistance to Lepidoptera pests.

BACKGROUND: The commercialized Bt (Bacillus thuringiensis) crops accumulate Bt protein within cells, but the intracellular interactions of foreign protein with endogenous protein inevitably result in large or small unintended effects. In this study, the Bt gene Cry1Ca was linked with the sequences of extracellular secretion signal peptide and carbohydrate binding module 11 to constitute a fusion gene SP-Cry1Ca-CBM11, and the fusion gene driven by constitutive promoters was used for secreting and anchoring onto the cell wall to minimize unintended effects. RESULTS: The transient expression in tobacco leaves demonstrated that the fusion protein was anchored on cell walls. The Cry1Ca contents of five homozygous rice transformants of single-copy insertion were different and descended in the order leaf > root > stem. The maximum content of Cry1Ca was 17.55 µg g-1 in leaves of transformant 21H037. The bioassay results revealed that the transformants exhibited high resistance to lepidopteran pests. The corrected mortality of pink stem borer (Sesamia inferens) and striped stem borer (Chilo suppressalis) ranged from 96.33% to 100%, and from 83.32% to 100%, respectively, and the corrected mortality of rice leaf roller (Cnaphalocrocis medinalis) was 92.53%. Besides, the agronomic traits of the five transformants were normal and similar to that of the recipient, and the transformants were highly resistant to glyphosate at the germination and seedling stages. CONCLUSION: The fusion Bt protein was accumulated on cell walls and endowed the rice with high resistance to lepidopteran pests without unintended effects in agronomic traits. © 2023 Society of Chemical Industry.