Interface Dipole Management of D-A-Type Molecules for Efficient Perovskite Solar Cells.

Interfacial engineering of perovskite films has been the main strategies in improving the efficiency and stability of perovskite solar cells (PSCs). In this study, three new donor-acceptor (D-A)-type interfacial dipole (DAID) molecules with hole-transporting and different anchoring units are designed and employed in PSCs. The formation of interface dipoles by the DAID molecules on the perovskite film can efficiently modulate the energy level alignment, improve charge extraction, and reduce non-radiative recombination. Among the three DAID molecules, TPA-BAM with amide group exhibits the best chemical and optoelectrical properties, achieving a champion PCE of 25.29% with the enhanced open-circuit voltage of 1.174 V and fill factor of 84.34%, due to the reduced defect density and improved interfacial hole extraction. Meanwhile, the operational stability of the unencapsulated device has been significantly improved. Our study provides a prospect for rationalized screening of interfacial dipole materials for efficient and stable PSCs.

[Developmental toxicity of Cry1Ab protein in the embryonic stem-cell model].

OBJECTIVE: To evaluate the developmental toxicity of Cry1Ab protein by studying its effects on cell proliferation and differentiation ability using a developmental toxicity assessment model based on embryonic stem-cell. METHODS: Cry1Ab protein was tested in seven dose groups (31.25, 62.50, 125.00, 250.00, 320.00, 1 000.00, and 2 000.00 µg/L) on mouse embryonic stem cells D3 (ES-D3) and 3T3 mouse fibroblast cells, with 5-fluorouracil (5-FU) used as the positive control and phosphate buffer saline (PBS) as the solvent control. Cell viability was detected by CCK-8 assay to calculate the 50% inhibitory concentration (IC50) of the test substance for different cells. Additionally, Cry1Ab protein was tested in five dose groups (125.00, 250.00, 320.00, 1 000.00, and 2 000.00 µg/L) on ES-D3 cells, with PBS as the solvent control and 5-FU used for model validation. After cell treatment, cardiac differentiation was induced using the embryonic bodies (EBs) culture method. The growth of EBs was observed under a microscope, and their diameters on the third and fifth days were measured. The proportion of EBs differentiating into beating cardiomyocytes was recorded, and the 50% inhibition concentration of differentiation (ID50) was calculated. Based on a developmental toxicity discrimination function, the developmental toxicity of the test substances was classified. Furthermore, at the end of the culture period, mRNA expression levels of cardiac differentiation-related markers (Oct3/4, GATA-4, Nkx2.5, and ß-MHC) were quantitatively detected using real-time quantitative polymerase chain reaction (qPCR) in the collected EBs samples. RESULTS: The IC50 of 5-FU was determined as 46.37 µg/L in 3T3 cells and 32.67 µg/L in ES-D3 cells, while the ID50 in ES-D3 cells was 21.28 µg/L. According to the discrimination function results, 5-FU was classified as a strong embryotoxic substance. There were no statistically significant differences in cell viability between different concentrations of Cry1Ab protein treatment groups and the control group in both 3T3 cells and ES-D3 cells (P>0.05). Moreover, there were no statistically significant differences in the diameter of EBs on the third and fifth days, as well as their morphology, between the Cry1Ab protein treatment groups and the control group (P>0.05). The cardiac differentiation rate showed no statistically significant differences between different concentrations of Cry1Ab protein treatment groups and the control group (P>0.05). 5-FU significantly reduced the mRNA expression levels of ß-MHC, Nkx2.5, and GATA-4 (P < 0.05), showing a dose-dependent trend (P < 0.05), while the mRNA expression levels of the pluripotency-associated marker Oct3/4 exhibited an increasing trend (P < 0.05). However, there were no statistically significant differences in the mRNA expression levels of mature cardiac marker ß-MHC, early cardiac differentiation marker Nkx2.5 and GATA-4, and pluripotency-associated marker Oct3/4 between the Cry1Ab protein treatment groups and the control group (P>0.05). CONCLUSION: No developmental toxicity of Cry1Ab protein at concentrations ranging from 31.25 to 2 000.00 µg/L was observed in this experimental model.

Universal inter-molecular radical transfer reactions on metal surfaces.

On-surface synthesis provides tools to prepare low-dimensional supramolecular structures. Traditionally, reactive radicals are a class of single-electron species, serving as exceptional electron-withdrawing groups. On metal surfaces, however, such species are affected by conduction band screening effects that may even quench their unpaired electron characteristics. As a result, radicals are expected to be less active, and reactions catalyzed by surface-stabilized radicals are rarely reported. Herein, we describe a class of inter-molecular radical transfer reactions on metal surfaces. With the assistance of aryl halide precursors, the coupling of terminal alkynes is steered from non-dehydrogenated to dehydrogenated products, resulting in alkynyl-Ag-alkynyl bonds. Dehalogenated molecules are fully passivated by detached hydrogen atoms. The reaction mechanism is unraveled by various surface-sensitive technologies and density functional theory calculations. Moreover, we reveal the universality of this mechanism on metal surfaces. Our studies enrich the on-surface synthesis toolbox and develop a pathway for producing low-dimensional organic materials.

Na3K6(CO3)3(NO3)2X·6H2O (X = NO3, Cl, Br): Exploring High-Performance UV Birefringent Crystals Induced by Coplanar π-Conjugated CO3 and NO3 Groups.

Planar π-conjugated groups, like CO3, NO3, and BO3 triangles, are ideal functional units for designing birefringent materials due to their large optical anisotropy and wide band gap. The key point for designing birefringent crystals is to select appropriate functional building blocks (FBBs) and the proper arrangement mode. It is well known that the substitution strategy has proven to be a promising and accessible approach. In this work, alkali metals were chosen to regulate and control two different π-conjugated groups, CO3 and NO3, to build new compounds with large birefringence. Subsequently, three new compounds, Na3K6(CO3)3(NO3)2X·6H2O (X = NO3, Cl, Br), were successfully synthesized using the hydrothermal method. The aliovalent substitution between the [NO3]- anionic group and halogen anions [Cl]-/[Br]- has been achieved in these compounds. Na3K6(CO3)3(NO3)2X·6H2O feature the well-coplanar CO3 and NO3 groups in their crystal structure. This coplanar arrangement mode may effectively enhance the anisotropic polarizability of Na3K6(CO3)3(NO3)2X·6H2O. And their experimental birefringence can reach 0.094-0.131 at 546 nm. Diffuse reflectance spectra demonstrate that these compounds exhibit short ultraviolet (UV) absorption edges of ∼235 nm. Meanwhile, Na3K6(CO3)3(NO3)2X·6H2O also have an easily grown capacity under facile conditions. This work not only reports three new potential UV birefringent crystals but also provides a strategy to make the π-conjugated MO3 group coplanar.

A MEMS Electrochemical Angular Accelerometer with Silicon-Based Four-Electrode Structure.

This paper presents a MEMS electrochemical angular accelerometer with a silicon-based four-electrode structure, which was made of thousands of interconnected microchannels for electrolyte flow, anodes uniformly coated on structure surfaces and cathodes located on the sidewalls of flow holes. From the perspective of device fabrication, in this study, the previously reported multi-piece assembly was simplified into single-piece integrative manufacturing, effectively addressing the problems of complex assembly and manual alignment. From the perspective of the sensitive structure, in this study, the silicon-based four-electrode structure featuring with complete insulation layers between anodes and cathodes can enable fast electrochemical reactions with improved sensitivities. Numerical simulations were conducted to optimize the geometrical parameters of the silicon-based four-electrode structure, where increases in fluid resistance and cathode area were found to expand working bandwidths and improve device sensitivity, respectively. Then, the silicon-based four-electrode structure was fabricated by conventional MEMS processes, mainly composed of wafer-level bonding and wafer-level etching. As to device characterization, the MEMS electrochemical angular accelerometer with the silicon-based four-electrode structure exhibited a maximum sensitivity of 1458 V/(rad/s2) at 0.01 Hz and a minimum noise level of -164 dB at 1 Hz. Compared with previously reported electrochemical angular accelerometers, the angular accelerometer developed in this study offered higher sensitivities and lower noise levels, indicating strong potential for applications in the field of rotational seismology.

A resonant high-pressure microsensor based on a composite pressure-sensitive mechanism of diaphragm bending and volume compression.

In this paper, a composite pressure-sensitive mechanism combining diaphragm bending and volume compression was developed for resonant pressure microsensors to achieve high-pressure measurements with excellent accuracy. The composite mechanism was explained, and the sensor structure was designed based on theoretical analysis and finite element simulation. An all-silicon resonant high-pressure microsensor with multiple miniaturized cavities and dual resonators was developed, where dual resonators positioned in two resonant cavities with suitably different widths are used to perform opposite characteristics in pressure and the same characteristics at different temperatures, which can improve pressure sensitivities and realize temperature self-compensation by differential frequency output. The microsensor was fabricated by microfabrication, and the experimental results showed that the sensor had an accuracy of ±0.015% full scale (FS) in a pressure range of 0.1~100 MPa and a temperature range of -10~50 °C. The pressure sensitivity of the differential frequency was 261.10 Hz/MPa (~2523 ppm/MPa) at a temperature of 20 °C, and the temperature sensitivities of the dual resonators were -1.54 Hz/°C (~-14.5 ppm/°C) and -1.57 Hz/°C (~-15.6 ppm/°C) at a pressure of 2 MPa. The differential output had an outstanding stability within ±0.02 Hz under constant temperature and pressure. Thus, this research provides a convenient solution for high-pressure measurements because of its advantages, namely, large range, excellent accuracy and stability.

Monitoring Memory B Cells by Next-Generation ImmunoSpot® Provides Insights into Humoral Immunity that Measurements of Circulating Antibodies Do Not Reveal.

Memory B cells (Bmem) provide the second wall of adaptive humoral host defense upon specific antigen rechallenge when the first wall, consisting of preformed antibodies originating from a preceding antibody response, fails. This is the case, as recently experienced with SARS-CoV-2 infections and previously with seasonal influenza, when levels of neutralizing antibodies decline or when variant viruses arise that evade such. While in these instances, reinfection can occur, in both scenarios, the rapid engagement of preexisting Bmem into the recall response can still confer immune protection. Bmem are known to play a critical role in host defense, yet their assessment has not become part of the standard immune monitoring repertoire. Here we describe a new generation of B cell ELISPOT/FluoroSpot (collectively ImmunoSpot®) approaches suited to dissect, at single-cell resolution, the Bmem repertoire ex vivo, revealing its immunoglobulin class/subclass utilization, and its affinity distribution for the original, and for variant viruses/antigens. Because such comprehensive B cell ImmunoSpot® tests can be performed with minimal cell material, are scalable, and robust, they promise to be well-suited for routine immune monitoring.

Fulvic acid alleviates the stress of low nitrogen on maize by promoting root development and nitrogen metabolism.

The potential of fulvic acid (FA) to improve plant growth has been acknowledged, but its effect on plant growth and nutrient uptake under nutrient stress remains unclear. This study investigated the effects of different FA application rates on maize growth and nitrogen utilization under low nitrogen stress. The results showed that under low nitrogen stress, FA significantly stimulated maize growth, particularly root development, biomass, and nitrogen content. The enhanced activity levels of key enzymes in nitrogen metabolism were observed, along with differential gene expression in maize, which enriched nitrogen metabolism, amino acid metabolism and plant hormone metabolism. The application of FA regulated the hormones' level, reduced abscisic acid content in leaves and Me-JA content in roots, and increased auxin and zeatin ribose content in leaves. This study concludes that, by promoting root development, nitrogen metabolism, and hormone metabolism, an appropriate concentration of FA can enhance plant tolerance to low nitrogen conditions and improve nitrogen use efficiency.

Self-Polymerized Spiro-Type Interfacial Molecule toward Efficient and Stable Perovskite Solar Cells.

In the pursuit of highly efficient perovskite solar cells, spiro-OMeTAD has demonstrated recorded power conversion efficiencies (PCEs), however, the stability issue remains one of the bottlenecks constraining its commercial development. In this study, we successfully synthesize a novel self-polymerized spiro-type interfacial molecule, termed v-spiro. The linearly arranged molecule exhibits stronger intermolecular interactions and higher intrinsic hole mobility compared to spiro-OMeTAD. Importantly, the vinyl groups in v-spiro enable in situ polymerization, forming a polymeric protective layer on the perovskite film surface, which proves highly effective in suppressing moisture degradation and ion migration. Utilizing these advantages, poly-v-spiro-based device achieves an outstanding efficiency of 24.54 %, with an enhanced open-circuit voltage of 1.173 V and a fill factor of 81.11 %, owing to the reduced defect density, energy level alignment and efficient interfacial hole extraction. Furthermore, the operational stability of unencapsulated devices is significantly enhanced, maintaining initial efficiencies above 90 % even after 2000 hours under approximately 60 % humidity or 1250 hours under continuous AM 1.5G sunlight exposure. This work presents a comprehensive approach to achieving both high efficiency and long-term stability in PSCs through innovative interfacial design.

Segmentation, feature extraction and classification of leukocytes leveraging neural networks, a comparative study.

The gold standard of leukocyte differentiation is a manual examination of blood smears, which is not only time and labor intensive but also susceptible to human error. As to automatic classification, there is still no comparative study of cell segmentation, feature extraction, and cell classification, where a variety of machine and deep learning models are compared with home-developed approaches. In this study, both traditional machine learning of K-means clustering versus deep learning of U-Net, U-Net + ResNet18, and U-Net + ResNet34 were used for cell segmentation, producing segmentation accuracies of 94.36% versus 99.17% for the dataset of CellaVision and 93.20% versus 98.75% for the dataset of BCCD, confirming that deep learning produces higher performance than traditional machine learning in leukocyte classification. In addition, a series of deep-learning approaches, including AlexNet, VGG16, and ResNet18, was adopted to conduct feature extraction and cell classification of leukocytes, producing classification accuracies of 91.31%, 97.83%, and 100% of CellaVision as well as 81.18%, 91.64% and 97.82% of BCCD, confirming the capability of the increased deepness of neural networks in leukocyte classification. As to the demonstrations, this study further conducted cell-type classification of ALL-IDB2 and PCB-HBC datasets, producing high accuracies of 100% and 98.49% among all literature, validating the deep learning model used in this study.

AX·(H2SeO3)n (A = K, Cs; X = Cl, Br; n = 1, 2): A Series of Ionic Cocrystals as Promising UV Birefringent Materials with Large Birefringence and Wide Band Gap.

The design and syntheses of new birefringent crystals will be of great importance in commercial applications and materials science. A series of ultraviolet (UV) birefringent crystals, AX·(H2SeO3)n (A = K, Cs; X = Cl, Br; n = 1, 2), with large sizes up to 23 × 6 × 3 mm3, was successfully synthesized by simple aqueous solution method. These four compounds belong to three different space groups. Isomorphic KCl·(H2SeO3)2 and CsCl·(H2SeO3)2 crystallize in the P1¯ space group, while CsBr·(H2SeO3)2 and CsCl·H2SeO3 crystallize in the P21/m and P21/c space groups, respectively. They exhibit cocrystal structures composed of [2(H2SeO3)]∞ and [AX]∞ frameworks, ingeniously inheriting the large optical anisotropy of selenite and the wide band gap of alkali metal halide. And it proves that these compounds indeed possess large birefringence (0.1-0.17 at 532 nm) and short UV cutoff edges (227-239 nm), achieving a balance of optical properties. This research affords a simple and viable strategy for the design and syntheses of new UV birefringent crystals. Besides, it is also found that the n value and ionic size (A and X ions) have important influences on the crystal structures and optical properties of AX·(H2SeO3)n. And this will promote further understanding of the alkali metal halide selenite family.

Electrical micro flow cytometry with LSTM and its application in leukocyte differential.

This paper developed an electrical micro flow cytometry to realize leukocyte differentials leveraging a constrictional microchannel and a deep neural network. Firstly, purified granulocytes, lymphocytes or monocytes traveled through the constrictional microchannel with a cross-sectional area marginally larger than individual cells and produced large impedance variations by blocking focused electric field lines. By optimizing key elements (e.g., normalization, learning rate, batch size and neuron number) of the recurrent neural network (RNN), electrical results of purified leukocytes were analyzed to establish a leukocyte differential system with a classification accuracy of 95.2%. Then the leukocyte mixtures were forced to travel through the same constrictional microchannel, producing mixed impedance profiles which were classified into granulocytes, lymphocytes and monocytes based on the aforementioned differential system. As to the classification results, two leukocyte mixtures from the same donor were processed, producing comparable classification results, which were 57% versus 59% of granulocytes, 37% versus 34% of lymphocytes and 6% versus 7% of monocytes. These results validated the established classification system based on the constrictional microchannel and the recurrent neural network, providing a new perspective of differentiating white blood cells by electrical flow cytometry.

Advance of microfluidic flow cytometry enabling high-throughput characterization of single-cell electrical and structural properties.

This paper reported a micro flow cytometer capable of high-throughput characterization of single-cell electrical and structural features based on constrictional microchannels and deep neural networks. When single cells traveled through microchannels with constricted cross-sectional areas, they effectively blocked concentrated electric field lines, producing large impedance variations. Meanwhile, the traveling cells were confined within the cross-sectional areas of the constrictional microchannels, enabling the capture of high-quality images without losing focuses. Then single-cell features from impedance profiles and optical images were extracted from customized recurrent and convolution networks (RNN and CNN), which were further fused for cell-type classification based on support vector machines (SVM). As a demonstration, two leukemia cell lines (e.g., HL60 vs. Jurkat) were analyzed, producing high-classification accuracies of 99.3% based on electrical features extracted from Long Short-Term Memory (LSTM) of RNN, 96.7% based on structural features extracted from Resnet18 of CNN and 100.0% based on combined features enabled by SVM. The microfluidic flow cytometry developed in this study may provide a new perspective for the field of single-cell analysis.

Leukocyte differential based on an imaging and impedance flow cytometry of microfluidics coupled with deep neural networks.

The differential of leukocytes functions as the first indicator in clinical examinations. However, microscopic examinations suffered from key limitations of low throughputs in classifying leukocytes while commercially available hematology analyzers failed to provide quantitative accuracies in leukocyte differentials. A home-developed imaging and impedance flow cytometry of microfluidics was used to capture fluorescent images and impedance variations of single cells traveling through constrictional microchannels. Convolutional and recurrent neural networks were adopted for data processing and feature extractions, which were then fused by a support vector machine to realize the four-part differential of leukocytes. The classification accuracies of the four-part leukocyte differential were quantified as 95.4% based on fluorescent images plus the convolutional neural network, 90.3% based on impedance variations plus the recurrent neural network, and 99.3% on the basis of fluorescent images, impedance variations, and deep neural networks. Based on single-cell fluorescent imaging and impedance variations coupled with deep neural networks, the four-part leukocyte differential can be realized with almost 100% accuracy.

Rational Design of the Alkali Metal Sn-Based Mixed Halides with Large Birefringence and Wide Transparent Range.

Birefringent materials are widely used in various advanced optical systems, owing to their vital role in creating and controlling polarized light. Currently, Sn2+-based compounds containing stereochemically active lone-pair (SCALP) cations are extensively investigated and considered as one class of promising birefringent materials. To solve the problem of relatively narrow bandgap of Sn2+-based compounds, alkali metals and multiple halogens are introduced to widen the bandgap during the research. Based on this strategy, four new Sn2+-based halides, A2Sn2F5Cl and ASnFCl2 (A = Rb and Cs), with large birefringence, short ultraviolet (UV) cutoff edge, and wide transparent range are successfully found. The birefringences of A2Sn2F5Cl (A = Rb and Cs) are 0.31 and 0.28 at 532 nm, respectively, which are among the largest in Sn-based halide family. Remarkably, A2Sn2F5Cl possess relatively shorter UV cutoff edge (<300 nm) and broad infrared (IR) transparent range (up to 16.6 µm), so they can become promising candidates as birefringent materials applied in both UV and IR regions. In addition, a comprehensive analysis on crystal structures and structure-property relationship of metal Sn2+-based halides is performed to fully understand this family. Therefore, this work provides insights into designing birefringent materials with balanced optical properties.

Synthesis of Large-Scale High-Quality Metal-Organic Frameworks on Cu(100) via Hierarchical Dehydrogenation Reactions.

Thermal stimulus has been considered as a promising strategy for controlling on-surface reactions, allowing the formation of diverse products on metal substrates. Here, we successfully achieve hierarchical dehydrogenation reactions of amino groups on a Cu(100) surface. By carefully adjusting the experimental parameters, we synthesize large-scale and low-defect density surface metal-organic frameworks on copper surfaces. Our work sheds light on a controllable route for the synthesis of high-quality metal-organic coordination supramolecular structures via on-surface chemistry.

Blind light field image quality assessment based on deep meta-learning.

In recent years, the use of deep convolutional neural networks (DCNNs) for light field image quality assessment (LFIQA) has gained significant attention. Despite their notable successes, it is widely accepted that training DCNNs heavily depends on a large amount of annotated data. Additionally, convolutional network-based LFIQA methods show a limitation in capturing long-range dependencies. Unfortunately, LFIQA is essentially a typical small-sample problem, leading to existing DCNN-based LFIQA metrics requiring data augmentation but with unsatisfactory performance. To address these issues, this study proposes utilizing the self-attention capability of the Swin Transformer to efficiently capture spatial-angular information while employing meta-learning for small-sample learning in the LFIQA task. Specifically, a collection of LFIQA tasks is gathered, representing different distortions. Then, meta-learning is employed to acquire shared prior knowledge across diverse distortions. Finally, the quality prior model is fine-tuned on a target LFIQA task to obtain the final LFIQA model quickly. Experimental results show that the proposed LFIQA metric achieves high consistency with subjective scores, and outperforms several state-of-the-art LFIQA approaches.

BDNF-enriched small extracellular vesicles protect against noise-induced hearing loss in mice.

Noise-induced hearing loss (NIHL) is one of the most prevalent acquired sensorineural hearing loss etiologies and is characterized by the loss of cochlear hair cells, synapses, and nerve terminals. Currently, there are no agents available for the treatment of NIHL because drug delivery to the inner ear is greatly limited by the blood-labyrinth barrier. In this study, we used mesenchymal stem cell-derived small extracellular vesicles (MSC-sEVs) as nanoscale vehicles to deliver brain-derived neurotrophic factor (BDNF) and evaluated their protective effects in a mouse model of NIHL. Following intravenous administration, BDNF-loaded sEVs (BDNF-sEVs) efficiently increased the expression of BDNF protein in the cochlea. Systemic application of sEVs and BDNF-sEVs significantly attenuated noise-induced cochlear hair cell loss and NIHL in CBA/J mice. BDNF-sEVs also alleviated noise-induced loss of inner hair cell ribbon synapses and cochlear nerve terminals. In cochlear explants, sEVs and BDNF-sEVs effectively protected hair cells against H2O2-induced cell loss. Additionally, BDNF-sEVs remarkably ameliorated H2O2-induced oxidative stress, cell apoptosis, and cochlear nerve terminal degeneration. Transcriptomic analysis revealed that many mRNAs and miRNAs were involved in the protective actions of BDNF-sEVs against oxidative stress. Collectively, our findings reveal a novel therapeutic strategy of MSC-sEVs-mediated BDNF delivery for the treatment of NIHL.

A novel evolutionary method for parameter-free MEMS structural design and its application in piezoresistive pressure sensors.

In this paper, a novel simulation-based evolutionary method is presented for designing parameter-free MEMS structures with maximum degrees of freedom. This novel design method enabled semiautomatic structure evolution by weighing the attributes of each segment of the structure and yielded an optimal design after multiple iterations. The proposed method was utilized to optimize the pressure-sensitive diaphragm of a piezoresistive pressure sensor (PPS). Finite element method (FEM) simulations revealed that, in comparison to conventional diaphragms without islands and with square islands, the optimized diaphragm increased the stress by 10% and 16% and reduced the nonlinearity by 57% and 77%, respectively. These improvements demonstrate the value of this method. Characterization of the fabricated PPS revealed a high sensitivity of 8.8 mV V-1 MPa-1 and a low nonlinearity of 0.058% FS at 20 °C, indicating excellent sensor performance.

Design method for a small F-number two-material uniform dispersion immersion grating imaging spectrometer.

Immersion gratings have high dispersion efficiency and have important application value in miniaturized imaging spectrometers, but its serious dispersion nonlinearity causes difficulties in calibration and image processing, which limits its application range. To solve this, this paper presents a design method for a two-material linear dispersion immersion grating device design method, and a compact small F-number immersion grating spectrometer based on it. First the vector form dispersion equation of the two-material immersion grating is derived and the linear spectral dispersion immersion grating design process is given, then a compact small F-number uniform dispersion imaging spectrometer is given as a design example using the proposed method. The results show that when the operating band of the system is 1590-1675 nm, the spectral resolution is better than 0.25 nm, and F-number can achieve better than 2. Compared with traditional single-material immersion grating imaging spectrometer, the designed imaging spectrometer dispersion linearity is significantly improved. Finally, the influence of prism materials, structure parameters and grating parameters on dispersion nonlinearity is analyzed. Design and analysis results show that the proposed two-material immersion grating device has much better spectral dispersion nonlinearity correction ability, and its design method can provide reference to the compact spectrometer design based on immersion gratings.