Near-infrared Research Articles

Discrimination model of geographical area from coconut milk by near-infrared spectroscopy: Exploration in tandem with classical chemometrics, machine learning, and deep learning

This work proposes exploring the discrimination model by near-infrared (NIR) spectroscopy (FT-NIR and Micro-NIR) for geographical source areas of coconut milk in tandem with the classical to modern chemometrics classifier. The discrimination model was developed using qualitative chemometrics techniques from classic (Principal Component Analysis-PCA, Partial Least Squares Discriminant Analysis-PLS-DA, Linear Discriminant Analysis-LDA) to modern, including classifiers from machine learning (Support Vector Machine-SVM, k-Nearest Neighbor-KNN, Artificial Neural Network-ANN) and deep learning (Simple Convolutional Neural Networks-S-CNN, S-AlexNET, Residual Networks-ResNET). Three sources as geographical areas of coconut milk originally from Thailand were used, including the south region (Chumphon Province), middle region (Samut Songkhram Province), and east region (Chonburi Province). Our findings showed that a classifier from SVM and ResNET could yield the optimal performance for discriminating the geographical source area of coconut milk using FT-NIR. Furthermore, when using Micro-NIR, the classifier from LDA, SVM, KNN and ResNET delivered the highest accuracy. The performance discrimination models above were excellent when classified based on the kappa coefficient. This study concluded that both FT-NIR and Micro-NIR supported by classical to modern chemometric classifiers could be used to evaluate the geographical area source from coconut milk. Also, the method in this study includes a strategy for discovering feature-important NIR spectra for interpretability purposes, thereby facilitating the qualitative interpretation of results for all types of classifiers.

Two-photon upconversion photoluminescence in CsPbBr3 nanoplates

The utilization of solar energy by light conversion processes in both natural and artificial photosynthesis systems has become a pivotal means of sustaining a consistent power supply for our daily lives and production. In general, these reactions rely on the visible spectra region where the sun produces abundant energy according to the black body's emission. Further expanding the adoption of the near-infrared (NIR) spectral region through upconversion has become an intelligent strategy to improve the entire utilization rate of solar energy. In this work, the two-photon upconversion (TPUC) properties were discovered in CsPbBr3 nanoplates (NPs) emitted at 450 nm, and a sub-gap energy level was observed to serve as the center to facilitate the upconversion process. The excitation threshold for TPUC is drastically lower than that for the two-photon absorption, another nonlinear upconversion path that requires strengthened excitation power. Moreover, a significant negative correlation between the excitation threshold for TPUC in the CsPbBr3 NPs and the exciton binding energy was unveiled, which could be attributed to the enhanced quantum confinement effects. Our work paved the way for a feasible way to expand the utilization of the NIR spectral region in light conversion applications.

Authentication of Argentinean extra-virgin olive oils using three-way fluorescence and two-way near-infrared data fused with multi-block DD-SIMCA

A trending problem of Extra Virgin Olive Oil (EVOO) adulteration is investigated using two analytical platforms, involving: (1) Near Infrared (NIR) spectroscopy, resulting in a two-way data set, and (2) Fluorescence Excitation-Emission Matrix (EEFM) spectroscopy, producing three-way data. The related instruments were employed to study genuine and adulterated samples. Each data set was first separately analyzed using the Data Driven-Soft Independent Modeling of Class Analogies (DD-SIMCA) method, based on Principal Component Analysis (for the two-way NIR data) and PARallel FACtor analysis (for the three-way EEFM data). The data sets were then processed together using the multi-block fusion method, based on the concept of Cumulative Analytical Signal (CAS). A comparison of the data processing methods in terms of sensitivity, specificity and selectivity showed the following order of excellence: NIR < EEFM < NIR + EEFM. This finding confirms the effectiveness of multi-block data fusion, which cumulatively improves the model performance.

Classification of Histamine Content in Fish Using Near-Infrared Spectroscopy and Machine Learning Techniques

Near-infrared (NIR) spectroscopy has emerged as a popular technique for assessing food quality due to its advantages over complex chemical analysis methods. However, the application of NIR spectroscopy for evaluating fish quality based on histamine content has not been extensively explored. This study investigates the use of NIR spectroscopy in combination with machine learning (ML) techniques to classify fish samples into two safety classes, Safe and Unsafe, based on their histamine content. A comprehensive NIR dataset comprising 11,360 spectra collected at eight distinct positions within the fish body was obtained from 284 fish samples of mackerel, tuna, and pompano species. ML experiments were conducted to classify fish samples based on whether their histamine content exceeded the permissible limit of 100 ppm. To address class imbalance and optimize ML models, various data pre-processing and feature extraction techniques as well as ML algorithms were explored. The results demonstrated that utilizing NIR data specifically obtained from the tail’s flesh, a specific location within the fish, yielded superior models for fish safety classification. A feature extraction method employing pre-processed NIR spectra and their second derivatives, combined with an optimized convolutional neural network architecture, outperformed traditional ML classifiers with an accuracy of approximately 93%.

The highly efficient and stable near-infrared phosphor Ca3MgSnGe3O12: Cr3+ for multifunctional application

The investigation of efficient and stable near-infrared (NIR) luminescent materials is crucial for rapidly developing near-infrared spectroscopic techniques. Herein, NIR phosphors Ca3MgSnGe3O12: Cr3+ with ultra thermal stability and high internal quantum yield (IQY) are explored. The emission intensity remained at 91.75 %@423 K of room temperature and the IQY/EQE reaches 91.41 %/34.04 % after doping the H3BO3 flux agent for optimization. Moreover, a single luminescence center was identified by cryogenic photo luminescence spectroscopy (PL) from 4 K to 300 K and lifetime decay curve. Importantly, NIR light can easily removes all kinds of background interference that cannot be easily eliminated by visible light, which is not only widely used in night vision and biological tissue penetration, but also has higher application prospects in NIR fingerprint detection. Moreover, it clearly displays high level of fingerprint details under high temperature conditions and after water immersion, thus it is perfectly suited for using in Automatic Fingerprint Identification System (AFIS) systems. Therefore, Ca3MgSnGe3O12: Cr3+ NIR pc-LEDs have great potential for latent fingerprint detection at actual crime scenes.

Highly Efficient Near-Infrared Luminescent Radicals with Emission Peaks over 750 nm.

Purely organic molecules exhibiting near-infrared (NIR) emission possess considerable potential for applications in both biological and optoelectronic technological domains, owing to their inherent advantages such as cost-effectiveness, biocompatibility, and facile chemical modifiability. However, the repertoire of such molecules with emission peaks exceeding 750 nm and concurrently demonstrating high photoluminescence quantum efficiency (PLQE) remains relatively scarce due to the energy gap law. Herein, we report two open-shell NIR radical emitters, denoted as DMNA-Cz-BTM and DMNA-PyID-BTM, achieved through the strategic integration of a donor group (DMNA) onto the Cz-BTM and PyID-BTM frameworks, respectively. We found that the donor-acceptor molecular structure allows the two designed radical emitters to exhibit a charge-transfer excited state and spatially separated electron and hole levels with non-bonding characteristics. Thus, the high-frequency vibrations are effectively suppressed. Besides, the reduction of low-frequency vibrations is observed. Collectively, the non-radiative decay channel is significantly suppressed, leading to exceptional NIR PLQE values. Specifically, DMNA-Cz-BTM manifests an emission peak at 758 nm alongside a PLQE of 55%, whereas DMNA-PyID-BTM exhibits an emission peak at 778 nm with a PLQE of 66%. Notably, these represent the pinnacle of PLQE among metal-free organic NIR emitters with emission peaks surpassing 750 nm.

Highly Efficient Near‐Infrared Luminescent Radicals with Emission Peaks over 750 nm

Purely organic molecules exhibiting near‐infrared (NIR) emission possess considerable potential for applications in both biological and optoelectronic technological domains, owing to their inherent advantages such as cost‐effectiveness, biocompatibility, and facile chemical modifiability. However, the repertoire of such molecules with emission peaks exceeding 750 nm and concurrently demonstrating high photoluminescence quantum efficiency (PLQE) remains relatively scarce due to the energy gap law. Herein, we report two open‐shell NIR radical emitters, denoted as DMNA‐Cz‐BTM and DMNA‐PyID‐BTM, achieved through the strategic integration of a donor group (DMNA) onto the Cz‐BTM and PyID‐BTM frameworks, respectively. We found that the donor‐acceptor molecular structure allows the two designed radical emitters to exhibit a charge‐transfer excited state and spatially separated electron and hole levels with non‐bonding characteristics. Thus, the high‐frequency vibrations are effectively suppressed. Besides, the reduction of low‐frequency vibrations is observed. Collectively, the non‐radiative decay channel is significantly suppressed, leading to exceptional NIR PLQE values. Specifically, DMNA‐Cz‐BTM manifests an emission peak at 758 nm alongside a PLQE of 55%, whereas DMNA‐PyID‐BTM exhibits an emission peak at 778 nm with a PLQE of 66%. Notably, these represent the pinnacle of PLQE among metal‐free organic NIR emitters with emission peaks surpassing 750 nm.

Design and validation of a high-speed hyperspectral laparoscopic imaging system.

Minimally invasive surgery (MIS) has shown vast improvement over open surgery by reducing post-operative stays, intraoperative blood loss, and infection rates. However, in spite of these improvements, there are still prevalent issues surrounding MIS that may be addressed through hyperspectral imaging (HSI). We present a laparoscopic HSI system to further advance the field of MIS. We present an imaging system that integrates high-speed HSI technology with a clinical laparoscopic setup and validate the system's accuracy and functionality. Different configurations that cover the visible (VIS) to near-infrared (NIR) range of electromagnetism are assessed by gauging the spectral fidelity and spatial resolution of each hyperspectral camera. Standard Spectralon reflectance tiles were used to provide ground truth spectral footprints to compare with those acquired by our system using the root mean squared error (RMSE). Demosaicing techniques were investigated and used to measure and improve spatial resolution, which was assessed with a USAF resolution test target. A perception-based image quality evaluator was used to assess the demosaicing techniques we developed. Two configurations of the system were developed for evaluation. The functionality of the system was investigated in a phantom study and by imaging ex vivo tissues. Multiple configurations of our system were tested, each covering different spectral ranges, including VIS (460 to 600nm), red/NIR (RNIR) (610 to 850nm), and NIR (665 to 950nm). Each configuration is capable of achieving real-time imaging speeds of up to 20 frames per second. RMSE values of , , and 3.47% were achieved for the VIS, RNIR, and NIR systems, respectively. We obtained sub-millimeter resolution using our demosaicing techniques. We developed and validated a high-speed hyperspectral laparoscopic imaging system. The HSI system can be used as an intraoperative imaging tool for tissue classification during laparoscopic surgery.

Combined Chemo- and Photothermal Therapies of Non-Small Cell Lung Cancer Using Polydopamine/Au Hollow Nanospheres Loaded with Doxorubicin.

The chemotherapeutic agent doxorubicin (DOX) is limited by its cardiotoxicity, posing challenges in its application for non-small cell lung cancer (NSCLC). This study aims to explore the efficacy of polydopamine/Au nanoparticles loaded with DOX for chemotherapy and photothermal therapy in NSCLC to achieve enhanced efficacy and reduced toxicity. Hollow polydopamine (HPDA)/Au@DOX was synthesized via polydopamine chemical binding sacrificial template method. Morphology was characterized using transmission electron microscopy, particle size and potential were determined using dynamic light scattering, and photothermal conversion efficiency was assessed using near-infrared (NIR) thermal imaging. Drug loading rate and in vitro drug release were investigated. In vitro, anti-tumor experiments were conducted using CCK-8 assay, flow cytometry, and live/dead cell staining to evaluate the cytotoxicity of HPDA/Au@DOX on A549 cells. Uptake of HPDA/Au@DOX by A549 cells was detected using the intrinsic fluorescence of DOX. The in vivo anti-metastasis and anti-tumor effects of HPDA/Au@DOX were explored in mouse lung metastasis and subcutaneous tumor models, respectively. HPDA/Au@DOX with a particle size of (164.26±3.25) nm, a drug loading rate of 36.31%, and an encapsulation efficiency of 90.78% was successfully prepared. Under 808 nm laser irradiation, HPDA/Au@DOX accelerated DOX release and enhanced uptake by A549 cells. In vitro photothermal performance assessment showed excellent photothermal conversion capability and stability of HPDA/Au@DOX under NIR laser irradiation. Both in vitro and in vivo experiments demonstrated that the photothermal-chemotherapy combination group (HPDA/Au@DOX+NIR) exhibited stronger anti-metastatic and anti-tumor activities compared to the monotherapy group (DOX). HPDA/Au@DOX nanosystem demonstrated excellent photothermal effect, inhibiting the growth and metastasis of A549 cells. This nanosystem achieves the combined effect of chemotherapy and photothermal, making it promising for NSCLC treatment.

Quantitative prediction of minced chicken gel strength under ultrasonic treatment by NIR spectroscopy coupled with nonlinear chemometric tools evaluated using APaRPs

Achieving the ideal gel strength is essential for desired texture in minced chicken products. This study developed a rapid, non-destructive method using near-infrared (NIR) spectroscopy and nonlinear chemometric modeling to predict minced chicken gel strength under ultrasonic treatment. Initially, minced chicken samples were subjected to high-intensity ultrasound for 0–50 min. This was followed by heat-induced gelation. Gel strength was conventionally measured, and NIR spectra were collected. Nonlinearity between gel strength and spectral data was confirmed using augmented partial residual plots (APaRPs). Subsequently, nonlinear support vector machine (SVM) and extreme learning machine (ELM) models were developed using full NIR spectra and variable selection methods, including uninformative variable elimination (UVE), competitive adaptive reweighting (CARS), and genetic algorithms (GA). GA proved most effective for enhancing model performance, achieving the highest predicted coefficient of determination (Rp2 = 0.8772) with the ELM model, demonstrating potential for rapid, non-destructive prediction of minced chicken gel strength quality.

Effects of UV ozone treatment on the photoresponse of the Pt nanoparticles decorated WS2

Chemical vapor deposition (CVD)-grown and Pt nanoparticles (NPs) decorated multilayer WS2 is treated by ultraviolet (UV) ozone for the modification of the surface roughness to realize the enhanced hot carriers injection via the internal photoemission (IPE). The morphology, structure and photophysical properties as well as the dependence of the photoresponse on the UV ozone treatment are investigated. The UV ozone treatment demonstrates obvious effect on the WS2 surface roughness (Sa), which reaches the maximum around 14 nm after 2 min exposure and subsequently decrease with the extension of treatment duration. UV ozone treatment also leads to obviously diminished photoluminescence (PL) and shortened excitons lifetime for bare WS2 while its influence on the electronic structure is negligible. The diminished PL, shortened PL decaying lifetime and increased Sa are all originated from the formation of WOx due to the consumption of top WS2 layer by the severe oxidation, and such effects will be greatly alleviated when the fresh and undisturbed underlying WS2 layer appears with the treatment duration extended to 4 min. The 2 min UV ozone treated WS2/Pt exhibits optimal wide spectrum photoresponse (400–900 nm) with the near infrared (NIR) responsivity around 18 A/W at 750 nm, about 60 % higher compared to that of untreated one while the 4 min overtreated WS2/Pt demonstrates much deteriorated photoresponse. Such behavior can be ascribed to the enhanced hot electrons injection from Pt to WS2 due to the formation of rough Schottky contact as well as the separation of photo-excited electron-hole pairs by Schottky junction. Our study proves that the Sa is a key factor not only for the exciton dynamics but also for the hot electron injection from Pt to WS2.

ALMA reveals a dust-obscured galaxy merger at cosmic noon

Context. Galaxy mergers play a critical role in galaxy evolution. They alter the size, morphology, dynamics, and composition of galaxies. Galaxy mergers have so far mostly been identified through visual inspection of their rest-frame optical and near-IR (NIR) emission. Dust can obscure this emission, however, resulting in the misclassification of mergers as single galaxies and in an incorrect interpretation of their baryonic properties. Aims. Having serendipitously discovered a dust-obscured galaxy merger at z = 1.17, we aim to determine the baryonic properties of the two merging galaxies, including the star formation rate (SFR) and the stellar, molecular gas and dust masses. Methods. Using Band 3 and 6 observations from the Atacama Large Millimeter and submillimeter Array (ALMA) and ancillary data, we studied the morphology of this previously misclassified merger. We deblended the emission, derived the gas masses from CO observations, and modeled the spectral energy distributions to determine the properties of each galaxy. Using the rare combination of ALMA CO(2–1), CO(5–4) and dust-continuum (rest-frame 520 μm) observations, we provide insight into the gas and dust content and into the properties of the interstellar medium of each merger component. Results. We find that only one of the two galaxies is highly obscured by dust, but both are massive (&gt; 1010.5 M⊙) and highly star forming (SFR = 60 − 900 M⊙/yr), have a moderate-to-short depletion time (tdepl &lt; 0.7 Gyr) and a high gas fraction (fgas ≥ 1). Conclusions. These properties can be interpreted as the positive impact of the merger. With this serendipitous discovery, we highlight the power of (sub)millimeter observations to identify and characterise the individual components of obscured galaxy mergers.

Photoacoustic tracking of photo-magnetically powered nanoparticles for cancer therapy

Abstract The in vivo propulsion and monitoring of nanoparticles (NPs) have received tremendous achievements in the past decade. Developing functional NPs that can be efficiently manipulated inside the human body with a non-invasive tracking modality is critical to clinical translation. This study synthesized a photo-magnetically powered nanoparticle (PMN) with a Fe3O4 core and gold spiky surface. The Au-nanotips ensure PMNs have a strong light absorption in the second near-infrared (NIR) window and produce outstanding photoacoustic signals. The Bio-transmission electron microscopy and simulation results prove that the assembly of PMNs under a magnetic field further enhances the photothermal conversion in cells, contributing to the reduction of ambient viscosity. Photoacoustic imaging (PAI) realized real-time monitoring of PMN movements and revealed that laser plus magnetic coupling could improve intratumoral distribution and retention. The proposed methods exhibit excellent potential for the clinical research of cancer nanotherapies.

Facile synthesis, multimode and tunable luminescence, and multifunctional applications of rare earth ions activated lead-free double perovskite crystals

Lead-free double perovskites have gained recognition as top luminescent materials due to their environmental friendliness, high chemical stability, structural adjustability, and excellent photoelectric properties. However, the poor modulation of emission restricts their applications, and it is highly desirable to explore stable and efficient double perovskites with multimode luminescence and adjustable spectra for multifunctional photoelectric applications. Herein, the rare earth ions Ln3+ (Er3+ and Ho3+) doped Cs2NaYCl6:Sb3+ crystals were synthesized by a simple solvothermal route. The X-ray diffraction pattern (XRD), energy-dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and elemental mapping images demonstrate that the Sb3+, Er3+, and Ho3+ ions have been homogeneously incorporated into the Cs2NaYCl6 crystals. As anticipated, the emission spectra of Cs2NaYCl6:Sb3+/Ln3+ are composed of two bands. One broad blue band derives from self-trapped exciton (STE) in [SbCl6]3− octahedra while another group of emission peaks stems from the f-f transitions of Ln3+ ions. The emission colors of Cs2NaYCl6:Sb3+/Ln3+ phosphors can be tuned in a wide range by modulating the doping concentrations of Ln3+ ions. The efficient energy transfer from STE to Ln3+ is the key point to achieving the efficient and tunable emissions Cs2NaYCl6:Sb3+/Ln3+ samples. Interestingly, Cs2NaYCl6:Sb3+/Ln3+ can also exhibit characteristic up-conversion luminescence of Ln3+ under near-infrared (NIR) excitation besides the down-conversion luminescence, revealing that the materials may have potential applicability in multimode anti-counterfeiting and information encryption applications. Furthermore, the light emitting diodes (LEDs) assembled by Cs2NaYCl6:Sb3+ and Cs2NaYCl6:Sb3+/Ln3+ phosphors display dazzling blue, green, and red emissions under a forward bias current, which indicates that the as-obtained double perovskites materials may have great potential in solid-state lighting and optoelectronic devices.

Stretchable, Self-Healing, and Bioactive Hydrogel with High-Functionality N,N'-bis(acryloyl)cystamine Dynamically Bonded Ag@polydopamine Crosslinkers for Wearable Sensors.

Hydrogels present attractive opportunities as flexible sensors due to their soft nature and tunable physicochemical properties. Despite significant advances, practical application of hydrogel-based sensor is limited by the lack of general routes to fabricate materials with combination of mechanical, conductive, and biological properties. Here, a multi-functional hydrogel sensor is reported by in situ polymerizing of acrylamide (AM) with N,N'-bis(acryloyl)cystamine (BA) dynamic crosslinked silver-modified polydopamine (PDA) nanoparticles, namely PAM/BA-Ag@PDA. Compared with traditional polyacrylamide (PAM) hydrogel, the BA-Ag@PDA nanoparticles provide both high-functionality crosslinks and multiple interactions within PAM networks, thereby endowing the optimized PAM/BA-Ag@PDA hydrogel with significantly enhanced tensile/compressive strength (349.80kPa at 383.57% tensile strain, 263.08kPa at 90% compressive strain), lower hysteresis (5.2%), improved conductivity (2.51 S m-1) and excellent near-infrared (NIR) light-triggered self-healing ability. As a strain sensor, the PAM/BA-Ag@PDAhydrogel shows a good sensitivity (gauge factor of 1.86), rapid response time (138ms), and high stability. Owing to abundant reactive groups in PDA, the PAM/BA-Ag@PDA hydrogel exhibits inherent tissue adhesiveness and antioxidant, along with a synergistic antibacterial effect by PDA and Ag. Toward practical applications, the PAM/BA-Ag@PDA hydrogel can conformally adhere to skin and monitor subtle activities and large-scale movements with excellent reliability, demonstrating its promising applications as wearable sensors for healthcare.

Visible/near-infrared luminescence and concentration effects of Pr3+-doped Sr2Al2GeO7 downconversion phosphors

The Pr3+ ion has been widely doped into various materials as a red and near-infrared (NIR) emitting center for applications in lighting and solar spectrum downconversion. Herein, the preparation of a new library of Pr3+-doped Sr2Al2GeO7 phosphors was proved by powder x-ray diffraction patterns and Rietveld refinements and characterized by a scanning electron microscope with energy-dispersive x-ray spectrometry. The Sr2Al2GeO7:Pr3+ sample strongly absorbs blue photons over 420–500 nm and yields intense visible emissions with dominant peaks around 490 nm from the Pr3+ 3P0 → 3H4 transition, as well as robust NIR emission bands over 800–1200 nm. In addition to the typical transitions of 1D2 → 3F2 at 880 nm, 1G4 → 3H4 at 1000 nm, and 1D2 → 3F3,4 at 1070 nm, the distinguishable NIR emission at 929 nm was demonstrated from the 3P0 → 1G4 transition via static and dynamic spectroscopic analysis. Most interestingly, for the 3P0 blue-excited state, a considerably elevated concentration of about 10%Pr3+ was optimal for the visible/NIR emissions, in stark contrast to the diluted optimal 1%Pr3+ for the 1D2 state. The relevant cross-relaxation from the 3P0 and 1D2 states between Pr3+ was comprehensively treated by theoretical speculations and experimental results. Such concentrated Pr3+ blue activators would significantly facilitate the blue-to-NIR downconversion through a desired two-step sequential transition from the 3P0 initial state to the 1G4 intermediate level for quantum efficiency exceeding unity. The current results would consolidate the basis of concentrated Pr3+ donors to promote the novel Pr3+/Yb3+ codoping downconversion for greatly increasing Si solar cell efficiency.

Visible light-triggered NIR ratiometric fluorescent metal-free CO-releasing molecule for self-monitoring of CO delivery and effective cancer therapy

Cancer is a serious global health issue, and exploring effective treatment methods is of great significance for cancer prevention and control. Carbon monoxide (CO), as an important gas signaling molecule in the life system, has been proven to have good anti-cancer effects. However, how to controllably, safely, and effectively deliver CO to the tumor site for clinical treatment remains a challenge. Herein, a new metal-free CO-releasing molecule COR-XAC was developed for controlling CO release and cancer therapy. COR-XAC is based on the hybrid of 3-hydroxyl flavone and oxanthracene fluorophores, showing visible light-controlled CO-releasing properties and near-infrared (NIR) ratiometric fluorescence changes at 690 and 760 nm. COR-XAC shows low cytotoxicity and can be successfully applied to release CO in cells and tumors, and the CO-releasing and delivery process could be monitored by its own NIR ratiometric fluorescence changes. More importantly, the anti-cancer performance of COR-XAC was evaluated in 4T1 tumor mice, and it was found that COR-XAC plus light illumination showed excellent tumor inhibition effect, which provided a promising new effective method for cancer treatment.

Understanding Macrophage Interaction with Antimony-Doped Tin Oxide Plasmonic Nanoparticles.

Antimony-doped tin oxide nanoparticles (ATO NPs) have emerged as a promising tool in biomedical applications, namely robust photothermal effects upon near-infrared (NIR) light exposure, enabling controlled thermal dynamics to induce spatial cell death. This study investigated the interplay between ATO NPs and macrophages, understanding cellular uptake and cytokine release. ATO NPs demonstrated biocompatibility with no impact on macrophage viability and cytokine secretion. These findings highlight the potential of ATO NPs for inducing targeted cell death in cancer treatments, leveraging their feasibility, unique NIR properties, and safe interactions with immune cells. ATO NPs offer a transformative platform with significant potential for future biomedical applications by combining photothermal capabilities and biocompatibility.

Plasmonic perovskite photodetector with high photocurrent and low dark current mediated by Au NR/PEIE hybrid layer

Hybrid organic-inorganic perovskite photodetectors have gained significant attention due to their superior potential for optoelectronic applications, offering various advantages such as low-cost processing, high charge carrier mobility, and lightweight properties. However, these perovskite photodetectors exhibit relatively low absorption in the near-infrared (NIR) range, which limits their potential applications. Here, to address this challenge, the integration of gold nanorods (Au NR) utilizing localized surface plasmon resonance (LSPR) effects in the NIR range has been developed, leading to enhanced light absorption in the active region and higher photocurrent generation. Additionally, ∼7.9 nm of thin polyethyleneimine ethoxylated (PEIE) interlayers were incorporated into the Au NR photodetectors, suppressing dark current by blocking charge injection. As a result, the synergistic effect of the Au NR/PEIE hybrid layer has led to a high-performance photodetector with a responsivity of 0.360 A/W and a detectivity of 1.81 × 1010 Jones, demonstrating a noticeable enhancement compared to the control device. Finite-difference time-domain (FDTD) simulations, morphological characterizations, and photoluminescence studies further support the mechanism for enhancing the performance of the device. We believe that our plasmon-enhanced protocol holds strong potential as a promising platform for perovskite optoelectronic devices.

A method of maize seed variety identification based on near-infrared spectroscopy combined with improved DenseNet model

The development of a real-time online system for rapid and non-destructive identification of seed varieties can significantly improve production efficiency in modern agriculture. Near-infrared spectroscopy technology has become one of the commonly used techniques in seed variety identification due to its fast and non-destructive characteristics. However, existing convolutional neural networks are difficult to reflect the complex nonlinear relationships of the near-infrared (NIR) spectrum, resulting in poor modeling performance, and their high model complexity is not conducive to real-time online identification tasks. Therefore, this study proposes a maize seed variety identification method using near-infrared spectroscopy technology and lightweight deep learning network (BAC-DenseNet). First, a total of 750 samples from 5 different types of maize seeds were taken as the research object. The spectral data were pre-processing using the SGD2-SNV, and the identification accuracy was improved by an average of 15.78 %. Then, the attraction–repulsion optimization algorithm combined with Laplacian Eigenmaps (AROA-LE) was used to perform dimension reduction on the pre-processed data, and the dimensionality was reduced from 1845 to 66. Finally, a lightweight deep learning network model (BAC-DenseNet) was constructed based on DenseNet-121 network with layer pruning and the introduction of batch channel normalization (BCN), self-attention and convolution mixed module (ACmix) and convolutional block attention module (CBAM). The experimental results show that the proposed BAC-DenseNet model has an identification accuracy of 99.33 %. Compared with the original network and seven other classical deep learning models, the proposed method has an average improvement of 2.83 %, 3.52 %, and 3.47 % in accuracy, Kappa, and MCC, respectively. Meanwhile, Params, Size, and FLOPs decreased by an average of 9.09 M, 35.08 MB, and 88.66 M, respectively. This method offered high accuracy and reliability in maize seed variety identification, which can provide qualitative indicators for the breeding, planting, and management of maize seed varieties. This study can provide a reference method for variety identification of other agricultural products.