Search Results (222)

Background/Objectives: Boron-dipyrromethene (BODIPY) derivatives are a superior class of fluorophores prized for their exceptional photostability and tunable photophysical properties. While ideal for imaging, their translation to photodynamic therapy (PDT) has been hampered by excitation in the visible range, leading to poor tissue penetration. To overcome this, intense research has focused on developing near-infrared (NIR)-absorbing BODIPY photosensitizers (PS). This review aims to systematically summarize the hierarchical design strategies, from molecular engineering to advanced nanoplatform construction, that underpin the recent progress of NIR-BODIPY PS in therapeutic applications. Methods: We conducted a comprehensive literature review using PubMed, Scopus, and Web of Science databases. The search focused on keywords such as “BODIPY”, “aza-BODIPY”, “near-infrared”, “photodynamic therapy”, “photothermal therapy”, “nanocarriers”, “hypoxia”, “immuno-phototherapy”, and “antibacterial.” This review analyzes key studies describing molecular design, chemical modification strategies (e.g., heavy-atom effect, π-extension), nanoplatform formulation, and therapeutic applications in vitro and in vivo. Results: Our analysis reveals a clear progression in design complexity. At the molecular level, we summarize strategies to enhance selectivity, including active targeting, designing “smart” PS responsive to the tumor microenvironment (TME) (e.g., hypoxia or low pH), and precise subcellular localization (e.g., mitochondria, lysosomes). We then detail the core chemical strategies for achieving NIR absorption and high singlet oxygen yield, including π-extension, the internal heavy-atom effect, and heavy-atom-free mechanisms (e.g., dimerization). The main body of the review categorizes the evolution of advanced theranostic nanoplatforms, including targeted systems, stimuli-responsive ‘smart’ systems, photo-immunotherapy (PIT) platforms inducing immunogenic cell death (ICD), hypoxia-overcoming systems, and synergistic chemo-phototherapy carriers. Finally, we highlight emerging applications beyond oncology, focusing on the use of NIR-BODIPY PS for antibacterial therapy and biofilm eradication. Conclusions: NIR-BODIPY photosensitizers are a highly versatile and powerful class of theranostic agents. The field is rapidly moving from simple molecules to sophisticated, multifunctional nanoplatforms designed to overcome key clinical hurdles like hypoxia, poor selectivity, and drug resistance. While challenges in scalability and clinical translation remain, the rational design strategies and expanding applications, including in infectious diseases, confirm that NIR-BODIPY derivatives will be foundational to the next generation of precision photomedicine. Full article

The osmium(II) polypyridyl complex [Os(tpy)(pydppn)]²⁺ (tpy = 2,2′:6′,2″-terpyridine; pydppn = 3-(pyrid-2′-yl)-4,5,9,16-tetraaza-dibenzo[a,c]naphthacene) was synthesized and characterized to evaluate the effect of an extended planar π-system on photophysical properties and DNA interactions. This complex represents the π-expanded analog of the previously studied [Os(tpy)(pydppz)]²⁺ system. Electrochemical studies revealed a reversible Os(II)/Os(III) oxidation at +0.99 V vs. SCE and five ligand-centered reductions, generally less negative than those of the smaller pydppz analog, consistent with enhanced electron-accepting ability. In acetonitrile, the complex exhibits UV absorption bands at 328 and 473 nm and near-infrared emission at 840 nm, assigned to a long-lived ³MLCT state (τ = 110 ns, Φ = 0.02). Upon titration with calf-thymus DNA, [Os(tpy)(pydppn)]²⁺ shows a pronounced light-switch effect, hypochromism, red-shifted MLCT bands, induced circular dichroism, and an increase in DNA melting temperature (ΔT_m = 8.9 ± 0.5 °C), consistent with intercalative binding. Viscometric titrations further support intercalation, with a binding constant K_B ≈ 1.2 × 10⁶ M⁻¹. Transient absorption spectroscopy indicates that DNA binding prolongs the excited-state lifetime and modifies vibrational relaxation pathways. These results highlight how π-system extension in Os(II) complexes modulates photophysical behavior and DNA affinity, offering insights for the rational design of NIR-emitting, DNA-targeted luminescent probes and potential phototherapeutic agents. Full article

Synergetic therapeutic study using multifunctional nanoplatforms has been developed as an innovative modality for effective cancer treatment to improve the clinical efficiency of anticancer drugs and reduce severe off-target side effects. Herein, an artificial nanoplatform (denoted as PPy-RhB-PDA-CD-LA) was prepared by grafting β-cyclodextrin (β-CD) derivatives and lactobionic acid (LA) on the surface of rhodamine B (RhB)-doped polypyrrole nanoparticles (PPy-RhB NPs) using polydopamine (PDA) as the intermediate linker. Doxorubicin (DOX) was selected and successfully loaded onto the nanoplatforms with a high loading content of 327 mg/g. Furthermore, significant NIR light-triggered release of DOX was observed in a weak acidic tumor microenvironment. The nanoplatform exhibited superior photostability with a high photothermal effect of 51.7% under irradiation by a 808 nm laser and a competent temperature sensitivity (SR is 1.44% °C⁻¹) under a single wavelength excitation. MTT assay against SMMC-7721 cells clearly illustrated that the nanoplatform had low cytotoxicity at a high level (200 μg/mL) after 24 h and high therapeutic efficacy of chemo-phototherapy. Thus, it is highly promising for use in biomedical applications. Full article

This study developed identification models for five domestic rice varieties—Akitakomachi (Akita 31), Hitomebore (Tohoku 143), Hinohikari (Nankai 102), Koshihikari (Etsunan 17) and Nanatsuboshi (Soriku 163)—using fluorescence spectroscopy, near-infrared (NIR) spectroscopy, and machine learning. Two-dimensional fluorescence images were generated from excitation emission matrix (EEM) spectra in the 250–550 nm and 900–1700 nm ranges. Four machine learning hybrid models combining a convolutional neural network (CNN) with k-nearest neighbor algorithm (KNN), random forest (RF), logistic regression (LR), and support vector machine (SVM), were constructed using Python (ver. 3.13.2) by integrating feature extraction from CNN with traditional algorithms. The performances of KNN, RF, LR, and SVM were compared with NIR spectra. The NIR+KNN model achieved 0.9367 accuracy, while the fluorescence fingerprint+CNN model reached 0.9717. The CNN+KNN model obtained the highest mean accuracy (0.9817). All hybrid models outperformed individual algorithms in discrimination accuracy. Fluorescence images revealed at 280 nm excitation/340 nm emission linked to tryptophan, and weaker peaks at 340 nm excitation/440 nm emission, likely due to advanced glycation end products. Hence, combining fluorescent fingerprinting with deep learning enables accurate, reproducible rice variety identification and could prove useful for assessing food authenticity in other agricultural products. Full article

To exploit the near-infrared (NIR) light of MoO₃, the MoVO_x mixed oxide was synthesized using a one-pot approach. The effects of different electrodes, V doping, and bias on the optoelectronic properties were investigated. The photoelectric responses to light sources with wavelengths of 405, 532, 650, 780, 808, 980, and 1064 nm were studied using both Au and carbon electrodes with 6B pencil drawings. The results demonstrate that the MoVO_x nanoblets exhibit photocurrent switching characteristics across the broadband region of the light spectrum. Even when zero bias was applied and the mixed oxide sample was stored at room temperature for over two years, a good photoelectric signal was still observed. This demonstrates that the MoVO_x nanoblets present an interface where interfacial charge transfer forms a strong built-in electric field, promoting photogenerated charge separation and transfer while suppressing photogenerated carrier recombination, and exhibiting self-powered characteristics. Interestingly, reducing the power of the typical excitation light sources resulted in a transition from positive to negative photocurrent features. This reflects the result of an imbalance between the concentration of material defects and the concentration of photogenerated electrons. The MoVO_x nanoblets not only enhance charge transport performance, but also significantly improve the exploitation of near-infrared light. Doping with V significantly improves the nanocomposites’ near-infrared (NIR) photoelectric sensitivity. This study demonstrates that heavily doping aliovalent ions during the in situ preparation of nanocomposites effectively enhances their photophysical properties. It provides a straightforward approach to narrowing the band gap of wide-bandgap oxides and effectively avoiding the recombination of photogenerated carriers. Full article

The online rapid classification of multi-cultivar watermelon, including seedless and seeded types, has far-reaching significance for enhancing quality control in the watermelon industry. However, interference in one-dimensional spectra affects the high-accuracy classification of multi-cultivar watermelons with similar appearances. This study proposed an innovative method integrating Gramian Angular Field (GAF), feature fusion, and Squeeze-and-Excitation (SE)-guided convolutional neural networks (CNN) based on VIS-NIR transmittance spectroscopy. First, one-dimensional spectra of 163 seedless and 160 seeded watermelons were converted into two-dimensional Gramian Angular Summation Field (GASF) and Gramian Angular Difference Field (GADF) images. Subsequently, a dual-input CNN architecture was designed to fuse discriminative features from both GASF and GADF images. Feature visualization of high-weight channels of the input images in convolutional layer revealed distinct spectral features between seedless and seeded watermelons. With the fusion of distinguishing feature information, the developed CNN model achieved a classification accuracy of 95.1% on the prediction set, outperforming traditional models based on one-dimensional spectra. Remarkably, wavelength optimization through competitive adaptive reweighted sampling (CARS) reduced GAF image generation time to 55.19% of full-wavelength processing, while improving classification accuracy to 96.3%. A better generalization of the model was demonstrated using 17 seedless and 20 seeded watermelons from other origins, with a classification accuracy of 91.9%. These findings substantiated that GAF-enhanced feature fusion CNN can significantly improve the classification accuracy of multi-cultivar watermelons, casting innovative light on fruit quality based on VIS-NIR transmittance spectroscopy. Full article

Improving charge transport in the aggregated state of nanocomposites is challenging due to the large number of defects present at grain boundaries. To enhance the charge transfer and photogenerated carrier extraction of MnO_x nanofibers, a MnO_x/GO (graphene oxide) nanocomposite was prepared. The effects of GO content and bias on the optoelectronic properties were studied. Representative light sources at 405, 650, 780, 808, 980, and 1064 nm were used to examine the photoelectric signals. The results indicate that the MnO_x/GO nanocomposites have photocurrent switching behaviours from the visible region to the NIR (near-infrared) when the amount of GO added is optimised. It was also found that even with zero bias and storage of the nanocomposite sample at room temperature for over 8 years, a good photoelectric signal could still be extracted. This demonstrates that the MnO_x/GO nanocomposites present a strong built-in electric field that drives the directional motion of photogenerated carriers, avoids the photogenerated carrier recombination, and reflect a good photophysical stability. The strength of the built-in electric field is strongly affected by the component ratios of the resulting nanocomposite. The formation of the built-in electric field results from interfacial charge transfer in the nanocomposite. Modulating the charge behaviour of nanocomposites can significantly improve the physicochemical properties of materials when excited by light with different wavelengths and can be used in multidisciplinary applications. Since the recombination of photogenerated electron–hole pairs is the key bottleneck in multidisciplinary fields, this study provides a simple, low-cost method of tailoring defects at grain boundaries in the aggregated state of nanocomposites. These results can be used as a reference for multidisciplinary fields with low energy consumption. Full article

Highly integrable silicon carbide (SiC) has emerged as a promising platform for photonic integrated circuits (PICs), offering a comprehensive set of material and optical properties that are ideal for the integration of nonlinear devices and solid-state quantum defects. However, despite significant progress in nanofabrication technology, the development of SiC on an insulator (SiCOI)-based photonics faces challenges due to fabrication-induced material optical losses and complex processing steps. An alternative approach to mitigate these fabrication challenges is the direct deposition of amorphous SiC on an insulator (a-SiCOI). However, there is a lack of systematic studies aimed at producing high optical quality a-SiC thin films, and correspondingly, on evaluating and determining their optical properties in the telecom range. To this end, we have studied a single-source precursor, 1,3,5-trisilacyclohexane (TSCH, C₃H₁₂Si₃), and chemical vapor deposition (CVD) processes for the deposition of SiC thin films in a low-temperature range (650–800 °C) on a multitude of different substrates. We have successfully demonstrated the fabrication of smooth, uniform, and stoichiometric a-SiCOI thin films of 20 nm to 600 nm with a highly controlled growth rate of ~0.5 Å/s and minimal surface roughness of ~5 Å. Spectroscopic ellipsometry and resonant micro-photoluminescence excitation spectroscopy and mapping reveal a high index of refraction (~2.7) and a minimal absorption coefficient (<200 cm⁻¹) in the telecom C-band, demonstrating the high optical quality of the films. These findings establish a strong foundation for scalable production of high-quality a-SiCOI thin films, enabling their application in advanced chip-scale telecom PIC technologies. Full article

Theranostic agents enable the simultaneous diagnosis and treatment of diseases, and they are particularly useful in fluorescent imaging and cancer therapies. In this study, carbon quantum dots were synthesized via a microwave-assisted method using citric acid and bovine serum albumin (BSA) as precursors. The resulting CQDs exhibited spherical morphology, an average size of 4 nm, and an amorphous graphitic structure. FT-IR characterization revealed the presence of amide bonds and oxygenated functional groups. At the same time, optical analysis showed excitation at 320 nm and emission between 360 and 400 nm, with fluorescent stability maintained for one month. Furthermore, the CQDs demonstrated good thermal stability and photothermal efficiency, reaching temperatures above 41 °C within 15 min under NIR irradiation, with a mass loss of less than 1%. Their stability was evaluated in media with different pH levels, simulating physiological and tumor environments. While their behavior was affected under acidic conditions, their excellent photothermal conversion capacity and overall stability in triple-distilled water positioned them as promising candidates for theranostic applications in cancer, effectively combining diagnostic imaging and thermal therapy. Full article

Visible and near-infrared (Vis–NIR) spectroscopy enables the rapid prediction of soil properties but faces three limitations with conventional machine learning: information loss and overfitting from high-dimensional spectral features; inadequate modeling of nonlinear soil–spectra relationships; and failure to integrate multi-scale spatial features. To address these challenges, we propose ReSE-AP Net, a multi-scale attention residual network with spatial pyramid pooling. Built on convolutional residual blocks, the model incorporates a squeeze-and-excitation channel attention mechanism to recalibrate feature weights and an atrous spatial pyramid pooling (ASPP) module to extract multi-resolution spectral features. This architecture synergistically represents weak absorption peaks (400–1000 nm) and broad spectral bands (1000–2500 nm), overcoming single-scale modeling limitations. Validation on the LUCAS2009 dataset demonstrated that ReSE-AP Net outperformed conventional machine learning by improving the R² by 2.8–36.5% and reducing the RMSE by 14.2–69.2%. Compared with existing deep learning methods, it increased the R² by 0.4–25.5% for clay, silt, sand, organic carbon, calcium carbonate, and phosphorus predictions, and decreased the RMSE by 0.7–39.0%. Our contributions include statistical analysis of LUCAS2009 spectra, identification of conventional method limitations, development of the ReSE-AP Net model, ablation studies, and comprehensive comparisons with alternative approaches. Full article

This study investigates near-infrared (NIR)-induced, Phyto-enhanced, second harmonic generation-mediated photodynamic therapy (Phyto-SHG-PDT) using barium titanate (BT)/rhein/polyethylene glycol 100 (PEG100) and BT/Yemenite “Etrog” leaf extract/PEG100 nanoconjugates. We compare continuous-wave (CW), multi-line Argon-ion laser illumination in the NIR range with high-peak-power femtosecond (fs) 800 nm pulses. Under CW NIR light, BT/rhein nanoconjugates reduced PC3 prostate cancer cell viability by 18% versus non-irradiated controls (p < 0.05), while BT/extract nanoconjugates exhibited 15% dark toxicity. The observed SHG signal matched theoretical predictions and previous CW laser studies. Reactive Oxygen Species (ROS) scavenger 1,3-diphenyl-isobenzofuran (DPBF) showed reduced absorbance at 410 nm upon NIR illumination, indirectly supporting SHG emission at 400 nm from nanoconjugates. Under fs-pulsed laser exposure, pronounced two-photon absorption (TPA) and SHG effects were observed in both nanoconjugate types. Our results demonstrate the effectiveness of BT/rhein nanoconjugates under both laser conditions, while the BT/extract nanoconjugates benefited from high-power pulsed excitation. These results highlight the potential of BT-based Phyto-SHG-PDT nanoconjugates for NIR and blue light applications, leveraging nonlinear optical effects for advanced photochemical cancer therapies. Full article

Near-Infrared Spectroscopy (NIRS) analysis technology faces numerous challenges in industrial applications. Firstly, the generalization capability of models is significantly affected by instrumental heterogeneity, environmental interference, and sample diversity. Traditional modeling methods exhibit certain limitations in handling these factors, making it difficult to achieve effective adaptation across different scenarios. Specifically, data distribution shifts and mismatches in multi-scale features hinder the transferability of models across different crop varieties or instruments from different manufacturers. As a result, the large amount of previously accumulated NIRS and reference data cannot be effectively utilized in modeling for new instruments or new varieties, thereby limiting improvements in modeling efficiency and prediction accuracy. To address these limitations, this study proposes a novel transfer learning framework integrating multi-scale network architecture with Balanced Distribution Adaptation (BDA) to enhance cross-instrument compatibility. The key contributions include: (1) RX-Inception multi-scale structure: Combines Xception’s depthwise separable convolution with ResNet’s residual connections to strengthen global–local feature coupling. (2) Squeeze-and-Excitation (SE) attention: Dynamically recalibrates spectral band weights to enhance discriminative feature representation. (3) Systematic evaluation of six transfer strategies: Comparative analysis of their impacts on model adaptation performance. Experimental results on open corn and pharmaceutical datasets demonstrate that BDSER-InceptionNet achieves state-of-the-art performance on primary instruments. Notably, the proposed Method 6 successfully enables NIRS model sharing from primary to secondary instruments, effectively mitigating spectral discrepancies and significantly improving transfer efficacy. Full article

Photosensitizers with high singlet oxygen (¹O₂) generation capacity under near-infrared (NIR) irradiation are essential and challenging for photodynamic therapy (PDT). A simple yet effective molecular design strategy is realized to construct 1 + 1 > 2 photosensitizers with synergistic effects by covalently integrating iridium complexes with cyanine via ether linkages, as well as introducing aldehyde groups to suppress non-radiative decay, named CHO−Ir−Cy. It is demonstrated that CHO−Ir−Cy successfully maintains the NIR absorption and emission originated from cyanine units and high ¹O₂ generation efficiency from the iridium complex part, which gives full play to their respective advantages while compensating for shortcomings. Density functional theory (DFT) calculations reveal that CHO−Ir−Cy exhibits a stronger spin–orbit coupling constant (ξ (S1, T1) = 9.176 cm⁻¹) and a reduced energy gap (ΔE = −1.97 eV) between triplet excited states (T₁) and first singlet excited states (S₁) compared to parent Ir−Cy or Cy alone, directly correlating with its enhanced ¹O₂ production. Remarkably, CHO−Ir−Cy demonstrates superior cellular internalization in 4T1 murine breast cancer cells, generating substantially elevated ¹O₂ yields compared to individual Ir−Cy/Cy under 808 nm laser irradiation. Such enhanced reactive oxygen species production translates into effective cancer cell ablation while maintaining favorable biocompatibility, significant phototoxicity and negligible dark toxicity. This molecular engineering strategy overcomes the inherent NIR absorption limitation of traditional iridium complexes and ensures their own high ¹O₂ generation ability through dye–metal synergy, establishing a paradigm for designing metal–organic photosensitizers with tailored photophysical properties for precision oncology. Full article

Herein, we study a method for developing a broad-emission emitter that can emit radiation from the visible light to NIR regions. Firstly, an NIR phosphor’s optical properties (e.g., scattering vs. weight concentration, conversion efficiency, and emission spectra under blue and red light excitation) are investigated. Then, pcW-LEDs encapsulated with NIR down-conversion phosphor samples are prepared to test these optical properties. The results show that pcW-LEDs encapsulated with the NIR phosphor at different weight concentrations of 10.0%, 12.5%, and 15.5%, respectively, emit a broadband emission from 400 nm to 900 nm. The EQE values of the pcW-LEDs encapsulated with NIR phosphor at weight concentrations of 10%, 12.5%, and 15.0% are 26%, 23%, and 19%, respectively. The correlated color temperatures of these samples are 5767 K, 5940 K, and 6068 K, respectively. The obtained radiant fluxes of the samples are 26 mW, 22 mW, and 18 mW, respectively, at an injection current of 50 mA. Full article

Near-infrared (NIR) rhodamine dyes are pivotal for bioimaging due to the minimal tissue interference. Yet, their rational design is hindered by unreliable computational methods for excited-state property prediction. We benchmarked the time-dependent density functional theory (TDDFT) with the linear-response (LR) and state-specific (SS) solvation models across five functionals (CAM-B3LYP, M06-2X, ωB97X-D, B3LYP, MN15) and optimized the ground/excited states for 42 rhodamine derivatives. A robust linear calibration framework was established by connecting the computed and experimental wavelengths, which was rigorously validated through six-fold cross-validation. The key metrics included the mean absolute error (MAE) and R² to assess the prediction robustness. CAM-B3LYP combined with LR solvation achieved the highest accuracy (absorption: MAE = 6 nm, R² = 0.94; emission: MAE = 12 nm, R² = 0.72). By integrating the TDDFT with a calibrated linear-response solvation model, we achieved sub-12 nm accuracy in predicting the NIR fluorescence peaks. This framework enabled the rational design of nine novel rhodamine derivatives with emissions beyond 700 nm, offering a paradigm shift in bioimaging probe development. Full article