Remarkable Near-Infrared Electrochromism in Tungsten Oxide Driven by Interlayer Water-Induced Battery-to-Pseudocapacitor Transition

Near-infrared (NIR) electrochromism is of academic and technological interest for a variety of applications in advanced solar heat regulation, photodynamic therapy, optical telecommunications, and military camouflage. However, inorganic materials with outstanding NIR modulation capability are quite few. Herein, we propose a promising strategy for achieving strong NIR electrochromism in tungsten oxide that is closely related to its electrochemical transformation from battery-type behavior to pseudocapacitance, induced by introducing an interlayer space with water molecules within tungsten oxide. Further evidence demonstrates that the interlayer water molecules significantly reduced the energy barrier to ion diffusion and increased the ion flux in tungsten oxide. As a result, compared with anhydrous WO₃, the as-synthesized WO₃·2H₂O nanoplates exhibited remarkably improved NIR electrochromic properties, including a large transmittance modulation (90.4%), high coloration efficiency (322.6 cm² C^-1), and high cyclic stability (maintaining 93.7% after 500 cycles), which were comparable to those of the best reported NIR electrochromic materials. Moreover, the application of the WO₃·2H₂O nanoplate-based electrochromic device resulted in a temperature difference of 11.9 °C, indicating good solar thermal regulation ability.

Near-infrared heating of skin to delineate non-melanoma skin cancer lesions: A pilot study

BACKGROUND

Surgical excision is a mainstay of treatment for non-melanoma skin cancer (NMSC); improving margin delineation can reduce the need for further monitoring/treatment. The objective of this pilot study was to determine if near-infrared radiation (NIR) application to skin causes visible changes in normal and NMSC skin, to help delineate margins.

MATERIALS/METHODS

Eleven biopsy-proven NMSC lesions were included. The skin was then heated under a 175W NIR heating bulb; margins were traced onto acetate film before and after heating. Lesions were then randomly assigned to excision based on pre- or post-heating margins. Composite images were generated by overlaying the heat and no-heat lesion contours. All specimens were sent for histopathology.

RESULTS

The range of closest margins in the control group was 2.0-3.0 mm with a median of 2.0 mm; the range in the intervention group was 4.0-9.0 mm with a median of 5.0 mm. Composite images showed larger heat contours when the initial lesion was larger. There was a statistically significant difference between the two groups. Overall, NIR light caused visible hyperaemia to skin, and more intense erythema to malignant skin lesions.

CONCLUSION

Near-infrared light may have use in an outpatient setting for skin cancer delineation, possibly reducing the rate of positive margins.

Rapid and robust on-scene detection of cocaine in street samples using a handheld near-infrared spectrometer and machine learning algorithms

On‐scene drug detection is an increasingly significant challenge due to the fast‐changing drug market as well as the risk of exposure to potent drug substances. Conventional colorimetric cocaine tests involve handling of the unknown material and are prone to false‐positive reactions on common pharmaceuticals used as cutting agents. This study demonstrates the novel application of 740–1070 nm small‐wavelength‐range near‐infrared (NIR) spectroscopy to confidently detect cocaine in case samples. Multistage machine learning algorithms are used to exploit the limited spectral features and predict not only the presence of cocaine but also the concentration and sample composition. A model based on more than 10,000 spectra from case samples yielded 97% true‐positive and 98% true‐negative results. The practical applicability is shown in more than 100 case samples not included in the model design. One of the most exciting aspects of this on‐scene approach is that the model can almost instantly adapt to changes in the illicit‐drug market by updating metadata with results from subsequent confirmatory laboratory analyses. These results demonstrate that advanced machine learning strategies applied on limited‐range NIR spectra from economic handheld sensors can be a valuable procedure for rapid on‐site detection of illicit substances by investigating officers. In addition to forensics, this interesting approach could be beneficial for screening and classification applications in the pharmaceutical, food‐safety, and environmental domains.

Theoretical Investigation of Near-Infrared Fabry-Pérot Microcavity Graphene/Silicon Schottky Photodetectors Based on Double Silicon on Insulator Substrates

In this work a new concept of silicon resonant cavity enhanced photodetector working at 1550 nm has been theoretically investigated. The absorption mechanism is based on the internal photoemission effect through a graphene/silicon Schottky junction incorporated into a silicon-based Fabry–Pérot optical microcavity whose input mirror is constituted by a double silicon-on-insulator substrate. As output mirror we have investigated two options: a distributed Bragg reflector constituted by some periods of silicon nitride/hydrogenated amorphous silicon and a metallic gold reflector. In addition, we have investigated and compared two configurations: one where the current is collected in the transverse direction with respect to the direction of the incident light, the other where it is collected in the longitudinal direction. We show that while the former configuration is characterized by a better responsivity, spectral selectivity and noise equivalent power, the latter configuration is superior in terms of bandwidth and responsivity × bandwidth product. Our results show responsivity of 0.24 A/W, bandwidth in GHz regime, noise equivalent power of 0.6 nW/cm√Hz and full with at half maximum of 8.5 nm. The whole structure has been designed to be compatible with silicon technology.

Toward Visibly Transparent Organic Photovoltaic Cells Based on a Near-Infrared Harvesting Bulk Heterojunction Blend

Wavelength-selective harvesting by organic solar cells (OSCs) has attracted significant research attention due to the unique potential of these materials for smart photovoltaic window applications. Here, a visibly transparent OSC is demonstrated by utilizing both near-infrared (NIR)-absorbing polymer donor and nonfullerene acceptor (NFA) materials with narrow optical band gaps of less than 1.4 eV. Despite the substantial overlap in absorption spectra between the donor and acceptor, sufficient lowest unoccupied molecular orbital (LUMO) and highest occupied molecule orbital (HOMO) energy offsets for efficient charge separation with concurrent very low voltage losses yield a power conversion efficiency (PCE) of 9.13%. Moreover, with the introduction of an ultrathin Ag film (8 nm) as a transparent top electrode, semitransparent OSCs exhibit an excellent dual-side photovoltaic performance of 5.7 and 3.9% under bottom and top illumination, respectively, with high transmittance reaching 60% at wavelengths from 400 to 600 nm. This approach is expected to provide a new perspective in developing the highly efficient and transparent OSCs.

The Detection of Substitution Adulteration of Paprika with Spent Paprika by the Application of Molecular Spectroscopy Tools

The spice paprika (Capsicum annuum and frutescens) is used in a wide variety of cooking methods as well as seasonings and sauces. The oil, paprika oleoresin, is a valuable product; however, once removed from paprika, the remaining spent product can be used to adulterate paprika. Near-infrared (NIR) and Fourier transform infrared (FTIR) were the platforms selected for the development of methods to detect paprika adulteration in conjunction with chemometrics. Orthogonal partial least squares discriminant analysis (OPLS-DA), a supervised technique, was used to develop the chemometric models, and the measurement of fit (R²) and measurement of prediction (Q²) values were 0.853 and 0.819, respectively, for the NIR method and 0.943 and 0.898 respectively for the FTIR method. An external validation set was tested against the model, and a receiver operating curve (ROC) was created. The area under the curve (AUC) for both methods was highly accurate at 0.951 (NIR) and 0.907 (FTIR). The levels of adulteration with 100% correct classification were 50–90% (NIR) and 40–90% (FTIR). Sudan I dye is a commonly used adulterant in paprika; however, in this study it was found that this dye had no effect on the outcome of the result for spent material adulteration.

Tissue oxygenation indices of cerebrovascular autoregulation in healthy volunteers: a comparison of two NIRS devices

BACKGROUND

Correlation coefficients between blood pressure and cerebral oxygen saturation measured using near-infrared spectrometry may be used to derive the tissue oximetry index of cerebral autoregulation. Cerebral oxygen saturations demonstrate poor agreement between near-infrared spectrometers however it is unclear if measurements of autoregulation are similarly specific to the equipment used.

METHODS

Cerebral oxygen saturation was monitored bilaterally in 74 healthy volunteers using both the FORE-SIGHT and EQUANOX monitors in random order. The tissue oximetry index was calculated during changes in blood pressure induced by isometric handgrip manoeuvres and the mean bias and limits of agreement were calculated.

RESULTS

Tissue oximetry index measured by FORE-SIGHT was higher than EQUANOX (0.21 ± 0.16 versus 0.15 ± 0.17, P < 0.001) and limits of agreement were -0.24 to 0.36. Baseline cerebral oxygen saturation by FORE-SIGHT was lower than EQUANOX by 1.48% (CI95% 0.63-2.33) and limits of agreement ranged from -11.8% to 8.8%.

CONCLUSIONS

The substantial bias and wide limits of agreement for the tissue oximetry index as a measure of cerebral autoregulation indicate that values must be treated as specific to models of near-infrared spectrometers.

Comparison of Individual and Integrated Inline Raman, Near-Infrared, and Mid-Infrared Spectroscopic Models to Predict the Viscosity of Micellar Liquids

In many industries, viscosity is an important quality parameter which significantly affects consumer satisfaction and process efficiency. In the personal care industry, this applies to products such as shampoo and shower gels whose complex structures are built up of micellar liquids. Measuring viscosity offline is well established using benchtop rheometers and viscometers. The difficulty lies in measuring this property directly in the process via on or inline technologies. Therefore, the aim of this work is to investigate whether proxy measurements using inline vibrational spectroscopy, e.g., near-infrared (NIR), mid-infrared (MIR), and Raman, can be used to predict the viscosity of micellar liquids. As optical techniques, they are nondestructive and easily implementable process analytical tools where each type of spectroscopy detects different molecular functionalities. Inline fiber optic coupled probes were employed; a transmission probe for NIR measurements, an attenuated total reflectance probe for MIR and a backscattering probe for Raman. Models were developed using forward interval partial least squares variable selection and log viscosity was used. For each technique, combinations of pre-processing techniques were trialed including detrending, Whittaker filters, standard normal variate, and multiple scatter correction. The results indicate that all three techniques could be applied individually to predict the viscosity of micellar liquids all showing comparable errors of prediction: NIR: 1.75 Pa s; MIR: 1.73 Pa s; and Raman: 1.57 Pa s. The Raman model showed the highest relative prediction deviation (RPD) value of 5.07, with the NIR and MIR models showing slightly lower values of 4.57 and 4.61, respectively. Data fusion was also explored to determine whether employing information from more than one data set improved the model quality. Trials involved weighting data sets based on their signal-to-noise ratio and weighting based on transmission curves (infrared data sets only). The signal-to-noise weighted NIR-MIR-Raman model showed the best performance compared with both combined and individual models with a root mean square error of cross-validation of 0.75 Pa s and an RPD of 10.62. This comparative study provides a good initial assessment of the three prospective process analytical technologies for the measurement of micellar liquid viscosity but also provides a good basis for general measurements of inline viscosity using commercially available process analytical technology. With these techniques typically being employed for compositional analysis, this work presents their capability in the measurement of viscosity-an important physical parameter, extending the applicability of these spectroscopic techniques.

Changes in facial moisture distribution and feelings of moisture/dryness among various environmental temperatures and humidities in summer and winter

BACKGROUND

As environmental conditions vary depending on area of residence, consideration of environmental temperature and humidity conditions is crucial for detection of actual skin conditions in daily life. In this study, we determined changes in facial moisture and sensory evaluation distributions in various environmental temperature and humidity conditions.

MATERIALS AND METHODS

An original near-infrared (NIR) imaging system was used to obtain moisture distributions. Sensory evaluations of feelings of moisture/dryness were graded, and changes were compared among 10 healthy Japanese female subjects in four different environmental temperature and humidity conditions (28°C, 60% RH; 28°C, 20% RH; 15°C, 60% RH; 15°C, 20% RH) in summer and winter.

RESULTS

Skin moisture was lower at high temperatures and higher at low temperatures. Feelings of dryness on bare skin were high in low humidity. Sensitivity of feelings of moisture and dryness was high around the center of the cheekbones between side of the eyes and the mouth, but the same was not true of the moisture distribution. Moisture level was lower in winter at high temperatures, especially under the eyes near the side of the nose ridge, while the sense of dryness was not strong. These divergences between sensory evaluation and moisture level indicate the presence of a "hidden dry situation."

CONCLUSION

Changes in moisture level and sensory evaluation scores in facial skin varied among environmental conditions, which differed between summer and winter, even under the same environmental temperature and humidity.

Near-Infrared Rewritable, Non-Volatile Subwavelength Absorber Based on Chalcogenide Phase Change Materials

Chalcogenide phase change materials enable the realization of novel, non-volatile, switchable electronic and photonic devices. In this paper, we propose a type of rewritable, non-volatile near infrared subwavelength absorber based on chalcogenide phase change materials. Our numerical simulations show that nearly perfect absorption more than 0.99 can be realized in the written state while the absorption of as-deposited or erased state is lower than 0.15 in the studied spectral range, leading to high contrast ratio of reflection more than 20 dB. Continuous tuning of the absorption spectra can be realized not only by varying the geometric parameters of the absorber but also by changing the crystallization ratio of the switched Ge2Sb2Te5 (GST). The proposed device may find widespread applications in optical modulation, beam steering and so on.

Detection and analysis of enamel cracks by ICG-NIR fluorescence dental imaging

Cracked teeth are the third most common cause of tooth loss, but there is no reliable imaging tool for the diagnosis of cracks. Here, we demonstrate the feasibility of indocyanine green near-infrared fluorescence (ICG-NIRF) dental imaging for the detection of enamel cracks and enamel-dentin cracks in vitro in the first (ICG-NIRF-I, 700-950 nm) and second (ICG-NIRF-II, 950-1700 nm) imaging windows with transmission excitation light, and compared ICG-NIRF with conventional NIR illumination-II (NIRi-II) and X-ray imaging. Dentin cracks were detected by CT scan, while most enamel cracks, undetectable under X-ray imaging, were clearly visible in NIR images. We found that ICG-NIRF-II detected cracks more effectively than NIRi-II, and that light orientation is an important factor for crack detection: an angled exposure obtained better image contrast of cracks than parallel exposure, as it created a shadow under the crack. Crack depth could be evaluated from the crack shadow in ICG-NIRF and NIRi-II images; from this shadow we could determine crack depth and discriminate enamel-dentin cracks from craze lines. Cracks could be observed clearly from ICG-NIRF images with 1-min ICG tooth immersion, although longer ICG immersion produced images with greater contrast. Overall, our data show that ICG-NIRF dental imaging is a useful tool for diagnosing cracked teeth at an early stage.

Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants

The normalized difference vegetation index (NDVI) is widely used in remote sensing to monitor plant growth and chlorophyll levels. Usually, a multispectral camera (MSC) or hyperspectral camera (HSC) is required to obtain the near-infrared (NIR) and red bands for calculating NDVI. However, these cameras are expensive, heavy, difficult to geo-reference, and require professional training in imaging and data processing. On the other hand, the RGBN camera (NIR sensitive RGB camera, simply modified from standard RGB cameras by removing the NIR rejection filter) have also been explored to measure NDVI, but the results did not exactly match the NDVI from the MSC or HSC solutions. This study demonstrates an improved NDVI estimation method with an RGBN camera-based imaging system (Ncam) and machine learning algorithms. The Ncam consisted of an RGBN camera, a filter, and a microcontroller with a total cost of only $70 ~ 85. This new NDVI estimation solution was compared with a high-end hyperspectral camera in an experiment with corn plants under different nitrogen and water treatments. The results showed that the Ncam with two-band-pass filter achieved high performance (R2 = 0.96, RMSE = 0.0079) at estimating NDVI with the machine learning model. Additional tests showed that besides NDVI, this low-cost Ncam was also capable of predicting corn plant nitrogen contents precisely. Thus, Ncam is a potential option for MSC and HSC in plant phenotyping projects.

Performance test methods for near-infrared fluorescence imaging

PURPOSE

Near-infrared fluorescence (NIRF) imaging using exogenous contrast has gained much attention as a technique for enhancing visualization of vasculature using untargeted agents, as well as for the detection and localization of cancer with targeted agents. In order to address the emerging need for standardization of NIRF imaging technologies, it is necessary to identify the best practices suitable for objective, quantitative testing of key image quality characteristics. Toward the development of a battery of test methods that are rigorous yet applicable to a wide variety of devices, we have evaluated techniques for phantom design, measurement, and calculation of specific performance metrics.

METHODS

Using a NIRF imaging system for indocyanine green imaging, providing excitation at 780 nm and detection above 830 nm, we explored methods to evaluate uniformity, field of view, spectral crosstalk, spatial resolution, depth of field, sensitivity, linearity, and penetration depth. These measurements were performed using fluorophore-doped multiwell plate and high turbidity planar phantoms, as well as a 3D-printed multichannel phantom and a USAF 1951 resolution target.

RESULTS AND CONCLUSIONS

Based on a wide range of approaches described in medical and fluorescence imaging literature, we have developed and demonstrated a cohesive battery of test methods for evaluation of fluorescence image quality in wide-field imagers. We also propose a number of key metrics that can facilitate direct, quantitative comparison of device performance. These methods have the potential to facilitate more uniform evaluation and inter-comparison of clinical and preclinical imaging systems than is typically achieved, with the long-term goal of establishing international standards for fluorescence image quality assessment.

Optimal imaging windows of indocyanine green-assisted near-infrared dental imaging with rat model and its comparison to X-ray imaging

In this study, we used rat animal model to compare the efficiency of indocyanine green (ICG)-assisted dental near-infrared fluorescence imaging with X-ray imaging, and we optimized the imaging window for both unerupted and erupted molars. The results show that the morphology of the dental structures was observed clearly from ICG-assisted dental images (especially through the endoscope). A better image contrast was easily acquired at the short imaging windows (<10 minutes) for unerupted and erupted molars. For unerupted molars, there is another optimized imaging window (48-96 hours) with a prominent glow-in-the-dark effect: only the molars remain bright. This study also revealed that the laser ablation of dental follicles can disrupt the molar development, and our method is able to efficiently detect laser-treated molars and acquire the precise morphology. Thus, ICG-assisted dental imaging has the potential to be a safer and more efficient imaging modality for the real-time diagnosis of dental diseases.

A Comparative Approach to Screen the Capability of Raman and Infrared (Mid- and Near-) Spectroscopy for Quantification of Low-Active Pharmaceutical Ingredient Content Solid Dosage Forms: The Case of Alprazolam

Content uniformity is a critical attribute for potent and low-dosage formulations of active pharmaceutical ingredient (API) that, in addition to the formulation parameters, plays pivotal role during pharmaceutical development and production. However, when API content is low, implementing a vibrational spectroscopic analytical tool to monitor the content and blend uniformity remains a challenging task. The aim of this study was to showcase the potentials of mid-infrared (MIR), near-infrared (NIR), and Raman spectroscopy for quantitative analysis of alprazolam (ALZ) in a low-content powder blends with lactose, which is used as a common diluent for tablets produced by direct compression. The offered approach might be further scaled up and exploited for potential application in the process analytical technology (PAT). Partial least square and orthogonal PLS (OPLS) methodologies were employed to build the calibration models from raw and processed spectral data (standard normal variate, first and second derivatives). The models were further compared regarding their main statistical indicators: correlation coefficients, predictivity, root mean square error of estimation (RMSEE), and root mean square error of cross-validation (RMSEEcv). All statistical models presented high regression and predictivity coefficients. The RMSEEcv for the optimal models was 1.118, 0.08, and 0.059% for MIR, NIR, and Raman spectroscopy, respectively. The scarce information content extracted from the ALZ NIR spectra and the major band overlapping with those from lactose monohydrate was the main culprit of poor accuracy in the NIR model, whereas the subsampling instrumental setup (resulting in a non-representative spectral acquisition of the sample) was regarded as a main limitation for the MIR-based calibration model. The OPLS models of the Raman spectra of the powder blends manifested favorable statistical indicators for the accuracy of the calibration model, probably due to the distinctive ALZ Raman pattern resulting in the largest number of predictive spectral points that were used for the mathematical modeling. Furthermore, the Raman scattering calibration model was optimized in narrower scanning range (1700-700 cm^-1) and its prediction power was evaluated (root mean square error of prediction, RMSEP = 0.03%). Thus, the Raman spectroscopy presented the most favorable statistical indicators in this comparative study and therefore should be further considered as a PAT for the quantitative determination of ALZ in low-content powder blends.

Detecting Low Concentrations of Nitrogen-Based Adulterants in Whey Protein Powder Using Benchtop and Handheld NIR Spectrometers and the Feasibility of Scanning through Plastic Bag

Nitrogen-rich adulterants in protein powders present sensitivity challenges to conventional combustion methods of protein determination which can be overcome by near Infrared spectroscopy (NIRS). NIRS is a rapid analytical method with high sensitivity and non-invasive advantages. This study developed robust models using benchtop and handheld spectrometers to predict low concentrations of urea, glycine, taurine, and melamine in whey protein powder (WPP). Effectiveness of scanning samples through optical glass and polyethylene bags was also tested for the handheld NIRS. WPP was adulterated up to six concentration levels from 0.5% to 3% w/w. The two spectrometers were used to obtain three datasets of 819 diffuse reflectance spectra each that were pretreated before linear discriminant analysis (LDA) and regression (PLSR). Pretreatment was effective and revealed important absorption bands that could be correlated with the chemical properties of the mixtures. Benchtop NIR spectrometer showed the best results in LDA and PLSR but handheld NIR spectrometers showed comparatively good results. There were high prediction accuracies and low errors attesting to the robustness of the developed PLSR models using independent test set validation. Both the plastic bag and optical glass gave good results with accuracies depending on the adulterant of interest and can be used for field applications.

Deep Trench Isolation and Inverted Pyramid Array Structures Used to Enhance Optical Efficiency of Photodiode in CMOS Image Sensor via Simulations

The photodiode in the backside-illuminated CMOS sensor is modeled to analyze the optical performances in a range of wavelengths (300-1100 nm). The effects of changing in the deep trench isolation depth (DTI) and pitch size (d) of the inverted pyramid array (IPA) on the peak value (OE_max.) of optical efficiency (OE) and its wavelength region are identified first. Then, the growth ratio (GR) is defined for the OE change in these wavelength ranges to highlight the effectiveness of various DTI and d combinations on the OEs and evaluate the OE difference between the pixel arrays with and without the DTI + IPA structures. Increasing DTI can bring in monotonous OE_max. increases in the entire wavelength region. For a fixed DTI, the maximum OE_max. is formed as the flat plane (d = 0 nm) is chosen for the top surface of Si photodiode in the RGB pixels operating at the visible light wavelengths; whereas different nonzero value is needed to obtain the maximum OE_max. for the RGB pixels operating in the near-infrared (NIR) region. The optimum choice in d for each color pixel and DTI depth can elevate the maximum GR value in the NIR region up to 82.2%.

Biomarkers of Muscle Metabolism in Peripheral Artery Disease: A Dynamic NIRS-Assisted Study to Detect Adaptations Following Revascularization and Exercise Training

We assessed whether muscle metabolism biomarkers (MMb) identified by near-infrared spectroscopy (NIRS) are valid for determining adaptations following revascularization or exercise training in peripheral artery disease (PAD). Eighteen patients (males n = 13; 69 ± 7 years) were randomized to receive revascularization (Rev = 6) or pain-free home-based exercise (Ex = 12). MMb were safely collected via a NIRS-assisted treadmill test as area-under-curve for the spectra of oxygenated (-oxy), deoxygenated (-deoxy), differential (-diff) and total (-tot) hemoglobin traces. MMb, ankle–brachial index (ABI), pain-free (PFWD) and 6-min (6MWD) walking distances were assessed at baseline and after four months. MMb were correlated at baseline with ABI (MMb-oxy r = 0.46) and 6MWD (MMb-tot r = 0.51). After treatments, MMb-oxy showed an expected increase, which was more relevant for Rev group than the Ex (56% vs. 20%), with trends towards normalization for the other MMb. These changes were significantly correlated with variations in ABI (MMb-oxy r = 0.71; p = 0.002) and 6MWD (MMb-tot r = 0.58; p = 0.003). The MMb-diff in Rev group and MMb-deoxy in Ex group at baseline predicted clinical outcomes being correlated with PFWD improvements after 4-month (r = −0.94; p = 0.005 and r = −0.57; p = 0.05, respectively). A noninvasive NIRS-based test, feasible in a clinical setting, identified muscle metabolism biomarkers in PAD. The novel MMb were associated with validated outcome measures, selectively modified after different interventions and able to predict long-term functional improvements after surgery or exercise training.

A novel photostable near-infrared-to-near-infrared fluorescent nanoparticle for in vivo imaging

Water-soluble K₅ HoLi₂ F₁₀ (KHLF) nanoprobes with the excitation and emission both in the near-infrared (NIR) region were developed and first demonstrated for in vivo imaging of living mice. The PEG₄₀₀ coating endows the nanoprobes with good water solubility and biocompatibility. Doping with Ho³⁺ ions is capable of emitting NIR fluorescence with two peaks centered, respectively, at 887 and 1,180 nm once excited by a 808 nm laser; meanwhile, it also possess good photothermal conversion performance. The KHLF matrix with specifically structure of large ion-distance and low photon energy imparts the nanoprobes low quenching effect and excellent photostability (fluorescence decrease <5% upon 120 min illumination of 808 nm continuous laser with a power density of 1 W/cm² ). The nanoparticles (NPs) were tested for in vitro bioimaging with living mice. The results show the NPs have low biotoxicity, rapid metabolism, normal biodistribution, together with the photothermal imaging performance and a high-contrast fluorescence images (signal-to-background ratio of 14:1). The superior performances of these nanoprobes in vivo imaging of mice proclaim the great potential of this type of probe for high-contrast imaging and photothermal treatment in practical applications.

Layer Morphology and Ink Compatibility of Silver Nanoparticle Inkjet Inks for Near-Infrared Sintering

The field of printed electronics is rapidly evolving, producing low cost applications with enhanced performances with transparent, stretchable properties and higher reliability. Due to the versatility of printed electronics, industry can consider the implementation of electronics in a way which was never possible before. However, a post-processing step to achieve conductive structures-known as sintering-limits the production ease and speed of printed electronics. This study addresses the issues related to fast sintering without scarifying important properties such as conductivity and surface roughness. A drop-on-demand inkjet printer is employed to deposit silver nanoparticle-based inks. The post-processing time of these inks is reduced by replacing the conventional oven sintering procedure with the state-of-the-art method, named near-infrared sintering. By doing so, the post-processing time shortens from 30-60 min to 6-8 s. Furthermore, the maximum substrate temperature during sintering is reduced from 200 °C to 120 °C. Based on the results of this study, one can conclude that near-infrared sintering is a ready-to-industrialize post-processing method for the production of printed electronics, capable of sintering inks at high speed, low temperature and with low complexity. Furthermore, it becomes clear that ink optimization plays an important role in processing inkjet printable inks, especially after being near-infrared sintered.

Dopamine-Modified Zero-Valent Iron Nanoparticles for Dual-Modality Photothermal and Photodynamic Breast Cancer Therapy

Phototherapy has the advantages of minimal invasion, few side effects, and improved accuracy for cancer therapy. The application of a polydopamine (PDA)-modified nano zero-valent iron (nZVI@PDA) as a new synergistic agent in combination with photodynamic/photothermal (PD/PT) therapy to kill cancer cells is discussed here. The nZVI@PDA offered high light-to-heat conversion and ROS generation efficiency under near-infrared (NIR) irradiation (808 nm), thus leading to irreversible damage to nZVI@PDA-treated MCF-7 cells at low concentration, without inducing apoptosis in normal cells. Irradiation of nZVI@PDA using an NIR laser converted the energy of the photons to heat and ROS. Our results showed that modification of the PDA on the surface of nZVI can improve the biocompatibility of the nZVI@PDA. This work integrated the PD and PT effects into a single nanodevice to afford a highly efficient cancer treatment. Meanwhile, nZVI@PDA, which combines the advantages of PDA and nZVI, displayed excellent biocompatibility and tumoricidal ability, thus suggesting its huge potential for future clinical research in cancer therapy.

Highly Efficient Near-Infrared Light-Emitting Diodes Based on Chloride Treated CdTe/CdSe Type-II Quantum Dots

Quantum dot light-emitting diodes (QLEDs) have been considered as the most promising candidate of light sources for the new generation display and solid-state lighting applications. Especially, the performance of visible QLEDs based on II-VI quantum dots (QDs) has satisfied the requirements of the above applications. However, the optoelectronic properties of the corresponding near-infrared (NIR) QLEDs still lag far behind the visible ones. Here, we demonstrated the highly efficient NIR QLEDs based on chloride treated CdTe/CdSe type-II QDs. The maximum radiant emittance and peak external quantum efficiency (EQE) increased by 24.5 and 26.3%, up to 66 mW/cm² and 7.2% for the corresponding devices based on the chloride treated CdTe/CdSe QDs with the PL peak located at 788 nm, respectively, compared with those of devices before chloride treatment. Remarkably, the EQE of > 5% can be sustained at the current density of 0.3–250 mA/cm² after the chloride treatment. Compared with NIR LEDs based on transition metal complex, the efficiency roll-off has been suppressed to some extent for chloride treated CdTe/CdSe based NIR QLEDs. Based on the optimized conditions, the peak EQE of 7.4, 5.0, and 1.8% can be obtained for other devices based on chloride treated CdTe/CdSe with PL peak of 744, 852, and 910 nm, respectively. This improved performance can be mainly attributed to the chloride surface ligand that not only increases the carrier mobility and reduces the carrier accumulation, but also increases the probability of electron-hole radiative efficiency within QD layers.

UV-Vis-NIR Full-Range Responsive Carbon Dots with Large Multiphoton Absorption Cross Sections and Deep-Red Fluorescence at Nucleoli and In Vivo

Carbon dots (CDs), with excellent optical property and cytocompatibility, are an ideal class of nanomaterials applied in the field of biomedicine. However, the weak response of CDs in the near-infrared (NIR) region impedes their practical applications. Here, UV-vis-NIR full-range responsive fluorine and nitrogen doped CDs (N-CDs-F) are designed and synthesized that own a favorable donor-π-acceptor (D-π-A) configuration and exhibit excellent two-photon (λ_ex = 1060 nm), three-photon (λ_ex = 1600 nm), and four-photon (λ_ex = 2000 nm) excitation upconversion fluorescence. D-π-A-conjugated CDs prepared by solvothermal synthesis under the assistance of ammonia fluoride are reported and are endowed with larger multiphoton absorption (MPA) cross sections (3PA: 9.55 × 10^-80 cm⁶ s² photon^-2 , 4PA: 6.32 × 10^-80 cm⁸ s³ photon^-3 ) than conventional organic compounds. Furthermore, the N-CDs-F show bright deep-red to NIR fluorescence both in vitro and in vivo, and can even stain the nucleoli of tumor cells. A plausible mechanism is proposed on the basis of the strong inter-dot and intra-dot hydrogen bonds through NH···F that can facilitate the expanding of conjugated sp² domains, and thus not only result in lower highest occupied molecular orbital-lowest unoccupied molecular orbital energy level but also larger MPA cross sections than those of undoped CDs.

A mini-review on rare-earth down-conversion nanoparticles for NIR-II imaging of biological systems

Rare-earth (RE) based luminescent probes exhibit rich optical properties including upconversion and down-conversion luminescence spanning a broad spectral range from 300 to 3,000 nm, and have generated great scientific and practical interest from telecommunication to biological imaging. While upconversion nanoparticles have been investigated for decades, down-conversion luminescence of RE-based probes in the second near-infrared (NIR-II, 1,000-1,700 nm) window for in vivo biological imaging with sub-centimeter tissue penetration and micrometer image resolution has come into light only recently. In this review, we present recent progress on RE-based NIR-II probes for in vivo vasculature and molecular imaging with a focus on Er3+-based nanoparticles due to the down-conversion luminescence at the long-wavelength end of the NIR-II window (NIR-IIb, 1,500-1,700 nm). Imaging in NIR-IIb is superior to imaging with organic probes such as ICG and IRDye800 in the ~ 800 nm NIR range and the 1,000-1,300 nm short end of NIR-II range, owing to minimized light scattering and autofluorescence background. Doping by cerium and other ions and phase engineering of Er3+-based nanoparticles, combined with surface hydrophilic coating optimization can afford ultrabright, biocompatible NIR-IIb probe towards clinical translation for human use. The Nd3+-based probes with NIR-II emission at 1,050 and 1,330 nm are also discussed, including Nd3+ doped nanocrystals and Nd3+-organic ligand complexes. This review also points out future directions for further development of multi-functional RE NIR-II probes for biological imaging.

Models for the rapid assessment of water and oil content in olive pomace by near-infrared spectrometry

BACKGROUND

The measurement of the water and oil content in olive pomace is crucial for controlling the olive-oil extraction process. The use of near-infrared (NIR) spectra could allow the measurement of the oil and water content in olive pomace.

RESULTS

Partial least squares for pomace oil content on a dry basis reached an error of 2.5% (±0.5). Principal component regression for pomace oil content on a wet basis reached an error of 3.7% (±0.5). Both were suitable for quantitative analysis. Principal component regression for pomace water content reached an error of 6.0% (±2.3), suitable for process control. The relationship between 'ratio of standard deviation of calibration data to standard error of prediction data' and 'range of confident prediction error percentage' was investigated, it results of hyperbolic type, the constant of the hyperbolic equation depends on the product under analysis: for the olive pomace this constant is equal to 45.60 (±1.78).

CONCLUSION

Near-infrared analysis confirmed the possibility of determining the oil and water content in the olive pomace, which is important in the olive oil extraction process control. A new algorithm was used, together with standard statistical algorithms, to identify and remove the less useful wavelengths from the model, improving the overall prediction performance. A new parameter (the 'range of confident prediction error percentage') has been proposed for estimating the model's prediction error in an objective way. © 2020 Society of Chemical Industry.