Near-infrared Transmission Research Articles

Convolution Neural Network Application in the Simultaneous Detection of Gender and Variety of Silkworm (Bombyx mori) Cocoons

Convolution neural network (CNN) has been widely studied in the field of computer vision with good results, and a lot of research is still needed to show its application effect in the near-infrared spectroscopy with 1-D input data and small sample set. In this paper, the near-infrared diffuse transmission spectra of 2386 silkworm (Bombyx mori) cocoons from the 4th day of cocooning to the 13th day before turning into moths were collected. After the mean center preprocessing, CNN, SVM and LDA were used to model and analyze. Experimental results showed that, with the convolution kernel width 100, the convolution kernel num 16, and the stride 50, the good generalization effect of CNN model can be achieved when the simple structure of 6 layers without pooling layer was adopted. For each day, the gender prediction accuracy of cocoons is more than 90% and the highest accuracy is 100% on the 6th day with optimal model CNN. For each day, the variety prediction accuracy of cocoons is more than 98% and the highest accuracy is 100% with optimal model LDA. There is no significant correlation between pupa age and the gender and variety detection accuracy of silkworm cocoons. This can help broaden the pupa gender identification time in the actual production of silkworm egg farms. In the application of simultaneous identification of gender and variety, CNN model has the highest accuracy of 94%, LDA model has the medium accuracy of 92.5%, and SVM model has the lowest accuracy of 89.5%.

Determination of damage Rate of Sunn pests (Eurygaster spp. and Aelia spp.) in Bread Wheat Varieties in Karatay (KONYA) District

Abstract The study was carried out in order to determine the damage rate of Sunn pests ( Eurygaster spp. and Aelia spp.) in bread wheat varieties which brought to Konya Commodity Exchange and grown in 33 neighborhoods of Karatay which is the central district of Konya in during 2014-2018 harvest seasons. Samples were taken homogeneously from the bread wheat varieties brought to Konya Commodity Exchange from the neighborhoods with an automatic probe device in accordance with the ISO 24333 Sampling Standard. Analysis sample was taken from this sample in accordance with TS 2974 Wheat Standard and was cleaned and sieved from foreign materials. The grains that have been damaged by sunn pest damage have been determined, selected and weighed, and the damage rate of the grains by mass has been found. Protein and hectolitre values were also determined by measuring the remaining sample on the device working with the Near Infrared Transmission (NIT) principle. As a result of the research; In harvest season between 2014-2018, the average of Sunn pests damage in bread wheat coming from all districts of Karatay District is 1.1%, 0.8%, 0.9%, 0.9% and 1.1%, respectively determined as. It was determined to change that the average of sunn pest rate damage ranged between 0.8-1.5%, protein averages ranged between 12.7-14.1% and hectoliter weights between 76.8-79.4 kg in 2014-2018 harvest seasons.

FVSR-Net: an end-to-end Finger Vein Image Scattering Removal Network

Based on the ever-growing emphasis on high security of biometrics recognition, finger vein recognition has captured more and more attention. However, due to the light scattering in human skin tissue during near-infrared light transmission imaging, the collected finger vein images are always degraded dramatically, which leads to the unreliability of vein features and the low accuracy of finger vein recognition. Although considerable traditional methods are dedicated to eliminating the effect of light scattering on imaging, the clearer images cannot be output end-to-end, the processes of restoring degraded finger vein images are laborious as well. Thereupon, with the aim at improving the visibility of finger vein features and generating clear finger vein images end-to-end, this effort represents a simple and effective method utilizing Convolutional Neural Network (CNN). First, in our previous work, the biological optical model used to settle the matter of skin scattering is modified to output restored finger vein images in an end-to-end manner. Second, a multi-scale CNN named E-Net is established to acquire credible estimation map of finger vein features, which is conducive to the acquisition of pleasurable restoration outcome. Finally, a scattering removal framework, addressed as Finger Vein Image Scattering Removal Network (FVSR-Net), is designed via integrating improved biological optical model with E-Net. Such a novel design facilitates the generation of clearer venous regions and increases computational efficiency and stability. Experiments accomplished on two finger vein datasets demonstrate the superiority of our proposed method in terms of visual quality and recognition performance.

How much anharmonicity is in vibrational spectra of CH3I and CD3I?

This work presents new experimental and theoretical insights on vibrational spectra of CH3I and CD3I in the liquid phase. For the first time, we provided the contributions from different vibrational modes to mid-infrared (MIR) and near-infrared (NIR) spectra and estimated the extent of anharmonicity in the MIR region. Direct comparison of the intensities from ATR-IR and NIR transmission spectra was possible due to normalization of ATR-IR spectra. As a reference for normalization, we applied the area of the νs(CH3)/νs(CD3) band recorded in transmission mode. Our results show that the corresponding vibrational modes of CH3I and CD3I have similar contributions to the total intensity (MIR + NIR), however, these contributions are distributed in a different way between MIR and NIR regions. As expected, most of intensity in MIR spectra originates from the fundamental transitions (>90%). The fundamental bands together with the first overtones and the binary combinations contribute to more than 99% of MIR intensity for both compounds. Therefore, reliable reconstruction of MIR spectra can be achieved by considering only these vibrational modes. On the other hand, accurate simulation of NIR spectra requires including the higher-order transitions. In the case of CD3I, the fourth-order transitions contribute to 12.7% of NIR intensity. The contributions from NIR region are significantly smaller than those from MIR range and were estimated to be 6.7% for CH3I and 2.3% for CD3I. The theoretical calculations provide a reasonable estimation of the total contribution from the fundamental bands. Yet, the calculated contributions from the anharmonic transitions are different from those obtained from the experimental data. MIR spectra of CH3I and CD3I reveal an unexpected increase in the intensity of some overtones and combination bands indicating the presence of Fermi resonances. These resonances are responsible for differences in contributions from the first overtones and binary combinations between CH3I and CD3I.

Numerical analysis of a thermally tunable spectrally selective absorber enabled by an all-dielectric metamirror.

In this Letter, we numerically propose a temperature-tunable, ultra-narrowband one-way perfect near-infrared radiation absorber with high transmission in the longer wavelength neighboring spectral range. We obtained this functionality by using a guided-mode resonance-based grating-waveguide metamirror that is comprised of silicon, a spacer dielectric, an absorbing semiconductor, and germanium. Within the ultra-narrow bandwidth of the guided-mode resonance excited at 1.16 µm with a full width at half-maximum of 3.3 nm, we confirmed perfect absorption when light is incident from one of the two opposite directions. Excitation from the opposite direction resulted in perfect reflection. The thickness of the entire structure is limited to about one third the operating wavelength. Furthermore, due to the temperature tunability of silicon and germanium the thermo-optical sensitivity was found to be approximately 0.068 nm/K. In addition to this spectral tunability, our proposed device supports transparency windows with 80% transmission in the higher wavelength ranges. Our device is highly promising in the applications of thermo-tunable modulators and obtaining single frequency near-infrared signals from broadband sources.

Acid number, viscosity and end-point detection in a multiphase high temperature polymerisation process using an online miniaturised MEMS Fabry-Pérot interferometer

Recent advances in the latest generation of MEMS (micro-electro-mechanical system) Fabry-Pérot interferometers (FPI) for near infrared (NIR) wavelengths has led to the development of ultra-fast and low cost NIR sensors with potential to be used by the process industry. One of these miniaturised sensors operating from 1350 to 1650 nm, was integrated into a software platform to monitor a multiphase solid-gas-liquid process, for the production of saturated polyester resins. Twelve batches were run in a 2 L reactor mimicking industrial conditions (24 h process, with temperatures ranging from 220 to 240 °C), using an immersion NIR transmission probe. Because of the multiphase nature of the reaction, strong interference produced by process disturbances such as temperature variations and the presence of solid particles and bubbles in the online spectra required robust pre-processing algorithms and a good long-term stability of the probe. These allowed partial least squares (PLS) regression models to be built for the key analytical parameters acid number and viscosity. In parallel, spectra were also used to build an end-point detection model based on principal component analysis (PCA) for multivariate statistical process control (MSPC). The novel MEMS-FPI sensor combined with robust chemometric analysis proved to be a suitable and affordable alternative for online process monitoring, contributing to sustainability in the process industry.

The widest broadband transmission spectrum (0.38–1.71μm) of HD 189733b from ground-based chromatic Rossiter–McLaughlin observations

Multiband photometric transit observations (spectro-photometric) have been used mostly so far to retrieve broadband transmission spectra of transiting exoplanets in order to study their atmospheres. An alternative method was proposed, and has only been used once, to recover broadband transmission spectra using chromatic Rossiter–McLaughlin observations. We use the chromatic Rossiter–McLaughlin technique on archival and new observational data obtained with the HARPS and CARMENES instruments to retrieve transmission spectra of HD 189733b. The combined results cover the widest retrieved broadband transmission spectrum of an exoplanet obtained from ground-based observation. Our retrieved spectrum in the visible wavelength range shows the signature of a hazy atmosphere, and also includes an indication for the presence of sodium and potassium. These findings all agree with previous studies. The combined visible and near-infrared transmission spectrum exhibits a strong steep slope that may have several origins, such as a super-Rayleigh slope in the atmosphere of HD 189733b, an unknown systematic instrumental offset between the visible and near-infrared, or a strong stellar activity contamination. The host star is indeed known to be very active and might easily generate spurious features in the retrieved transmission spectra. Using our CARMENES observations, we assessed this scenario and place an informative constraint on some properties of the active regions of HD 189733. We demonstrate that the presence of starspots on HD 189733 can easily explain our observed strong slope in the broadband transmission spectrum.

Infrared Spectra of the CH3NH3PbI3 Hybrid Perovskite: Signatures of Phase Transitions and of Organic Cation Dynamics

The high-resolution terahertz reflection and mid- and near-infrared transmission spectroscopic studies of CH3NH3PbI3 hybrid perovskite single crystals are performed for the temperature range from 5...

Superior optoelectrical properties of magnetron sputter-deposited cerium-doped indium oxide thin films for solar cell applications

Indium tin oxide (ITO) is the most commonly used front contact material for a variety of photovoltaic technologies. However, the presence of a high free carrier concentration in ITO thin films results in the well-known phenomenon of free carrier absorption in the near-infrared (NIR) region of the solar spectrum. This causes optical losses especially in those solar cells where the active layer is designed to preferentially absorb NIR photons. Therefore, a combination of high carrier mobility and high NIR transparency is desired for advanced transparent conductive oxides for substituting ITO in solar cells. In this work, cerium-doped indium oxide (ICeO) thin films are deposited by pulsed DC magnetron sputtering, giving a remarkable 137% improvement of the mobility (71 cm2 V−1 s−1) compared to the previous record value of 30 cm2 V−1 s−1 for DC magnetron sputtered cerium-doped ITO films on glass. When compared to conventional ITO films prepared in this work, the highest mobility of ICeO is found to be almost four times higher and also the NIR transmission is substantially enhanced. Theoretical modelling of the experimental results indicates that neutral impurity scattering limits the carrier mobility in our films. With the recent advancements in single and multi-junction organic and perovskite solar cells, the development of ICeO/glass substrates (as possible replacements for the commonly used ITO/glass substrates) demonstrates significant potential in minimizing optical losses in the NIR region.

Online milk composition analysis with an on-farm near-infrared sensor

On-farm monitoring of milk composition can support close control of the udder and metabolic health of individual dairy cows. In previous studies, near-infrared (NIR) spectroscopy applied to milk analysis has proven useful for predicting the main components of raw milk (fat, protein, and lactose). In this contribution, we present and evaluate a precise tool for online milk composition analysis on the farm. For each milking, the online analyzer automatically collects and analyses a representative milk sample. The system acquires the NIR transmission spectra of the milk samples in the wavelength range from 960 to 1690 nm and performs a milk composition prediction afterward.Over a testing period of 8 weeks, the sensor collected 1165 NIR transmittance spectra of raw milk samples originating from 36 cows for which reference values were obtained for fat, protein, and lactose. For the same online sensor system, two calibration scenarios were evaluated: training post-hoc prediction models based on a representative set of calibration samples (n = 319) acquired over the entire testing period, with different cows in the calibration and test set, and training real-time prediction models exclusively on the samples acquired in the first week of the testing period (n = 308).The obtained prediction models were thoroughly tested on all the remaining samples not included in the calibration sets (n respectively 846 and 857). For the post-hoc prediction models, this resulted in an overall prediction error (root-mean-squared error of prediction, RMSEP) smaller than 0.080% (all % are in wt/wt) for milk fat (range 1.5–6.3%), protein (2.6–4.3%) and lactose (4–5.1%), with a coefficient of determination R2 of 0.989, 0.947 and 0.689 for fat, protein, and lactose respectively. For the real-time prediction models, the RMSEP was smaller than 0.092% for milk fat and lactose, and 0.110% for protein, with an R2 of 0.989 (fat), 0.894 (protein) and 0.644 (lactose). The milk lactose predictions could be further improved (RMSEP = 0.088%, R2 = 0.675) by taking into account a cow-specific bias. The presented online sensor system using the real-time prediction approach can thus be used for detailed and autonomous on-farm monitoring of milk composition after each individual milking, as its accuracy is well within the requirements by the International Committee for Animal Recording (ICAR) for on-farm milk analyzers and even meet the standards for laboratory analysis systems for fat and lactose. For this real-time prediction approach, a drift was observed in the predictions, especially for protein. Therefore, further research on the development of online calibration maintenance techniques is required to correct for this model drift and further improve the performance of this sensor system.

Carcass Characteristics, Physicochemical Properties, and Texture and Microstructure of the Meat and Internal Organs of Carrier and King Pigeons.

Simple SummaryThe tradition of pigeon meat consumption dates back to ancient civilizations. Today, pigeons are a popular meat in the cuisines of China, North America, North Africa, and some European countries. The aim of this study was to compare carrier pigeons and pigeons of the King breed after three reproductive seasons for carcass weight and measurements, carcass composition, physicochemical characteristics, the texture, rheological properties and microstructure of meat, and some biometric characteristics of the digestive system. Significant differences (p < 0.05) were observed between the pigeon groups in terms of the carcass weight and measurements, carcass composition (except for breast muscle percentage), physicochemical (except for pH24 and redness of breast muscles) textural (except for cohesiveness and shear force), rheological, and microstructural characteristics, and more digestive system characteristics. These differences result primarily from the type of use. King pigeons are raised for meat, and carrier pigeons are used for flying.Pigeons have been the subject of research in the past, but the knowledge gained is incomplete and must be extended. The aim of the study was to provide information about differences in carcass weight and measurements, carcass composition, proximate chemical composition, acidity, electrical conductivity, color attributes, the texture, rheological properties and microstructure of the meat, and some biometric characteristics of the digestive system in carrier and King pigeons, and also to determine if the two compared breeds meet the expectations of pigeon meat consumers to the same extent. The study involved 40 carcasses from carrier pigeons and King pigeons after three reproductive seasons. The chemical composition was determined by near-infrared transmission (NIT) spectroscopy, color coordinates according to CIELab, the texture according to Texture Profile Analysis (TPA) and Warner–Bratzler (WB) tests, and the rheological properties of meat according to the relaxation test. The compared pigeon groups differed significantly (p < 0.05) in carcass weight and measurements, carcass composition (except breast muscle percentage), chemical composition (except leg muscle collagen content) and electrical conductivity, lightness (L*), yellowness (b*), chroma (C*) and hue angle (h*), textural characteristics (except cohesiveness and Warner‒Bratzler shear force), rheological properties, microstructure of the pectoralis major muscle, as well as the total length of intestine and its segments, duodenal diameter, weight of proventriculus, gizzard, liver, heart, and spleen. The sex of the birds had a significant (p < 0.05) effect on the carcass weight, chest circumference, carcass neck percentage, breast muscle collagen content, and caeca length. The genotype by sex interaction was significant (p < 0.05) for fat content, collagen content, hardness, sum of elastic moduli and sum of viscous moduli of the pectoralis major muscle, protein and collagen content of leg muscles, duodenal and caecal length, jejunal and ileal diameter, and spleen weight. The obtained results show a significant effect of genetic origin and sex on the nutritive and technological value of the meat, and on the digestive system development of the pigeons.

Hole-Assisted Solid Core Bragg Fibers With a High-Index-Contrast Cladding for Broadband Single-Polarization Operation

We propose a hole-assisted solid core Bragg fiber (SCBF) with a high-index-contrast cladding for near-infrared broadband single-polarization transmission in this article. The circular symmetry of a common SCBF is broken by the introduced air holes in the solid core for increasing the modal birefringence and polarization-dependent loss (PDL). In the proposed single-polarization SCBF, the confinement of guided modes predominantly depends on the photonic bandgap effect from the high-index-contrast cladding, and simultaneously rests with the total internal reflection from the interface between the solid core and air holes. The numerical results show that both the enhanced modal birefringence and PDL are strongly related to the refractive index, size and locations of air holes. We demonstrate that the modal birefringence for the fundamental mode can be up to the order of 10−3, and the difference in confinement losses between both polarized fundamental modes is no less than an order of magnitude, which is sufficiently large to support single-polarization operation. Moreover, the single-polarization bandwidth with the transmission loss lower than 0.1 dB/m is as high as 277 nm and the critical bend radius is as low as 1 cm, indicating the excellent performances of high bandwidth and bending resistance in the hole-assisted single-polarization SCBF.

Abstract A15: Prenatal exposure to polycyclic aromatic hydrocarbons and breast tissue composition in adolescent girls

Abstract Polycyclic aromatic hydrocarbons (PAH) are common environmental pollutants that result from incomplete combustion of biomass and fossil fuels. PAH have endocrine-disrupting properties and are known animal carcinogens. Evidence from case-control studies suggests an association between PAH and breast cancer risk, but longitudinal research on PAH exposure during critical windows of susceptibility, such as prenatally and in early life, is limited. The purpose of this study was to prospectively examine whether prenatal exposure to PAH is associated with breast tissue composition, an intermediate marker of breast cancer risk, in adolescent girls. We studied 105 adolescent girls in the Columbia Center for Children’s Environmental Health (CCCEH) birth cohort, which recruited nonsmoking African American and Dominican American pregnant women living in three low-income neighborhoods in New York City from 1998-2006. Women wore a small backpack holding a personal air monitor for 2 consecutive days during the 3rd trimester of pregnancy, which measured concentrations of pyrene and 8 other carcinogenic PAH (summed and categorized into tertiles for analysis). Girls completed a follow-up clinic visit in adolescence (ages 11.2-19.6 years, median=15.8), at which time breast tissue composition was measured by optical spectroscopy (OS). OS is a novel and noninvasive tool that provides a broad compositional view of the breast by capturing variation in the amount of water, lipid, oxy-hemoglobin, deoxy-hemoglobin, and collagen, as well as overall cellular and connective tissue density. OS measured red and near-infrared light transmission of 7 wavelengths (650-1060 nm) at 4 source-detector distances in each breast quadrant, resulting in 16 overlapping tissue volumes. Principal component analysis was used to reduce spectral data and generate principal component (PC) scores for each participant, which were averaged over both breasts. We used multivariable linear regression to examine associations of prenatal PAH measures (pyrene and Σ8 PAH) with each of the first 4 OS PCs, which explained &amp;gt;99% of the spectral variation in the sample. Models were adjusted for age, ethnicity, body mass index (BMI) at time of OS measurement, age at breast development, and mothers’ prepregnancy BMI. After adjusting for covariates, PC1 scores were significantly lower on average in the highest compared to lowest tertile of prenatal ambient Σ8 PAH (β = -0.42, 95% CI = -0.81 to -0.02, p = 0.04). PC1 covered 91.8% of the spectral variations and represents overall light attenuation from higher scattering due to higher cellularity and connective tissues. PC1 also mapped to multiple chromophores including hemoglobin and collagen. No associations were found between prenatal ambient Σ8 PAH and PCs 2-4, and no associations with OS PCs were found for pyrene. To conclude, we found evidence suggesting that prenatal exposure to PAH is associated with breast tissue composition in adolescent girls. Citation Format: Rebecca D. Kehm, Lothar Lilge, E. Jane Walter, Nur Zeinomar, Jasmine A. McDonald, Parisa Tehranifar, Julie B. Herbstman, Rachel L. Miller, Mary Beth Terry. Prenatal exposure to polycyclic aromatic hydrocarbons and breast tissue composition in adolescent girls [abstract]. In: Proceedings of the AACR Special Conference on Environmental Carcinogenesis: Potential Pathway to Cancer Prevention; 2019 Jun 22-24; Charlotte, NC. Philadelphia (PA): AACR; Can Prev Res 2020;13(7 Suppl): Abstract nr A15.

Assessment of supervised machine learning for atmospheric retrieval of exoplanets

ABSTRACT Atmospheric retrieval of exoplanets from spectroscopic observations requires an extensive exploration of a highly degenerate and high-dimensional parameter space to accurately constrain atmospheric parameters. Retrieval methods commonly conduct Bayesian parameter estimation and statistical inference using sampling algorithms such as Markov chain Monte Carlo or Nested Sampling. Recently several attempts have been made to use machine learning algorithms either to complement or to replace fully Bayesian methods. While much progress has been made, these approaches are still at times unable to accurately reproduce results from contemporary Bayesian retrievals. The goal of this work is to investigate the efficacy of machine learning for atmospheric retrieval. As a case study, we use the Random Forest supervised machine learning algorithm which has been applied previously with some success for atmospheric retrieval of the hot Jupiter WASP-12b using its near-infrared transmission spectrum. We reproduce previous results using the same approach and the same semi-analytic models, and subsequently extend this method to develop a new algorithm that results in a closer match to a fully Bayesian retrieval. We combine this new method with a fully numerical atmospheric model and demonstrate excellent agreement with a Bayesian retrieval of the transmission spectrum of another hot Jupiter, HD 209458b. Despite this success, and achieving high computational efficiency, we still find that the machine learning approach is computationally prohibitive for high-dimensional parameter spaces that are routinely explored with Bayesian retrievals with modest computational resources. We discuss the trade-offs and potential avenues for the future.

Optical to Near-infrared Transmission Spectrum of the Warm Sub-Saturn HAT-P-12b

Abstract We present the transmission spectrum of HAT-P-12b through a joint analysis of data obtained from the Hubble Space Telescope Space Telescope Imaging Spectrograph and Wide Field Camera 3 and Spitzer, covering the wavelength range 0.3–5.0 μm. We detect a muted water vapor absorption feature at 1.4 μm attenuated by clouds, as well as a Rayleigh scattering slope in the optical indicative of small particles. We interpret the transmission spectrum using both the state-of-the-art atmospheric retrieval code SCARLET and the aerosol microphysics model CARMA. These models indicate that the atmosphere of HAT-P-12b is consistent with a broad range of metallicities between several tens to a few hundred times solar, a roughly solar C/O ratio, and moderately efficient vertical mixing. Cloud models that include condensate clouds do not readily generate the submicron particles necessary to reproduce the observed Rayleigh scattering slope, while models that incorporate photochemical hazes composed of soot or tholins are able to match the full transmission spectrum. From a complementary analysis of secondary eclipses by Spitzer, we obtain measured depths of 0.042% ± 0.013% and 0.045% ± 0.018% at 3.6 and 4.5 μm, respectively, which are consistent with a blackbody temperature of 890+60 −70 K and indicate efficient day–night heat recirculation. HAT-P-12b joins the growing number of well-characterized warm planets that underscore the importance of clouds and hazes in our understanding of exoplanet atmospheres.

The Influence of Stellar Contamination on the Interpretation of Near-infrared Transmission Spectra of Sub-Neptune Worlds around M-dwarfs

Abstract The impact of unocculted stellar surface heterogeneities in the form of cool spots and hot faculae on the spectrum of a transiting planet has been a daunting problem for the characterization of exoplanet atmospheres. The wavelength-dependent nature of stellar surface heterogeneities imprinting their signatures on planetary transmission spectra are of concern particularly for systems of sub-Neptunes orbiting M-dwarfs. Here we present a systematic exploration of the impact of this spot-contamination on simulated near-infrared transmission spectra of sub-Neptune planets. From our analysis, we find that improper correction for stellar surface heterogeneities on transmission spectra can lead to significant bias when inferring planetary atmospheric properties. However, this bias is negligible for lower fractions of heterogeneities (&lt;1%). Additionally, we find that acquiring a priori knowledge of stellar heterogeneities does not improve precision in constraining planetary parameters if the heterogeneities are appropriately marginalized within a retrieval; however, these are conditional on our confidence of stellar atmospheric models being accurate representations of the true photosphere. In sum, to acquire unbiased constraints when characterizing planetary atmospheres with the James Webb Space Telescope, we recommend performing joint retrievals of both the disk-integrated spectrum of the star and the stellar-contamination-corrected transmission spectrum.

Efficient Super Broadband NIR Ca2LuZr2Al3O12:Cr3+,Yb3+ Garnet Phosphor for pc‐LED Light Source toward NIR Spectroscopy Applications

AbstractSuper broadband near‐infrared (NIR) phosphor converted light‐emitting diodes (pc‐LEDs) are future light sources in NIR spectroscopy applications such as food testing. At present, a few blue LED excitable super broadband NIR phosphors (bandwidth &gt; 300 nm) have been developed producing the NIR output powers below 26 mW at 100 mA input current after LED packaging. Here, an efficient super broadband NIR phosphor achieved by doping Yb3+ is reported in the NIR Ca2LuZr2Al3O12:Cr3+ (CLZA:Cr3+) garnet phosphor developed previously. Benefited from the superposition of Cr3+ emission and highly efficient Yb3+ emission excited by energy transfer from Cr3+, the codoped CLZA:Cr3+,Yb3+ phosphor shows a bandwidth of 320 nm and an internal quantum efficiency of 77.2% both higher than that (150 nm and 69.1%) of singly doped CLZA:Cr3+ phosphor. The codoped phosphor converts LED produced 41.8 mW NIR output at 100 mA input current. The pc‐LED as a light source is also well applied to the NIR transmission spectra measurement of water. The results indicate the great potential of CLZA:Cr3+,Yb3+ phosphor in super broadband NIR pc‐LED applications.

Investigation on the coloring and bleaching processes of WO3−x photochromic thin films

WO3−x (oxygen deficient tungsten oxide) thin films and WO3−x/Ta2O5 (tantalum oxide) composite films exhibit a huge photochromic effect with 60% near-infrared transmission modulation.

Detection of Moldy Cores in Apples with Near-Infrared Transmission Spectroscopy Based on Wavelet and BP Network

Moldy cores in apples are not initially obvious from the outside of the fruit, so developing methods to detect moldy cores is an important area of research in the apple industry. The objective of this study was to improve the ability of near-infrared spectrometry to detect moldy cores in apples. Transmission spectra were recorded for 200 apple samples in the range of 200–1100[Formula: see text]nm, and 140 and 60 samples were randomly selected as training and test sets, respectively. Signal de-noising was performed by wavelet thresholding based on the results of orthogonal experiments. The best wavelengths for discriminating between healthy and diseased apples were selected by a successive projection algorithm (SPA). The extracted wavelengths were used as the input in a back propagation artificial neural network (BP-ANN). Through these experiments, this study compared the correct recognition rates using different ratios of training to test numbers in the model, and functions in the hidden and output layers of the BP-ANN. The proposed method achieved the highest accuracies of 95.00% and 95.71% for the test and training sets, respectively. This method could be used to develop a portable instrument for detecting moldy cores in apples.

Ultrafast dynamics of pure many-body effect and its competition with bandgap widening via electron–phonon coupling in PbTe thin films

Bandgap renormalization (BGR), or bandgap narrowing effect, is one of the many-body effects predicted by many-body theory in semiconductor physics. However, pure BGR effect has never been observed experimentally although the mixed effect of BGR with lattice-heating induced bandgap narrowing was reported in GaAs and CdTe semiconductors. PbTe has a positive temperature coefficient of bandgap. Its lattice-heating induced bandgap narrowing can be eliminated so that the pure BGR effect is possibly observed. However, that has never been reported so far because the BGR effect is weak in PbTe due to its huge dielectric screening. We study the ultrafast dynamics of photo-excited carriers in PbTe films using near-infrared femtosecond-resolved transient differential transmission (TDT) spectroscopy. A complex oscillation-like damped decay dynamics is observed. A negative dip, a fingerprint signature of BGR effect, occurs immediately after the thermalization process of the photo-excited carriers. As such, we have observed a pure BGR effect in PbTe for the first time, strongly supporting the many-body theory. Meanwhile, we have also observed a dynamic transition from a transient absorption enhancement to absorption saturation, revealing the emergence of a slow lattice-heating induced bandgap widening via carrier-phonon couplings. Based on a two-temperature model, a simulation computation is carried out, supporting the lattice-heating induced bandgap widening leads to the dynamic transition. A phenomenological dynamic model is developed, including three dynamic components: the thermalization of the photo-excited carriers, recombination of the thermalized carriers and lattice-heating induced bandgap widening, and used to best fit the excitation-power dependent TDT dynamics. Time constants and strengths of the three dynamic components are obtained for different excitation powers. Time constant variation with the excitation power reveals different roles of the carrier–carrier and carrier-phonon scattering in the thermalizing process, as well as of free carrier and exciton recombination in the decaying process of hot carriers.