Infrared Imaging Using Thermally Stable HgTe/CdS Nanocrystals.

Transferring nanocrystals (NCs) from the laboratory environment toward practical applications has raised new challenges. HgTe appears as the most spectrally tunable infrared colloidal platform. Its low-temperature synthesis reduces the growth energy cost yet also favors sintering. Once coupled to a read-out circuit, the Joule effect aggregates the particles, leading to a poorly defined optical edge and large dark current. Here, we demonstrate that CdS shells bring the expected thermal stability (no redshift upon annealing, reduced tendency to form amalgams, and preservation of photoconduction after an atomic layer deposition process). The electronic structure of these confined particles is unveiled using k.p self-consistent simulations showing a significant exciton binding energy of ∼200 meV. After shelling, the material displays a p-type behavior that favors the generation of photoconductive gain. The latter is then used to increase the external quantum efficiency of an infrared imager, which now reaches 40% while presenting long-term stability.

Multiresonant Grating to Replace Transparent Conductive Oxide Electrode for Bias Selected Filtering of Infrared Photoresponse.

Optoelectronic devices rely on conductive layers as electrodes, but they usually introduce optical losses that are detrimental to the device performances. While the use of transparent conductive oxides is established in the visible region, these materials show high losses at longer wavelengths. Here, we demonstrate a photodiode based on a metallic grating acting as an electrode. The grating generates a multiresonant photonic structure over the diode stack and allows strong broadband absorption. The obtained device achieves the highest performances reported so far for a midwave infrared nanocrystal-based detector, with external quantum efficiency above 90%, detectivity of 7 × 1011 Jones at 80 K at 5 µm, and a sub-100 ns time response. Furthermore, we demonstrate that combining different gratings with a single diode stack can generate a bias reconfigurable response and develop new functionalities such as band rejection.

Mapping the Energy Landscape from a Nanocrystal-Based Field Effect Transistor under Operation Using Nanobeam Photoemission Spectroscopy.

As the field of nanocrystal-based optoelectronics matures, more advanced techniques must be developed in order to reveal the electronic structure of nanocrystals, particularly with device-relevant conditions. So far, most of the efforts have been focused on optical spectroscopy, and electrochemistry where an absolute energy reference is required. Device optimization requires probing not only the pristine material but also the material in its actual environment (i.e., surrounded by a transport layer and an electrode, in the presence of an applied electric field). Here, we explored the use of photoemission microscopy as a strategy for operando investigation of NC-based devices. We demonstrate that the method can be applied to a variety of materials and device geometries. Finally, we show that it provides direct access to the metal-semiconductor interface band bending as well as the distance over which the gate effect propagates in field-effect transistors.

Selection of highly responsive T cell receptors by an analysis combining the expression of multiple markers.

The clinical success of T cell receptor (TCR) gene-transduced T (TCR-T) cell therapy is expected as one of the next-generation immunotherapies for cancer, in which the selection of TCRs with high functional avidity (high-functional TCRs) is important. One widely used approach to select high-functional TCRs is a comparison of the EC50 values of TCRs, which involves laborious experiments. Therefore, the establishment of a simpler method to select high-functional TCRs is desired. We herein attempted to establish a simple method to select high-functional TCRs based on the expression of T cell activation markers using the mouse T cell line BW5147.3 (BW). We examined relationships between the EC50 values of TCRs in interleukin-2 production and the expression levels of TCR activation markers on BW cells. In TCR-expressing BW cells stimulated with antigenic peptides, the CD69, CD137, and PD-1 expression was differentially induced by various doses of peptides. An analysis of TCRs derived from the tumor-infiltrating lymphocytes of murine melanoma and peripheral blood T cells of hepatocellular carcinoma patients treated with a peptide vaccination revealed that an analysis combining CD69, CD137, and PD-1 expression levels in BW cells stimulated with a single dose of an antigenic peptide selected high-functional TCRs with functional avidity assessed by EC50 values. Our method facilitates the section of high-functional TCRs among tumor-reacting TCRs, which will promote TCR-T cell therapy. The stimulation of BW cells expressing objective TCRs with a single dose of antigenic peptides and analysis combining the expression of CD69, CD137, and PD-1 allows us to select highly responsive TCRs.

Mid-wave infrared sensitized InGaAs using intraband transition in doped colloidal II-VI nanocrystals.

Narrow bandgap nanocrystals (NCs) are now used as infrared light absorbers, making them competitors to epitaxially grown semiconductors. However, these two types of materials could benefit from one another. While bulk materials are more effective in transporting carriers and give a high degree of doping tunability, NCs offer a larger spectral tunability without lattice-matching constraints. Here, we investigate the potential of sensitizing InGaAs in the mid-wave infrared throughout the intraband transition of self-doped HgSe NCs. Our device geometry enables the design of a photodiode remaining mostly unreported for intraband-absorbing NCs. Finally, this strategy allows for more effective cooling and preserves the detectivity above 108 Jones up to 200 K, making it closer to cryo-free operation for mid-infrared NC-based sensors.

Helmholtz Resonator Applied to Nanocrystal-Based Infrared Sensing.

While the integration of nanocrystals as an active medium for optoelectronic devices progresses, light management strategies are becoming required. Over recent years, several photonic structures (plasmons, cavities, mirrors, etc.) have been coupled to nanocrystal films to shape the absorption spectrum, tune the directionality, and so on. Here, we explore a photonic equivalent of the acoustic Helmholtz resonator and propose a design that can easily be fabricated. This geometry combines a strong electromagnetic field magnification and a narrow channel width compatible with efficient charge conduction despite hopping conduction. At 80 K, the device reaches a responsivity above 1 A·W-1 and a detectivity above 1011 Jones (3 µm cutoff) while offering a significantly faster time-response than vertical geometry diodes.

Bias Tunable Spectral Response of Nanocrystal Array in a Plasmonic Cavity.

Nanocrystals (NCs) have gained considerable attention for their broadly tunable absorption from the UV to the THz range. Nevertheless, their optical features suffer from a lack of tunability once integrated into optoelectronic devices. Here, we show that bias tunable aspectral response is obtained by coupling a HgTe NC array with a plasmonic resonator. Up to 15 meV blueshift can be achieved from a 3 µm absorbing wavelength structure under a 3 V bias voltage when the NC exciton is coupled with a mode of the resonator. We demonstrate that the blueshift arises from the interplay between hopping transport and inhomogeneous absorption due to the presence of the photonic structure. The observed tunable spectral response is qualitatively reproduced in simulation by introducing a bias-dependent diffusion length in the charge transport. This work expands the realm of existing NC-based devices and paves the way toward light modulators.

Correlating Structure and Detection Properties in HgTe Nanocrystal Films.

HgTe nanocrystals (NCs) enable broadly tunable infrared absorption, now commonly used to design light sensors. This material tends to grow under multipodic shapes and does not present well-defined size distributions. Such point generates traps and reduces the particle packing, leading to a reduced mobility. It is thus highly desirable to comprehensively explore the effect of the shape on their performance. Here, we show, using a combination of electron tomography and tight binding simulations, that the charge dissociation is strong within HgTe NCs, but poorly shape dependent. Then, we design a dual-gate field-effect-transistor made of tripod HgTe NCs and use it to generate a planar p-n junction, offering more tunability than its vertical geometry counterpart. Interestingly, the performance of the tripods is higher than sphere ones, and this can be correlated with a stronger Te excess in the case of sphere shapes which is responsible for a higher hole trap density.

Stochastic Variational Inference for Bayesian Phylogenetics: A Case of CAT Model.

The pattern of molecular evolution varies among gene sites and genes in a genome. By taking into account the complex heterogeneity of evolutionary processes among sites in a genome, Bayesian infinite mixture models of genomic evolution enable robust phylogenetic inference. With large modern data sets, however, the computational burden of Markov chain Monte Carlo sampling techniques becomes prohibitive. Here, we have developed a variational Bayesian procedure to speed up the widely used PhyloBayes MPI program, which deals with the heterogeneity of amino acid profiles. Rather than sampling from the posterior distribution, the procedure approximates the (unknown) posterior distribution using a manageable distribution called the variational distribution. The parameters in the variational distribution are estimated by minimizing Kullback-Leibler divergence. To examine performance, we analyzed three empirical data sets consisting of mitochondrial, plastid-encoded, and nuclear proteins. Our variational method accurately approximated the Bayesian inference of phylogenetic tree, mixture proportions, and the amino acid propensity of each component of the mixture while using orders of magnitude less computational time.

Synthesis and solution studies of silver(I)-assembled porphyrin coordination cages.

The synthesis and the characterization of two porphyrin coordination cages are reported. The design of the cage formation is based on the coordination of silver(I) ions to the pyridyl units of 3-pyridyl appended porphyrins. (1)H/(109)Ag NMR spectroscopy, and diffusion-ordered spectroscopy (DOSY) experiments demonstrate that both the free base porphyrin 2H-TPyP and the Zn-porphyrin Zn-TPyP form the closed cages, [Ag4(2H-TPyP)2](4+) and [Ag4(Zn-TPyP)2](4+), respectively, upon addition of two equivalents of Ag(+). The complexation processes are characterized in details by means of absorption and emission spectroscopy in diluted CH2Cl2 solutions. The data are discussed in the frame of the point-dipole exciton coupling theory; the two porphyrin monomers, in fact, experience a rigid face-to-face geometry in the cages and a weak inter-porphyrin exciton coupling. An intermediate species is observed, for Zn-TPyP, in a porphyrin/Ag(+) stoichiometric ratio of about 1:0.5 and is tentatively ascribed to an oblique open form. The occurrence of a photoinduced electron-transfer reaction within the cages is excluded on the basis of the experimental outcomes and thermodynamic evaluations. Photophysical experiments evidence different reactivities of singlet and triplet excited states in the assemblies. A lower fluorescence quantum yield and triplet formation is discussed in relation to the constrained geometry of the complexes. Unusually long triplet excited state lifetimes are measured for the assemblies.

Safety and efficacy of autologous adipose tissue-derived stem cell transplantation in aging-related low-grade inflammation patients: a single-group, open-label, phase I clinical trial.

BACKGROUND: Inflamm-aging is associated with the rate of aging and is significantly related to diseases such as Alzheimer's disease, Parkinson's disease, atherosclerosis, heart disease, and age-related degenerative diseases such as type II diabetes and osteoporosis. This study aims to evaluate the safety and efficiency of autologous adipose tissue-derived mesenchymal stem cell (AD-MSC) transplantation in aging-related low-grade inflammation patients. METHODS: This study is a single-group, open-label, phase I clinical trial in which patients treated with 2 infusions (100 million cells i.v) of autologous AD-MSCs were initially evaluated in 12 inflamm-aging patients who concurrently had highly proinflammatory cytokines and 2 of the following 3 diseases: diabetes, dyslipidemia, and obesity. The treatment effects were evaluated based on plasma cytokines. RESULTS: During the study's follow-up period, no adverse effects were observed in AD-MSC injection patients. Compared to baseline (D-44), the inflammatory cytokines IL-1α, IL-1ß, IL-8, IL-6, and TNF-α were significantly reduced after 180 days (D180) of MSC infusion. IL-4/IL-10 at 90 days (D90) and IL-2/IL-10 at D180 increased, reversing the imbalance between proinflammatory and inflammatory ratios in the patients. CONCLUSION: AD-MSCs represent a potential intervention to prevent age-related inflammation in patients. TRIAL REGISTRATION: ClinicalTrials.gov number is NCT05827757, first registered on 13th Oct 2020.

Air-Stable Perylene Diimide Trimer Material for N-Type Organic Electrochemical Transistors.

A new method is reported to make air-stable n-type organic mixed ionic-electronic conductor (OMIEC) films for organic electrochemical transistors (OECTs) using a solution-processable small molecule helical perylene diimide trimer, hPDI[3]-C11. Alkyl side chains are attached to the conjugated core for processability and film making, which are then cleaved via thermal annealing. After the sidechains are removed, the hPDI[3] film becomes less hydrophobic, more ordered, and has a deeper lowest unoccupied molecular orbital (LUMO). These features provide improved ionic transport, greater electronic mobility, and increased stability in air and in aqueous solution. Subsequently, hPDI[3]-H is used as the active material in OECTs and a device with a transconductance of 44 mS, volumetric capacitance of ≈250 F cm-3, µC* value of 1 F cm-1 V-1 s-1, and excellent stability (> 5 weeks) is demonstrated. As proof of their practical applications, a hPDI[3]-H-based OECTs as a glucose sensor and electrochemical inverter is utilized. The approach of side chain removal after film formation charts a path to a wide range of molecular semiconductors to be used as stable, mixed ionic-electronic conductors.

oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data.

The complexity and high dimensionality of neuroimaging data pose problems for decoding information with machine learning (ML) models because the number of features is often much larger than the number of observations. Feature selection is one of the crucial steps for determining meaningful target features in decoding; however, optimizing the feature selection from such high-dimensional neuroimaging data has been challenging using conventional ML models. Here, we introduce an efficient and high-performance decoding package incorporating a forward variable selection (FVS) algorithm and hyper-parameter optimization that automatically identifies the best feature pairs for both classification and regression models, where a total of 18 ML models are implemented by default. First, the FVS algorithm evaluates the goodness-of-fit across different models using the k-fold cross-validation step that identifies the best subset of features based on a predefined criterion for each model. Next, the hyperparameters of each ML model are optimized at each forward iteration. Final outputs highlight an optimized number of selected features (brain regions of interest) for each model with its accuracy. Furthermore, the toolbox can be executed in a parallel environment for efficient computation on a typical personal computer. With the optimized forward variable selection decoder (oFVSD) pipeline, we verified the effectiveness of decoding sex classification and age range regression on 1,113 structural magnetic resonance imaging (MRI) datasets. Compared to ML models without the FVS algorithm and with the Boruta algorithm as a variable selection counterpart, we demonstrate that the oFVSD significantly outperformed across all of the ML models over the counterpart models without FVS (approximately 0.20 increase in correlation coefficient, r, with regression models and 8% increase in classification models on average) and with Boruta variable selection algorithm (approximately 0.07 improvement in regression and 4% in classification models). Furthermore, we confirmed the use of parallel computation considerably reduced the computational burden for the high-dimensional MRI data. Altogether, the oFVSD toolbox efficiently and effectively improves the performance of both classification and regression ML models, providing a use case example on MRI datasets. With its flexibility, oFVSD has the potential for many other modalities in neuroimaging. This open-source and freely available Python package makes it a valuable toolbox for research communities seeking improved decoding accuracy.

Lithium-Ion Glass Gating of HgTe Nanocrystal Film with Designed Light-Matter Coupling.

Nanocrystals' (NCs) band gap can be easily tuned over the infrared range, making them appealing for the design of cost-effective sensors. Though their growth has reached a high level of maturity, their doping remains a poorly controlled parameter, raising the need for post-synthesis tuning strategies. As a result, phototransistor device geometry offers an interesting alternative to photoconductors, allowing carrier density control. Phototransistors based on NCs that target integrated infrared sensing have to (i) be compatible with low-temperature operation, (ii) avoid liquid handling, and (iii) enable large carrier density tuning. These constraints drive the search for innovative gate technologies beyond traditional dielectric or conventional liquid and ion gel electrolytes. Here, we explore lithium-ion glass gating and apply it to channels made of HgTe narrow band gap NCs. We demonstrate that this all-solid gate strategy is compatible with large capacitance up to 2 µF·cm-2 and can be operated over a broad range of temperatures (130-300 K). Finally, we tackle an issue often faced by NC-based phototransistors:their low absorption; from a metallic grating structure, we combined two resonances and achieved high responsivity (10 A·W-1 or an external quantum efficiency of 500%) over a broadband spectral range.

Inside a nanocrystal-based photodiode using photoemission microscopy.

As nanocrystal-based devices gain maturity, a comprehensive understanding of their electronic structure is necessary for further optimization. Most spectroscopic techniques typically examine pristine materials and disregard the coupling of the active material to its actual environment, the influence of an applied electric field, and possible illumination effects. Therefore, it is critical to develop tools that can probe device in situ and operando. Here, we explore photoemission microscopy as a tool to unveil the energy landscape of a HgTe NC-based photodiode. We propose a planar diode stack to facilitate surface-sensitive photoemission measurements. We demonstrate that the method gives direct quantification of the diode's built-in voltage. Furthermore, we discuss how it is affected by particle size and illumination. We show that combining SnO2 and Ag2Te as electron and hole transport layers is better suited for extended-short-wave infrared materials than materials with larger bandgaps. We also identify the effect of photodoping over the SnO2 layer and propose a strategy to overcome it. Given its simplicity, the method appears to be of utmost interest for screening diode design strategies.

Using the WHO Self-Reporting Questionnaire-20 (SRQ-20) to Detect Symptoms of Common Mental Disorders among Pregnant Women in Vietnam: a Validation Study.

Purpose: Detection of antenatal common mental disorders in low-resource settings like Vietnam is important and requires a reliable, valid and practical screening tool. Currently, there is no such tool validated for use among pregnant women in Vietnam. This study aims to assess the validity of the Vietnamese version of the 20-item Self Reporting Questionnaire (SRQ-20) by evaluating its reliability, factorial structure, and performance in detecting common mental disorder (CMD) symptoms, thereby identifying the optimum cut-off score for CMD screening among pregnant women in Vietnam. Participants and Methods: A total of 210 pregnant women from four rural communes participated in a face-to-face interview using the Vietnamese version of the SRQ-20, followed by a clinical diagnostic interview based on ICD-10 diagnostic criteria of CMDs. The reliability of the SRQ-20 was assessed by calculating the scale's Cronbach's alpha to measure internal consistency. Factor analyses were undertaken to examine the factor structure of the instrument. The Receiver Operating Characteristic (ROC) curve analysis was performed to assess the performance of the SRQ-20 against the clinical diagnosis and to identify the optimum cut-off score. Results: Internal consistency was good, with a Cronbach's alpha of 0.87. Factor analyses resulted in a 4-factor solution. The area under the ROC curve (AUC) for detection of CMDs was 0.90. The optimum cut-off score of the SRQ-20 for detection of CMD symptoms among Vietnamese pregnant women was 5/6. Conclusion: The Vietnamese version of the SRQ-20 has the capacity to detect CMDs among pregnant women effectively and is recommended for use as a screening tool for CMDs in antenatal care settings in Vietnam.

Stochastic variational variable selection for high-dimensional microbiome data.

BACKGROUND: The rapid and accurate identification of a minimal-size core set of representative microbial species plays an important role in the clustering of microbial community data and interpretation of clustering results. However, the huge dimensionality of microbial metagenomics datasets is a major challenge for the existing methods such as Dirichlet multinomial mixture (DMM) models. In the approach of the existing methods, the computational burden of identifying a small number of representative species from a large number of observed species remains a challenge. RESULTS: We propose a novel approach to improve the performance of the widely used DMM approach by combining three ideas: (i) we propose an indicator variable to identify representative operational taxonomic units that substantially contribute to the differentiation among clusters; (ii) to address the computational burden of high-dimensional microbiome data, we propose a stochastic variational inference, which approximates the posterior distribution using a controllable distribution called variational distribution, and stochastic optimization algorithms for fast computation; and (iii) we extend the finite DMM model to an infinite case by considering Dirichlet process mixtures and estimating the number of clusters as a variational parameter. Using the proposed method, stochastic variational variable selection (SVVS), we analyzed the root microbiome data collected in our soybean field experiment, the human gut microbiome data from three published datasets of large-scale case-control studies and the healthy human microbiome data from the Human Microbiome Project. CONCLUSIONS: SVVS demonstrates a better performance and significantly faster computation than those of the existing methods in all cases of testing datasets. In particular, SVVS is the only method that can analyze massive high-dimensional microbial data with more than 50,000 microbial species and 1000 samples. Furthermore, a core set of representative microbial species is identified using SVVS that can improve the interpretability of Bayesian mixture models for a wide range of microbiome studies. Video Abstract.

Binder Selection to Modify Hydrocarbon Cracking Properties of Zeolite-Containing Composites.

Activity, selectivity, and deactivation behavior of catalyst materials determine their efficiency in hydrocarbon conversion processes. For hydrocarbon cracking, the industrial catalyst is an important parameter in reaction technology to produce valuable compounds, e.g., light olefins (C3-C5) and gasoline from crude oil fractions with high molecular weight (C16+). One strategy to enhance the catalytic activity for precracking is increasing the matrix activity, which depends on the used binder and additives. In this work, three binders (water glass, aluminum chloride, and a mixture of colloidal silica with aluminum dihydrogen phosphate) were used in combination with active zeolite Y, kaolin as filler, and ZSM-5 as additive to produce composite materials. Specific surface area and surface acidity measurements were combined with catalytic testing of the formulated samples in order to find the relation between the catalyst morphology and its activity. In addition, constraint index was used as a control parameter for the determination of the shape-selective properties and their correlation with the catalytic activity. The results show that the binders determine the porosity of the matrix and so the accessibility to zeolite pores and active sites. Matrixes with low porosity and activity enhance coke production and deactivate faster than matrixes with mesopores. Furthermore, ZSM-5 modifies the individual morphological and catalytic effects of the binders. Everything considered, the small crystals of ZSM-5 together with mesopores increase the olefins yield, reduce coking, and therefore enhance the performance of the final grain.

Dual-Mode Organic Electrochemical Transistors Based on Self-Doped Conjugated Polyelectrolytes for Reconfigurable Electronics.

Reconfigurable organic logic devices are promising candidates for next generations of efficient computing systems and adaptive electronics. Ideally, such devices would be of simple structure and design, be power efficient, and compatible with high-throughput microfabrication techniques. This work reports an organic reconfigurable logic gate based on novel dual-mode organic electrochemical transistors (OECTs), which employ a self-doped conjugated polyelectrolyte as the active material, which then allows the transistors to operate in both depletion mode and enhancement mode. Furthermore, mode switching is accomplished by simply altering the polarity of the applied gate and drain voltages, which can be done on the fly. In contrast, achieving similar mode-switching functionality with other organic transistors typically requires complex molecular design or multi-device engineering. It in shown that dual-mode functionality is enabled by the concurrent existence of anion doping and cation dedoping of the films. A device physics model that accurately describes the behavior of these transistors is developed. Finally, the utility of these dual-mode transistors for implementing reconfigurable logic by fabricating a logic gate that may be switched between logic gates AND to NOR, and OR to NAND on the fly is demonstrated.

Mechanical properties of steel slag replaced mineral aggregate for road base/sub-base application based Vietnam and Japan standard.

Steelmaking slag is one of the most massive industrial by-products generated during steelmaking processes. This paper presents the current steelmaking slag production status and its potential to use as mineral aggregates in base/sub-base layer of road pavement. The mechanical properties of steelmaking slag were confirmed by the test method specified in Vietnam specification. The volume stability test of the slag was conducted based on JIS A 5015-2018 (Japanese Industrial Standard: Iron and steel slag for road construction). From the results, it was confirmed that steelmaking slag can satisfy all the mechanical requirements specified in Vietnam specification and the requirements regarding stability specified in JIS A 5015-2018. In addition, it was found that the elastic modulus of steelmaking slag applied as a base or sub-base layer in pavement was higher than that of the conventional graded aggregate made from mineral aggregate. Therefore, the thickness of pavement can be reduced by using steelmaking slag, and the construction cost can be lower.