Real-time single-proton counting with transmissive perovskite nanocrystal scintillators.

High-sensitivity radiation detectors for energetic particles are essential for advanced applications in particle physics, astronomy and cancer therapy. Current particle detectors use bulk crystals, and thin-film organic scintillators have low light yields and limited radiation tolerance. Here we present transmissive thin scintillators made from CsPbBr3 nanocrystals, designed for real-time single-proton counting. These perovskite scintillators exhibit exceptional sensitivity, with a high light yield (~100,000 photons per MeV) when subjected to proton beams. This enhanced sensitivity is attributed to radiative emission from biexcitons generated through proton-induced upconversion and impact ionization. These scintillators can detect as few as seven protons per second, a sensitivity level far below the rates encountered in clinical settings. The combination of rapid response (~336 ps) and pronounced ionostability enables diverse applications, including single-proton tracing, patterned irradiation and super-resolution proton imaging. These advancements have the potential to improve proton dosimetry in proton therapy and radiography.

Gold-silver alloy hollow nanoshells-based lateral flow immunoassay for colorimetric, photothermal, and SERS tri-mode detection of SARS-CoV-2 neutralizing antibody.

Although many approaches have been developed for the quick assessment of SARS-CoV-2 infection, few of them are devoted to the detection of the neutralizing antibody, which is essential for assessing the effectiveness of vaccines. Herein, we developed a tri-mode lateral flow immunoassay (LFIA) platform based on gold-silver alloy hollow nanoshells (Au-Ag HNSs) for the sensitive and accurate quantification of neutralizing antibodies. By tuning the shell-to-core ratio, the surface plasmon resonance (SPR) absorption band of the Au-Ag HNSs is located within the near infrared (NIR) region, endowing them with an excellent photothermal effect under the irradiation of optical maser at 808 nm. Further, the Raman reporter molecule 4-mercaptobenzoic acid (MBA) was immobilized on the gold-silver alloy nanoshell to obtain an enhanced SERS signal. Thus, these Au-Ag HNSs could provide colorimetric, photothermal and SERS signals, with which, tri-mode strips for SARS-CoV-2 neutralizing antibody detection were constructed by competitive immunoassay. Since these three kinds of signals could complement one another, a more accurate detection was achieved. The tri-mode LFIA achieved a quantitative detection with detection limit of 20 ng/mL. Moreover, it also successfully detected the serum samples from 98 vaccinated volunteers with 79 positive results, exhibiting great application value in neutralizing antibody detection.

Anomalous Anisotropic Dopant Distribution in Hexagonal Yttrium Sublattice.

Trivalent lanthanides are commonly incorporated into sodium yttrium fluoride nanocrystals to enhance their optical properties. Lanthanides are expected to randomly replace trivalent yttrium cations due to their isovalent nature, and the dopant-dopant distance decreases with increasing dopant concentration. Combining spectroscopy with quantum mechanical calculations, we find that large lanthanides exhibit an anisotropic distribution in the hexagonal yttrium sublattice at low dopant concentrations. This counterintuitive substitution suggests the formation of one-dimensional dimers or chains with short dopant-dopant distances. Our study of the distance-sensitive cross-relaxation between Nd3+ dopants in ß-NaYF4 nanocrystals confirms that the concentration quenching threshold is lower than that of their cubic counterparts, consistent with the proposed chain-like model. Moreover, we demonstrate modulation of the anisotropic distribution by microstrain management via alkali metal codoping. Research into dopant distribution in inorganic crystals may enable the development of new materials and properties for future challenges.

Multi-functional Strategy: Ammonium Citrate-Modified SnO2 ETL for Efficient and Stable Perovskite Solar Cells.

The tin oxide (SnO2) electron transport layer (ETL) plays a crucial role in perovskite solar cells (PSCs). However, the heterogeneous dispersion of commercial SnO2 colloidal precursors is far from optimized, resulting in dissatisfied device performance with SnO2 ETL. Herein, a multifunctional modification material, ammonium citrate (TAC), is used to modify the SnO2 ETL, bringing four benefits: (1) due to the electrostatic interaction between TAC molecules and SnO2 colloidal particles, more uniformly dispersed colloidal particles are obtained; (2) the TAC molecules distributed on the surface of SnO2 provide nucleation sites for the perovskite film growth, promoting the vertical growth of the perovskite crystal; (3) TAC-doped SnO2 shows higher electron conductivity and better film quality than pristine SnO2 while offering better energy-level alignment with the perovskite layer; and (4) TAC has functional groups of C═O and N-H containing lone pair electrons, which can passivate the defects on the surface of SnO2 and perovskite films through chemical bonding and inhibit the device hysteresis. In the end, the device based on TAC-doped ETL achieved an increased power conversion efficiency (PCE) of 21.58 from 19.75% of the reference without such treatment. Meanwhile, the PSCs using the TAC-doped SnO2 as the ETL maintained 88% of their initial PCE after being stored for about 1000 h under dark conditions and controlled RH of 10-25%.

An Inverted Perovskite Solar Cell with Good Comprehensive Performance Realized by Reducing the Concentration of Precursors.

Inverted perovskite solar cells (PSCs) exhibit great potential for industrial application thanks to their low complexity and low fabrication temperature. Aiming at commercial applications, it is necessary to comprehensively consider the material consumption and its corresponding electrical performance. Here, a simple strategy has been proposed to obtain inverted PSCs with comprehensive performance, that is, reaching an acceptable electrical performance by reducing the usage of perovskite. More precisely, the inverted PSCs, whose perovskite film is prepared by 1.0 M precursor, yields a power conversion efficiency (PCE) of 15.50%, fulfilling the requirement for real commercial application. In addition, the thickness of the electron transport layer (C60 in this work) in the above inverted PSCs was further optimized by comparing the simulated absorption spectrum, J-V characteristics and impedance with three different thicknesses of C60 layer. More excitingly, the optimized device displays high storage stability which maintains more than 90% of its initial PCE for 28 days. Therefore, our work provides a simple and cost-effective method to reach good comprehensive performance of inverted PSCs for commercial applications.

Multimodal Tuning of Synaptic Plasticity Using Persistent Luminescent Memitters.

Mimicking memory processes, including encoding, storing, and retrieving information, is critical for neuromorphic computing and artificial intelligence. Synaptic behavior simulations through electronic, magnetic, or photonic devices based on metal oxides, 2D materials, molecular complex and phase change materials, represent important strategies for performing computational tasks with enhanced power efficiency. Here, a special class of memristive materials based on persistent luminescent memitters (termed as a portmanteau of "memory" and "emitter") with optical characteristics closely resembling those of biological synapses is reported. The memory process and synaptic plasticity can be successfully emulated using such memitters under precisely controlled excitation frequency, wavelength, pulse number, and power density. The experimental and theoretical data suggest that electron-coupled trap nucleation and propagation through clustering in persistent luminescent memitters can explain experience-dependent plasticity. The use of persistent luminescent memitters for multichannel image memorization that allows direct visualization of subtle changes in luminescence intensity and realization of short-term and long-term memory is also demonstrated. These findings may promote the discovery of new functional materials as artificial synapses and enhance the understanding of memory mechanisms.

Signal Filtering Enabled by Spike Voltage-Dependent Plasticity in Metalloporphyrin-Based Memristors.

Neural systems can selectively filter and memorize spatiotemporal information, thus enabling high-efficient information processing. Emulating such an exquisite biological process in electronic devices is of fundamental importance for developing neuromorphic architectures with efficient in situ edge/parallel computing, and probabilistic inference. Here a novel multifunctional memristor is proposed and demonstrated based on metalloporphyrin/oxide hybrid heterojunction, in which the metalloporphyrin layer allows for dual electronic/ionic transport. Benefiting from the coordination-assisted ionic diffusion, the device exhibits smooth, gradual conductive transitions. It is shown that the memristive characteristics of this hybrid system can be modulated by altering the metal center for desired metal-oxygen bonding energy and oxygen ions migration dynamics. The spike voltage-dependent plasticity stemming from the local/extended movement of oxygen ions under low/high voltage is identified, which permits potentiation and depression under unipolar different positive voltages. As a proof-of-concept demonstration, memristive arrays are further built to emulate the signal filtering function of the biological visual system. This work demonstrates the ionic intelligence feature of metalloporphyrin and paves the way for implementing efficient neural-signal analysis in neuromorphic hardware.

Stimuli-Responsive Memristive Materials for Artificial Synapses and Neuromorphic Computing.

Neuromorphic computing holds promise for building next-generation intelligent systems in a more energy-efficient way than the conventional von Neumann computing architecture. Memristive hardware, which mimics biological neurons and synapses, offers high-speed operation and low power consumption, enabling energy- and area-efficient, brain-inspired computing. Here, recent advances in memristive materials and strategies that emulate synaptic functions for neuromorphic computing are highlighted. The working principles and characteristics of biological neurons and synapses, which can be mimicked by memristive devices, are presented. Besides device structures and operation with different external stimuli such as electric, magnetic, and optical fields, how memristive materials with a rich variety of underlying physical mechanisms can allow fast, reliable, and low-power neuromorphic applications is also discussed. Finally, device requirements are examined and a perspective on challenges in developing memristive materials for device engineering and computing science is given.

High-resolution X-ray luminescence extension imaging.

Current X-ray imaging technologies involving flat-panel detectors have difficulty in imaging three-dimensional objects because fabrication of large-area, flexible, silicon-based photodetectors on highly curved surfaces remains a challenge1-3. Here we demonstrate ultralong-lived X-ray trapping for flat-panel-free, high-resolution, three-dimensional imaging using a series of solution-processable, lanthanide-doped nanoscintillators. Corroborated by quantum mechanical simulations of defect formation and electronic structures, our experimental characterizations reveal that slow hopping of trapped electrons due to radiation-triggered anionic migration in host lattices can induce more than 30 days of persistent radioluminescence. We further demonstrate X-ray luminescence extension imaging with resolution greater than 20 line pairs per millimetre and optical memory longer than 15 days. These findings provide insight into mechanisms underlying X-ray energy conversion through enduring electron trapping and offer a paradigm to motivate future research in wearable X-ray detectors for patient-centred radiography and mammography, imaging-guided therapeutics, high-energy physics and deep learning in radiology.

Examining palpebral conjunctiva for anemia assessment with image processing methods.

Examining the hemoglobin level of blood is an important way to achieve the diagnosis of anemia, but it requires blood drawing and blood test. Examining the color distribution of palpebral conjunctiva is a standard procedure of anemia diagnosis, which requires no blood test. However, since color perception is not always consistent among different people, we attempt to imitate the way of physical examination of palpebral conjunctiva to detect anemia, so that computers can identify anemia patients automatically in a consolidated manner for a screening process. In this paper we propose two algorithms for anemia diagnosis. The first algorithm is intended to be simple and fast, while the second one to be more sophisticated and robust, providing an option for different applications. The first algorithm consists of a simple two-stage classifier. In the first stage, we use a thresholding decision technique based on a feature called high hue rate (HHR) (extracted from the HSI color space). In the second stage, a feature called pixel value in the middle (PVM) (extracted from the RGB color space) is proposed, followed by the use of a minimum distance classifier based on Mahalanobis distance. In the second algorithm, we consider 18 possible features, including a newly added entropy feature, some improved features from the first algorithm, and 13 features proposed in a previous work. We use correlation and simple statistics to select 3 relatively independent features (entropy, binarization of HHR, and PVM of G component) for classification using a support vector machine or an artificial neural network. Finally, we evaluate the classification performance of the proposed algorithms in terms of sensitivity, specificity, and Kappa value. The experimental results show relatively good performance and prove the feasibility of our attempt, which may encourage more follow-up study in the future.