Rapid Sensing of Hidden Objects and Defects using a Single-Pixel Diffractive Terahertz Processor

Terahertz waves offer numerous advantages for the nondestructive detection of hidden objects/defects in materials, as they can penetrate through most optically-opaque materials. However, existing terahertz inspection systems are restricted in their throughput and accuracy (especially for detecting small features) due to their limited speed and resolution. Furthermore, machine vision-based continuous sensing systems that use large-pixel-count imaging are generally bottlenecked due to their digital storage, data transmission and image processing requirements. Here, we report a diffractive processor that rapidly detects hidden defects/objects within a target sample using a single-pixel spectroscopic terahertz detector, without scanning the sample or forming/processing its image. This terahertz processor consists of passive diffractive layers that are optimized using deep learning to modify the spectrum of the terahertz radiation according to the absence/presence of hidden structures or defects. After its fabrication, the resulting diffractive processor all-optically probes the structural information of the sample volume and outputs a spectrum that directly indicates the presence or absence of hidden structures, not visible from outside. As a proof-of-concept, we trained a diffractive terahertz processor to sense hidden defects (including subwavelength features) inside test samples, and evaluated its performance by analyzing the detection sensitivity as a function of the size and position of the unknown defects. We validated its feasibility using a single-pixel terahertz time-domain spectroscopy setup and 3D-printed diffractive layers, successfully detecting hidden defects using pulsed terahertz illumination. This technique will be valuable for various applications, e.g., security screening, biomedical sensing, quality control, anti-counterfeiting measures and cultural heritage protection.Comment: 23 Pages, 5 Figure

Variation of endosymbiont and citrus tristeza virus (CTV) titers in the Huanglongbing insect vector, Diaphorina citri, on CTV-infected plants

“Candidatus Liberibacter asiaticus” (CLas) is a notorious agent that causes Citrus Huanglongbing (HLB), which is transmitted by Diaphorina citri (D. citri). We recently found that the acquisition and transmission of CLas by D. citri was facilitated by Citrus tristeza virus (CTV), a widely distributed virus in the field. In this study, we further studied whether different CTV strains manipulate the host preference of D. citri, and whether endosymbionts variation is related to CTV strains in D. citri. The results showed that the non-viruliferous D. citri preferred to select the shoots infected with CTV, without strain differences was observed in the selection. However, the viruliferous D. citri prefered to select the mixed strain that is similar to the field’s. Furthermore, D. citri effectively acquired the CTV within 2–12 h depending on the strains of the virus. The persistence period of CTV in D. citri was longer than 24 days, without reduction of the CTV titers being observed. These results provide a foundation for understanding the transmission mode of D. citri on CTV. During the process of CTV acquisition and persistence, the titers of main endosymbionts in D. citri showed similar variation trend, but their relative titers were different at different time points. The titers of the “Candidatus Profftella armatura” and CTV tended to be positively correlated, and the titers of Wolbachia and “Candidatus Carsonella ruddii” were mostly negatively related with titers of CT31. These results showed the relationship among D. citri, endosymbionts, and CTV and provided useful information for further research on the interactions between D. citri and CLas, which may benefit the development of approaches for the prevention of CLas transmission and control of citrus HLB

Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array

Nonlinear optical processing of ambient natural light is highly desired in computational imaging and sensing applications. A strong optical nonlinear response that can work under weak broadband incoherent light is essential for this purpose. Here we introduce an optoelectronic nonlinear filter array that can address this emerging need. By merging 2D transparent phototransistors (TPTs) with liquid crystal (LC) modulators, we create an optoelectronic neuron array that allows self-amplitude modulation of spatially incoherent light, achieving a large nonlinear contrast over a broad spectrum at orders-of-magnitude lower intensity than what is achievable in most optical nonlinear materials. For a proof-of-concept demonstration, we fabricated a 10,000-pixel array of optoelectronic neurons, each serving as a nonlinear filter, and experimentally demonstrated an intelligent imaging system that uses the nonlinear response to instantly reduce input glares while retaining the weaker-intensity objects within the field of view of a cellphone camera. This intelligent glare-reduction capability is important for various imaging applications, including autonomous driving, machine vision, and security cameras. Beyond imaging and sensing, this optoelectronic neuron array, with its rapid nonlinear modulation for processing incoherent broadband light, might also find applications in optical computing, where nonlinear activation functions that can work under ambient light conditions are highly sought.Comment: 20 Pages, 5 Figure

Spent lithium manganate batteries for sustainable recycling: A review

Lithium-ion batteries (LIBs) account for the majority of energy storage devices due to their long service life, high energy density, environmentally friendly, and other characteristics. Although the cathode materials of LIB led by LiFePO4 (LFP), LiCoO2 (LCO), and LiNixCoyMn1-x-yO2 (NCM) occupy the majority of the market share at present, the demand of LiMn2O4 (LMO) cathode battery is also increasing year by year in recent years. With the rising price of various raw materials of LIBs and the need of environmental protection, the efficient recycling of spent LIBs has become a hot research topic. At present, the recycling of spent LIBs mainly focuses on LFP, LCO, and NCM batteries. However, with the continuous improvement of people’s safety of LIBs, LiMnxFe1-xPO4 (LMFP) batteries show better potential, which also improves the recycling value of LMO batteries. Therefore, this paper reviews current methods of spent LMO recovery, focusing on the characteristics of the recovery and separation process, which can serve as a reference for subsequent research on LMO recovery, increasing environmentally friendly recovery routes. Finally, the future development direction of LIBs recycling is prospected. Overall, this review is helpful to understand the current progress of LMO battery recycling

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties