Eu2+ doped fluorosilicate glass-ceramics containing BaF2 nanocrystals have high potential as spectral conversion materials for organic solar cells. However, it is difficult to realize the efficient design of BaF2:Eu2+ doped fluorosilicate glass and to vividly observe the glass microstructure in experiment through traditional trial-and-error glass preparation method. BaF2:Eu2+ doped fluorosilicate glass-ceramics with high transparency, and high photoluminescence (PL) performance were predicted, designed and prepared via molecular dynamics (MD) simulation method. By MD simulation prediction, self-organized nanocrystallization was realized to inhibit the abnormal growth of nanocrystals due to [AlO4] tetrahedra formed in the fluoride-oxide interface. The introduction of NaF reduces the effective phonon energy of the glass because Na + will prompt Al3+ to migrate from the fluoride phase to the silicate phase and interface. The local environment of Eu2+ is optimized by predicting the doping concentration of EuF3 and 2 mol% EuF3 is the best concentration in this work. Glass-ceramics sample GC2Eu as spectral conversion layer was successfully applied on organic solar cells to obtain more available visible phonons with a high photoelectric conversion efficiency (PCE). This work confirms the guidance of molecular dynamics simulation methods for fluorosilicate glasses design.

Fruit length (FL) is an important economical trait that affects fruit yield and appearance. Pumpkin (Cucurbita moschata Duch) contains a wealth genetic variation in fruit length. However, the natural variation underlying differences in pumpkin fruit length remains unclear. In this study, we constructed a F2 segregate population using KG1 producing long fruit and MBF producing short fruit as parents to identify the candidate gene for fruit length. By bulked segregant analysis (BSA-seq) and Kompetitive Allele-Specific PCR (KASP) approach of fine mapping, we obtained a 50.77 kb candidate region on chromosome 14 associated with the fruit length. Then, based on sequence variation, gene expression and promoter activity analyses, we identified a candidate gene (CmoFL1) encoding E3 ubiquitin ligase in this region may account for the variation of fruit length. One SNP variation in promoter of CmoFL1 changed the GT1CONSENSUS, and DUAL-LUC assay revealed that this variation significantly affected the promoter activity of CmoFL1. RNA-seq analysis indicated that CmoFL1 might associated with the cell division process and negatively regulate fruit length. Collectively, our work identifies an important allelic affecting fruit length, and provides a target gene manipulating fruit length in future pumpkin breeding.

The Boltzmann Tyranny, set by thermionic statistics, dictates the lower limit of switching slope (SS) of a MOSFET to be 60 mV/dec, the fundamental barrier for low-dissipative electronics. The large SS leads to nonscalable voltage, significant leakage, and power consumption, particularly at short channels, making transistor scaling an intimidating challenge. In recent decades, an array of steep-slope transistors has been proposed; none is close to an ideal switch with ultimately abrupt switching (SS ∼ 0 mV/dec) between the binary logic states. We demonstrated an all-2D-materials van-der-Waals-heterostructure (vdW)-based FET that exhibits ultrasteep switching (0.33 mV/dec), a large on/off current ratio (∼107), and an ultralow off current (∼0.1 pA). The "Subthreshold-Free" operation achieved by the collective behavior of functional materials enables FET switching directly from the OFF-state to the ON-state with entirely eliminated subthreshold region, behaving as the ideal logic switch. Two-inch wafer-scale device fabrication is demonstrated. Boosted by device innovation and emerging materials, the research presents an advancement in achieving the "beyond-Boltzmann" transistors, overcoming one of the CMOS electronics' most infamous technology barriers that have plagued the research community for decades.

Electroencephalography (EEG) signals are prone to contamination by noise, such as ocular and muscle artifacts. Minimizing these artifacts is crucial for EEG-based downstream applications like disease diagnosis and brain-computer interface (BCI). This paper presents a new EEG denoising model, DTP-Net. It is a fully convolutional neural network comprising Densely-connected Temporal Pyramids (DTPs) placed between two learnable time-frequency transformations. In the time-frequency domain, DTPs facilitate efficient propagation of multi-scale features extracted from EEG signals of any length, leading to effective noise reduction. Comprehensive experiments on two public semi-simulated datasets demonstrate that the proposed DTP-Net consistently outperforms existing state-of-the-art methods on metrics including relative root mean square error (RRMSE) and signal-to-noise ratio improvement ( ∆SNR). Moreover, the proposed DTP-Net is applied to a BCI classification task, yielding an improvement of up to 5.55% in accuracy. This confirms the potential of DTP-Net for applications in the fields of EEG-based neuroscience and neuro-engineering. An in-depth analysis further illustrates the representation learning behavior of each module in DTP-Net, demonstrating its robustness and reliability.

Plant evolution is driven by key innovations of functional traits that enables their survivals in diverse ecological environments. However, plant adaptive evolution from land to atmospheric niches remains poorly understood. In this study, we use the epiphytic Tillandsioideae subfamily of Bromeliaceae as model plants to explore their origin, evolution and diversification. We provide a comprehensive phylogenetic tree based on nuclear transcriptomic sequences, indicating that core tillandsioids originated approximately 11.3 million years ago in the Andes. The geological uplift of the Andes drives the divergence of tillandsioids into tank-forming and atmospheric types. Our genomic and transcriptomic analyses reveal gene variations and losses associated with adaptive traits such as impounding tanks and absorptive trichomes. Furthermore, we uncover specific nitrogen-fixing bacterial communities in the phyllosphere of tillandsioids as potential source of nitrogen acquisition. Collectively, our study provides integrative multi-omics insights into the adaptive evolution of tillandsioids in response to elevated aerial habitats. The mechanisms by which tillandsioids adapt to elevated aerial habitats remain largely unexplored. Here, the authors report their evolution and link life history, diversification, comparative genomic, and functional changes to processes underlying the unique biology of air plants.

Two-terminal optoelectronic synaptic devices have attracted increasing attention owing to their simplicity of structures, which facilitate the device integration in neuromorphic computing systems. However, synaptic-weight updates and self-rectifying properties in two-terminal optoelectronic synaptic devices are inferior. Here, we fabricate two-terminal optoelectronic synaptic devices in accordance with the hybrid structure of optically active layers MAPbI(3) and electron transport layers (ETLs) SnO2 in an n-i-p planar system, where MAPbI3 and SnO2 are used for generating and trapping carriers, respectively. Synaptic functionalities such as excitatory post-synaptic current (EPSC), paired-pulse facilitation (PPF), spike-number dependent plasticity (SNDP), and spike-rate dependent plasticity (SRDP) are all successfully mimicked without external bias. These synaptic devices possess self-rectifying properties with a highest ratio of similar to 0.3 x 10(3) and their synaptic weight exhibits largest-dynamic-range updates of 14.3 within 14 seconds among the reported two-terminal optoelectronic synaptic devices. Furthermore, the spike-number tunability of EPSC in the synaptic devices leads to the realization of straight running of agrimotor driverless technology. Results dramatically promote the development of two-terminal optoelectronic synaptic devices in neuromorphic computing.

Based on brain-inspired computing frameworks, neuromorphic systems implement large-scale neural networks in hardware. Although rapid advances have been made in the development of artificial neurons and synapses in recent years, further research is beyond these individual components and focuses on neuronal circuit motifs with specialized excitatory-inhibitory (E-I) connectivity patterns. In this study, we demonstrate a core processor that can be used to construct commonly used neuronal circuits. The neuron, featuring an ultracompact physical configuration, integrates a volatile threshold switch with a gate-modulated two-dimensional (2D) MoS2 field-effect channel to process complex E-I spatiotemporal spiking signals. Consequently, basic neuronal circuits are constructed for biorealistic neuromorphic computing. For practical applications, an algorithm-hardware co-design is implemented in a gate-controlled spiking neural network with substantial performance improvement in human speech separation.

Ag quantum clusters (Ag QCs) embedded in glasses are promising for various optoelectronic devices, but the manipulation over their aggregation states toward efficient photoluminescence (PL) is still challenging. Here, we propose two network strategies to tailor the Ag QCs aggregation and PL performance inside borate glass. Using the solubility strategy, the introduced network modifier (BaO) brings [BO3] -> [BO4]- transformation and poses steric hindrance, leading to the growth of Ag QCs. Through the charge compensator strategy (Al2O3), it brings negatively charged [AlO4]- units that favor isolated Ag+ ions to meet charge balance, rendering the cluster dissociation. With further SiO2 incorporation, the borosilicate constructs a rigid network that improves the glass stability and prevents molecular motions in Ag QCs, promoting PL quantum efficiency (up to 90.55%). Based on these design principles, the glass with highly emissive and stable Ag QCs is prepared and presents potential in the spectral converter for organic solar cells.

Recently, water-borne fluorescent inks have attracted extensive attention in anti-counterfeiting applications due to their convenient implementation and eco-friendliness. However, due to poor service durability, the latent authorization information from the inks is easily damaged, and even disappears when encountering water. Moreover, most of the existing fluorescent inks are monochromic, toxic, and allergic to skin, thus are unsuitable for their sustainability during real-life applications. Herein, this work presents environment-friendly, durable, and multicolor fluorescent anti-counterfeiting silicon nanoparticles (SiNPs)/sodium alginate (SA) inks. The multicolor SiNPs are synthesized by a one-pot method with defined morphologies and optical properties. Subsequently, SA is employed as the binder to prepare the fluorescent inks with optimized rheological properties. Practicability results show that the SiNPs/SA inks not only exhibit excellent printability, but also impart authentic information with superior covert performance. More notably, spraying solution of calcium dichloride can further improve fluorescent fastnesses of the SiNPs/SA inks by ionic crosslinking.

Sweetness and appearance of fresh fruits are key palatable and preference attributes for consumers and are often controlled by multiple genes. However, fine-mapping the key loci or genes of interest by single genome-based genetic analysis is challenging. Herein, we present the chromosome-level genome assembly of 1 landrace melon accession (Cucumis melo ssp. agrestis) with wild morphologic features and thus construct a melon pan-genome atlas via integrating sequenced melon genome datasets. Our comparative genomic analysis reveals a total of 3.4 million genetic variations, of which the presence/absence variations (PAVs) are mainly involved in regulating the function of genes for sucrose metabolism during melon domestication and improvement. We further resolved several loci that are accountable for sucrose contents, flesh color, rind stripe, and suture using a structural variation (SV)-based genome-wide association study. Furthermore, via bulked segregation analysis (BSA)-seq and map-based cloning, we uncovered that a single gene, (CmPIRL6), determines the edible or inedible characteristics of melon fruit exocarp. These findings provide important melon pan-genome information and provide a powerful toolkit for future pan-genome-informed cultivar breeding of melon.

Brain-inspired neuromorphic computing systems with the potential to drive the next wave of artificial intelligence demand a spectrum of critical components beyond simple characteristics. An emerging research trend is to achieve advanced functions with ultracompact neuromorphic devices. In this work, a single-transistor neuron is demonstrated that implements excitatory-inhibitory (E-I) spatiotemporal integration and a series of essential neuron behaviors. Neuronal oscillations, the fundamental mode of neuronal communication, that construct high-dimensional population code to achieve efficient computing in the brain, can also be demonstrated by the neuron transistors. The highly scalable E-I neuron can be the basic building block for implementing core neuronal circuit motifs and large-scale architectural plans to replicate energy-efficient neural computations, forming the foundation of future integrated neuromorphic systems.

Metal halide perovskites (MHPs) have emerged as promising X‐ray detection materials. However, most MHP‐based X‐ray detectors are incompatible for large‐area preparation and integration, and suffer from the serious ion migration issue. This work demonstrates a “perovskite‐in‐a‐host” nanocomposite structure for X‐ray detection, by embedding the perovskite nanocrystal (PNC) sensitizers in the organic interpenetrating charge transport channels to work as the X‐ray attenuation layer. Intriguingly, the photon sensitization mechanism can be readily tuned from indirect‐ to direct‐type X‐ray conversion by decreasing the ligand density on the PNC surface, which significantly increases the sensitivity to 5 696 µC Gy air –1 cm –2 . Besides, the ion migration gets suppressed due to the ion blocking effect of the surrounding organic phase. Therefore, an ultra‐small dark current relative drift of 3.57 × 10 –9 cm s –1 V –1 is achieved even under an extremely large electric field up to 5 100 V cm –1 , ensuring a low detection limit down to 72 nGy air s –1 . The superior sensitivity and biasing stability enable the high performance X‐ray imaging capability of the devices, which exhibit great potential in scaling up and integration for the flat panel imaging.

Eu2+doped transparent spectral conversion glass is feasible for various photovoltaic devices to get efficiency improvements, through harvesting extra photons out of the response region.

Silicon is vital for its high abundance, vast production, and perfect compatibility with the well-established CMOS processing industry. Recently, artificially stacked layered 2D structures have gained tremendous attention via fine-tuning properties for electronic devices. This article presents neuromorphic devices based on silicon nanosheets that are chemically exfoliated and surface-modified, enabling self-assembly into hierarchical stacking structures. The device functionality can be switched between a unipolar memristor and a feasibly reset-able synaptic device. The memory function of the device is based on the charge storage in the partially oxidized SiNS stacks followed by the discharge activated by the electric field at the Au-Si Schottky interface, as verified in both experimental and theoretical means. This work further inspired elegant neuromorphic computation models for digit recognition and noise filtration. Ultimately, it brings silicon - the most established semiconductor - back to the forefront for next-generation computations.

In the past decades, silicon nanocrystals have received vast attention and have been widely studied owing to not only their advantages including nontoxicity, high availability, and abundance but also their unique luminescent properties distinct from bulk silicon. Among the various synthetic methods of silicon nanocrystals, thermal disproportionation of silicon suboxides (often with H as another major composing element) bears the superiorities of unsophisticated equipment requirements, feasible processing conditions, and precise control of nanocrystals size and structure, which guarantee a bright industrial application prospect. In this paper, we summarize the recent progress of thermal disproportionation chemistry for the synthesis of silicon nanocrystals, with the focus on the effects of temperature, Si/O ratio, and the surface groups on the resulting silicon nanocrystals' structure and their corresponding photoluminescent properties. Moreover, the paradigmatic application scenarios of the photoluminescent silicon nanocrystals synthesized via this method are showcased or envisioned.

Two‐dimensional materials (2D M) possess unique structural, optical, and electronic properties in comparison with their bulk counterparts. Therefore, they have been demonstrated to be excellent performers for catalysis (especially photocatalysis). Among these 2D catalytic materials, 2D silicon (2D Si) is an emerging subclass, gifted with Si's high abundance, low toxicity, and strong light‐harvesting ability. Endowed with the universal advantages of 2D M including a large surface area, prolific active sites and loading positions for other elements, and ultrathin thickness for the generation of defects and transportation of photogenerated carriers, 2D Si exhibits additionally distinct surface chemistry and metal‐support interactions through geometrical assembly. These features render 2D Si a competitive candidate for (photo)catalysis, drawing burgeoning interest recently.

Mesoporous carbon (MC) nanomaterials have received intensive investigation in the past decades. However, the synthesis of MC with controllable morphologies and porous structures still remains challenging. Herein, we report a surface-induced assembly strategy to construct MC with various geometries and porous structures, using one-dimensional (1D) surface-modified multiwalled carbon nanotubes and two-dimensional (2D) graphene oxide nanosheets as morphological inducers. Positively charged polyaniline (PANI) and silica (SiO2) nanoparticles that serve as carbon source and pore template, respectively, were used to produce SiO2@PANI aggregations in hydrochloric acid media via S+X-I+ assembly pathway, which nucleate and grow on the negatively charged inducer surfaces through electrostatic interaction. MC nanomaterials with precisely tunable dimensions (1D to 2D), diameters (35-210 nm), thicknesses (7-145 nm), and pore sizes (7-22 nm) are successfully fabricated. More importantly, this method can be extended to other morphological inducers that contain negatively charged surfaces, such as Ti3C2Tx. The electrodes based on the MC nanomaterials demonstrate excellent energy storage performance in flexible sulfur electrodes and supercapacitors. Our findings shed light on a new strategy to prepare various MC for energy storage.

Oxyfluoride transparent glass-ceramics (GC) containing CaF2 and ZnAl2O4 nanocrystals have been fabricated with melt-quenching method. By carrying out the heat treatment of the precursor glass (PG), Er3+ and Cr3+ were selectively partitioned into CaF2 and ZnAl2O4 nanocrystals, respectively. The obtained multi-phase GC exhibited strong upconversion (UC) fluorescence of Er3+ as well as intense down-conversion (DC) fluorescence of Cr3+. Under 980 nm excitation, the green UC fluorescence of Er3+ due to H-2(11/2),S-4(3/2) -> I-4(15/2) transition and the red DC fluorescence lifetime of Cr3+ due to E-2, T-4(2) -> (4)A(2) transition were found to be highly dependent on the temperature and makes them possibly suitable for Optical Thermometry. With least-square fitting methods, the FIR of Er3+ from thermally coupled energy states (H-2(11/2) and S-4(3/2)) produced maximum temperature sensing sensitivity values of 0.33% K-1 at 437 K and 0.36% K-1 at 267 K, respectively. Similarly, fluorescence lifetime of Cr3+ attributed to the parity forbidden (E-2 -> (4)A(2)) and spin allowed (T-4(2) -> (4)A(2)) produced the maximum temperature sensor sensitivity value equal to 0.67% K-1 at 535 K.

Fluorosilicate glasses and glass-ceramics with MF2 (M = Ca, Sr, Ba), ZnF2 or LaF3 components were investigated to host divalent Eu2+ for photoluminescence (PL) application. X-ray diffraction phase identification and a series of spectroscopic analyses were performed to reveal the relationship between microstructure and the reduction of Eu3+ → Eu2+. The precursor glasses were believed being constituted by silicate-rich phases and fluoride-rich phases, due to the immiscibility of fluoride-and-silicate mixed glass system. After heat treatment, the fluoride-rich glass phases could transform into fluoride crystalline phase in the glass-ceramics. Europium tended to enrich in the fluoride-rich phases in the glasses or in the precipitated fluoride crystalline phases in the glass-ceramics. Small amounts of Eu3+ were reduced to Eu2+ in the glasses where the electronegativity had a crucial impact. In contrast, large amounts of Eu3+ were reduced to Eu2+ in the glass-ceramics containing MF2 nanocrystals, where the reduction was determined by lattice site substitution. Using ZnAl2O4 containing glass-ceramics as reference, it was evidenced that the similar and a little larger radii between sites and substitution ions are the prerequisite for Eu3+/M2+ substitution. And using LaF3 containing glass-ceramics as reference, it was certified that unbalanced charge at substitution sites induce the Eu3+ → Eu2+ reduction.