Silicon-based transient electronics: principles, devices and applications.

Recent advances in materials science, device designs and advanced fabrication technologies have enabled the rapid development of transient electronics, which represents a class of devices or systems that their functionalities and constitutions can be partially/completely degraded via chemical reaction or physical disintegration over a stable operation. Therefore, numerous potentials, including zero/reduced waste electronics, bioresorbable electronic implants, hardware security, and others, are expected. In particular, transient electronics with biocompatible and bioresorbable properties could completely eliminate the secondary retrieval surgical procedure after their in-body operation, thus offering significant potentials for biomedical applications. In terms of material strategies for the manufacturing of transient electronics, silicon nanomembranes (SiNMs) are of great interest because of their good physical/chemical properties, modest mechanical flexibility (depending on their dimensions), robust and outstanding device performances, and state-of-the-art manufacturing technologies. As a result, continuous efforts have been made to develop silicon-based transient electronics, mainly focusing on designing manufacturing strategies, fabricating various devices with different functionalities, investigating degradation or failure mechanisms, and exploring their applications. In this review, we will summarize the recent progresses of silicon-based transient electronics, with an emphasis on the manufacturing of SiNMs, devices, as well as their applications. After a brief introduction, strategies and basics for utilizing SiNMs for transient electronics will be discussed. Then, various silicon-based transient electronic devices with different functionalities are described. After that, several examples regarding on the applications, with an emphasis on the biomedical engineering, of silicon-based transient electronics are presented. Finally, summary and perspectives on transient electronics are exhibited.

PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants.

N 6-methyladenosine (m6A), which is the mostly prevalent modification in eukaryotic mRNAs, is involved in gene expression regulation and many RNA metabolism processes. Accurate prediction of m6A modification is important for understanding its molecular mechanisms in different biological contexts. However, most existing models have limited range of application and are species-centric. Here we present PEA-m6A, a unified, modularized and parameterized framework that can streamline m6A-Seq data analysis for predicting m6A-modified regions in plant genomes. The PEA-m6A framework builds ensemble learning-based m6A prediction models with statistic-based and deep learning-driven features, achieving superior performance with an improvement of 6.7% to 23.3% in the area under precision-recall curve compared with state-of-the-art regional-scale m6A predictor WeakRM in 12 plant species. Especially, PEA-m6A is capable of leveraging knowledge from pretrained models via transfer learning, representing an innovation in that it can improve prediction accuracy of m6A modifications under small-sample training tasks. PEA-m6A also has a strong capability for generalization, making it suitable for application in within- and cross-species m6A prediction. Overall, this study presents a promising m6A prediction tool, PEA-m6A, with outstanding performance in terms of its accuracy, flexibility, transferability, and generalization ability. PEA-m6A has been packaged using Galaxy and Docker technologies for ease of use and is publicly available at https://github.com/cma2015/PEA-m6A.

Dynamic constitutive identification of concrete based on improved dung beetle algorithm to optimize long short-term memory model.

In order to improve the accuracy of concrete dynamic principal identification, a concrete dynamic principal identification model based on Improved Dung Beetle Algorithm (IDBO) optimized Long Short-Term Memory (LSTM) network is proposed. Firstly, the apparent stress-strain curves of concrete containing damage evolution were measured by Split Hopkinson Pressure Bar (SHPB) test to decouple and separate the damage and rheology, and this system was modeled by using LSTM network. Secondly, for the problem of low convergence accuracy and easy to fall into local optimum of Dung Beetle Algorithm (DBO), the greedy lens imaging reverse learning initialization population strategy, the embedded curve adaptive weighting factor and the PID control optimal solution perturbation strategy are introduced, and the superiority of IDBO algorithm is proved through the comparison of optimization test with DBO, Harris Hawk Optimization Algorithm, Gray Wolf Algorithm, and Fruit Fly Algorithm and the combination of LSTM is built to construct the IDBO-LSTM dynamic homeostasis identification model. The final results show that the IDBO-LSTM model can recognize the concrete material damage without considering the damage; in the case of considering the damage, the IDBO-LSTM prediction curves basically match the SHPB test curves, which proves the feasibility and excellence of the proposed method.

Role of BcSfb3, the subunit of COPII vesicles, in fungal development and pathogenicity, ER-phagy and autophagy in the gray mold fungus Botrytis cinerea.

Cytoplasmic coat protein complex II (COPII) plays a multifunctional role in the transport of newly synthesized proteins, autophagosome formation, and endoplasmic reticulum (ER)-ER-phagy. However, the molecular mechanisms of the COPII subunit in ER-phagy in plant pathogens remain unknown. Here, we identified the subunit of COPII vesicles (BcSfb3) and explored the importance of BcSfb3 in Botrytis cinerea. BcSfb3 deletion affected vegetative growth, conidiation, conidial morphology, and plasma membrane integrity. We confirmed that the increase in infectious hyphal growth was delayed in the ΔBcSfb3 mutant, reducing its pathogenicity in the host plant. Furthermore, the ΔBcSfb3 mutant was sensitive to ER stress, which caused massive ER expansion and induced the formation of ER whorls that were taken up into the vacuole. Further examination demonstrated that BcSfb3 deletion caused ER stress initiated by unfolded protein response, and which led to the promotion of ER-phagy and autophagy that participate in sclerotia formation. In conclusion, these results demonstrate that BcSfb3 plays an important role in fungal development, pathogenesis, ER-phagy and autophagy in B. cinerea.

Whole-transcriptome sequencing revealed the role of noncoding RNAs in susceptibility and resistance of Pekin ducks to DHAV-3.

As the most prevalent pathogen of duck viral hepatitis (DVH), duck hepatitis A virus genotype 3 (DHAV-3) has caused huge economic losses to the duck industry in China. Herein, we obtained whole-transcriptome sequencing data of susceptible (S) and resistant (R) Pekin duckling samples at 0 h, 12 h, and 24 h after DHAV-3 infection. We found that DHAV-3 infection induces 5,396 differentially expressed genes (DEGs), 85 differentially expressed miRNAs (DEMs), and 727 differentially expressed lncRNAs (DELs) at 24 hpi in S vs. R ducks, those upregulated genes were enriched in inflammation and cell communications pathways and downregulated genes were related to metabolic processes. Upregulated genes showed high connectivity with the miR-33, miR-193, and miR-11591, and downregulated genes were mainly regulated by miR-2954, miR-125, and miR-146b. With the construction of lncRNA-miRNA-mRNA axis, we further identified a few aberrantly expressed lncRNAs (e.g., MSTRG.36194.1, MSTRG.50601.1, MSTRG.34328.7, and MSTRG.29445.1) that regulate expression of hub genes (e.g., THBD, CLIC2, IL8, ACOX2, GPHN, SMLR1, and HAO1) by sponging those highly connected miRNAs. Altogether, our findings defined a dual role of ncRNAs in immune and metabolic regulation during DHAV-3 infection, suggesting potential new targets for treating DHAV-3 infected ducks.

Primary Budd-Chiari syndrome versus sinusoidal obstruction syndrome: a review.

Budd-Chiari syndrome (BCS) and sinusoidal obstruction syndrome (SOS) are two major vascular disorders of the liver, of which both can cause portal hypertension related complications, but their locations of obstruction are different. BCS refers to the obstruction from the hepatic vein to the junction between the inferior vena cava and right atrium, which is the major etiology of post-sinusoidal portal hypertension; by comparison, SOS is characterized as the obstruction at the level of hepatic sinusoids and terminal venulae, which is a cause of sinusoidal portal hypertension. Both of them can cause hepatic congestion with life-threatening complications, especially acute liver failure and chronic portal hypertension, and share some similar features in terms of imaging and clinical presentations, but they have heterogeneous risk factors, management strategy, and prognosis. Herein, this paper reviews the current evidence and then summarizes the difference between primary BCS and SOS in terms of risk factors, clinical features, diagnosis, and treatment.

Stable blue phosphorescent organic LEDs that use polariton-enhanced Purcell effects.

Phosphorescent organic light-emitting diodes (PHOLEDs) feature high efficiency1,2, brightness and colour tunability suitable for both display and lighting applications3. However, overcoming the short operational lifetime of blue PHOLEDs remains one of the most challenging high-value problems in the field of organic electronics. Their short lifetimes originate from the annihilation of high-energy, long-lived blue triplets that leads to molecular dissociation4-7. The Purcell effect, the enhancement of the radiative decay rate in a microcavity, can reduce the triplet density and, hence, the probability of destructive high-energy triplet-polaron annihilation (TPA)5,6 and triplet-triplet annihilation (TTA) events4,5,7,8. Here we introduce the polariton-enhanced Purcell effect in blue PHOLEDs. We find that plasmon-exciton polaritons9 (PEPs) substantially increase the strength of the Purcell effect and achieve an average Purcell factor (PF) of 2.4 ± 0.2 over a 50-nm-thick emission layer (EML) in a blue PHOLED. A 5.3-fold improvement in LT90 (the time for the PHOLED luminance to decay to 90% of its initial value) of a cyan-emitting Ir-complex device is achieved compared with its use in a conventional PHOLED. Shifting the chromaticity coordinates to (0.14, 0.14) and (0.15, 0.20) into the deep blue, the Purcell-enhanced devices achieve 10-14 times improvement over similarly deep-blue PHOLEDs, with one structure reaching the longest Ir-complex device lifetime of LT90 = 140 ± 20 h reported so far10-21. The polariton-enhanced Purcell effect and microcavity engineering provide new possibilities for extending deep-blue PHOLED lifetimes.

SoyDNGP: a web-accessible deep learning framework for genomic prediction in soybean breeding.

Soybean is a globally significant crop, playing a vital role in human nutrition and agriculture. Its complex genetic structure and wide trait variation, however, pose challenges for breeders and researchers aiming to optimize its yield and quality. Addressing this biological complexity requires innovative and accurate tools for trait prediction. In response to this challenge, we have developed SoyDNGP, a deep learning-based model that offers significant advancements in the field of soybean trait prediction. Compared to existing methods, such as DeepGS and DNNGP, SoyDNGP boasts a distinct advantage due to its minimal increase in parameter volume and superior predictive accuracy. Through rigorous performance comparison, including prediction accuracy and model complexity, SoyDNGP represents improved performance to its counterparts. Furthermore, it effectively predicted complex traits with remarkable precision, demonstrating robust performance across different sample sizes and trait complexities. We also tested the versatility of SoyDNGP across multiple crop species, including cotton, maize, rice and tomato. Our results showed its consistent and comparable performance, emphasizing SoyDNGP's potential as a versatile tool for genomic prediction across a broad range of crops. To enhance its accessibility to users without extensive programming experience, we designed a user-friendly web server, available at http://xtlab.hzau.edu.cn/SoyDNGP. The server provides two features: 'Trait Lookup', offering users the ability to access pre-existing trait predictions for over 500 soybean accessions, and 'Trait Prediction', allowing for the upload of VCF files for trait estimation. By providing a high-performing, accessible tool for trait prediction, SoyDNGP opens up new possibilities in the quest for optimized soybean breeding.

Plasma lipidome reveals susceptibility and resistance of Pekin ducks to DHAV-3.

Duck hepatitis A virus genotype 3 (DHAV-3) is the most popular pathogen of duck viral hepatitis (DVH) and has led to a huge economic threat to the Asian duck industry. In this work, we investigated the differences in the LC-MS/MS-based dynamic lipid profiles between susceptible and resistant Pekin duck lines with DHAV-3 infection. We found that the plasma lipidome of the two duck lines was characterized differently in expression levels of lipids during the infection, such as decreased levels of glycerolipids and increased levels of cholesteryl esters and glycerophospholipids in susceptible ducks compared with resistant ducks. By integrating lipidomics and transcriptomics analysis, we showed that the altered homeostasis of lipids was potentially regulated by a variety of differentially expressed genes including CHPT1, PI4K2A, and OSBP2 between the two duck lines, which could account for liver dysfunction, apoptosis, and illness upon DHAV-3 infection. Using the least absolute shrinkage and selection operator (LASSO) approach, we determined a total of 25 infection-related lipids that were able to distinguish between the infection states of susceptible and resistant ducks. This study provides molecular clues for elucidating the pathogenesis and therapeutic strategies of DHAV-3 infection in ducklings, which has implication for the development of resistance breeding.

A Lightweight Recognition Method for Rice Growth Period Based on Improved YOLOv5s.

The identification of the growth and development period of rice is of great significance to achieve high-yield and high-quality rice. However, the acquisition of rice growth period information mainly relies on manual observation, which has problems such as low efficiency and strong subjectivity. In order to solve these problems, a lightweight recognition method is proposed to automatically identify the growth period of rice: Small-YOLOv5, which is based on improved YOLOv5s. Firstly, the new backbone feature extraction network MobileNetV3 was used to replace the YOLOv5s backbone network to reduce the model size and the number of model parameters, thus improving the detection speed of the model. Secondly, in the feature fusion stage of YOLOv5s, we introduced a more lightweight convolution method, GsConv, to replace the standard convolution. The computational cost of GsConv is about 60-70% of the standard convolution, but its contribution to the model learning ability is no less than that of the standard convolution. Based on GsConv, we built a lightweight neck network to reduce the complexity of the network model while maintaining accuracy. To verify the performance of Small-YOLOv5s, we tested it on a self-built dataset of rice growth period. The results show that compared with YOLOv5s (5.0) on the self-built dataset, the number of the model parameter was reduced by 82.4%, GFLOPS decreased by 85.9%, and the volume reduced by 86.0%. The mAP (0.5) value of the improved model was 98.7%, only 0.8% lower than that of the original YOLOv5s model. Compared with the mainstream lightweight model YOLOV5s- MobileNetV3-Small, the number of the model parameter was decreased by 10.0%, the volume reduced by 9.6%, and the mAP (0.5:0.95) improved by 5.0%-reaching 94.7%-and the recall rate improved by 1.5%-reaching 98.9%. Based on experimental comparisons, the effectiveness and superiority of the model have been verified.

Long-Range Propagation of Exciton-Polaritons in Large-Area 2D Semiconductor Monolayers.

Atomically thin transition metal dichalcogenides (TMDs), a subclass of two-dimensional (2D) layered materials, have numerous fascinating properties that make them a promising platform for photonic and optoelectronic devices. In particular, excited state transport by TMDs is important in energy harvesting and photonic switching; however, long-range transport in TMDs is challenging due to the lack of availability of large area films. Whereas most previous studies have focused on small, exfoliated monolayer flakes, in this work we demonstrate metal-organic chemical vapor deposition grown centimeter-scale monolayers of WS2 that support polariton propagation lengths of up to 60 µm. The polaritons form through the strong coupling of excitons with Bloch surface waves (BSWs) supported by all-dielectric photonic structures. We observe that the propagation length increases with the number of dielectric pairs due to the increased quality factor of the supporting distributed Bragg reflector. Furthermore, a longer propagation length is observed as the guided or BSW content of the polariton is increased. Our results provide a practical approach for the systematic engineering of long-range energy transport mediated by exciton-polaritons in TMD layers. Along with the accessibility of large area TMDs, our work enables applications for practical TMD-based polaritonic devices that operate at room temperature.

Identifying the potential role of serum miR-20a as a biomarker for olfactory dysfunction in patients with Parkinson's disease.

INTRODUCTION: Olfactory dysfunction (OD), one of the most common non-motor symptoms in Parkinson's disease (PD), is a cardinal prodromal symptom that can appear years before the onset of motor symptoms. Ongoing studies have demonstrated that microRNAs (miRNAs) are suitable biomarkers for PD, while there is a lack of robust miRNAs that can serve as markers for OD in PD. METHODS: The concordantly differentially expressed miRNAs (DE miRNAs) in the damaged olfactory system were first identified in 2 OD-related Gene Expression Omnibus (GEO) datasets. Then, they were verified in another PD-related GEO dataset and only one miRNA (miR-20a) was found to be significantly altered. Serum levels of miR-20a were further measured by qPCR in 79 PD patients with OD (PD-OD), 52 PD patients without OD (PD-NOD), and 52 healthy controls (HC). Objective measure of OD was defined by 16-item Sniffin' Sticks odor identification test. All the participants underwent a demographic and comprehensive PD-related clinical assessment. RESULTS: Our results proved that miR-20a was significantly downregulated in PD-OD compared with PD-NOD and the area under curve (AUC) for OD detection by miR-20a was 0.803 (95% confidence interval, 0.724-0.883). In addition, PD-OD had higher scores of Movement Disorder Society-Unified Parkinson's Disease Rating Scale (UPDRS) II, Hoehn and Yahr stage (H-Y), Non-Motor Symptoms Scale (NMSS) 3, NMSS 5, NMSS 9, Hamilton Rating Scale for Depression (HAMD), Hamilton Anxiety Scale (HAMA), Activity of Daily Living (ADL), and lower scores of Mini-Mental State Examination (MMSE) and 39-item PD Quality of Life Questionnaire (PDQ-39) than PD-NOD. Binary regression model further presented that lower expressions of miR-20a and poorer cognitive function acted as promoting factors in the development of OD. CONCLUSION: Our results suggest that miR-20a could be a novel biomarker for OD in PD and PD-OD patients tend to have higher disease stage, poorer motor aspects of experiences of daily living, worse cognitive scores, and inferior quality of life, and were more likely to have mental disorders. Cognitive function, in particular, is strongly associated with OD in PD patients.

Perillaldehyde Functions as a Potential Antifungal Agent by Triggering Metacaspase-Independent Apoptosis in Botrytis cinerea.

Botrytis cinerea, the causal agent of gray mold, is an important plant pathogen causing preharvest and postharvest diseases. Due to the extensive use of commercial fungicides, fungicide-resistant strains have emerged. Natural compounds with antifungal properties are widely present in various kinds of organisms. Perillaldehyde (PA), derived from the plant species Perilla frutescens, is generally recognized as a potent antimicrobial substance and to be safe to humans and the environment. In this study, we demonstrated that PA could significantly inhibit the mycelial growth of B. cinerea and reduced its pathogenicity on tomato leaves. We also found that PA had a significant protective effect on tomato, grape, and strawberry. The antifungal mechanism of PA was investigated by measuring the reactive oxygen species (ROS) accumulation, the intracellular Ca2+ level, the mitochondrial membrane potential, DNA fragmentation, and phosphatidylserine exposure. Further analyses revealed that PA promoted protein ubiquitination and induced autophagic activities and then triggered protein degradation. When the two metacaspase genes, BcMca1 and BcMca2, were knocked out from B. cinerea, all mutants did not exhibit reduced sensitivity to PA. These findings demonstrated that PA could induce metacaspase-independent apoptosis in B. cinerea. Based on our results, we proposed that PA could be used as an effective control agent for gray mold management. IMPORTANCE Botrytis cinerea causes gray mold disease, is considered one of the most important dangerous pathogens worldwide, and leads to severe economic losses worldwide. Due to the lack of resistant varieties of B. cinerea, gray mold control has mainly relied on application of synthetic fungicides. However, long-term and extensive use of synthetic fungicides has increased fungicide resistance in B. cinerea and is harmful to humans and the environment. In this study, we found that perillaldehyde has a significant protective effect on tomato, grape, and strawberry. We further characterized the antifungal mechanism of PA on B. cinerea. Our results indicated that PA induced apoptosis that was independent of metacaspase function.

Parkinson's disease patients combined with constipation tend to have higher serum expression of microRNA 29c, prominent neuropsychiatric disorders, possible RBD conversion, and a substandard quality of life.

INTRODUCTION: The symptom of constipation has been confirmed as an early diagnose criteria for Parkinson's disease (PD). Furthermore, evidences suggest that pathogenesis of PD initiates in gut, rather than brain. If so, identifying biomarkers for constipation in PD might have potentials to assist early diagnosis and initial treatment. METHOD: We first identified that microRNA 29c (miR-29c) was dysregulated both in PD and constipation patients through bioinformatics analysis. Then, serological analysis of the expression of miR-29c in 67 PD patients with constipation (PD-C), 51 PD patients without constipation (PD-NC), and 50 healthy controls (HC) was carried out by qPCR. Demographic and clinical features were also compared. Patients in PD-C group were further classified into two groups: those with prodromal stage constipation (PD-C-Pro) (n = 36) and those with clinical stage constipation (PD-C-Clinic) (n = 31), to explore their different characteristics. RESULTS: The levels of miR-29c in PD-C group were higher than that in PD-NC group, both higher than HC group. PD-C-Pro group's miR-29c levels were statistically higher compared with PD-C-Clinic group's. What is more, PD-C group had higher scores of MDS-UPDRS-I, NMSS, NMSS3, NMSS4, NMSS6, NMSS9, SCOPA-AUT, HAMD, HAMA, RBDSQ, CSS, and PACQOL compared with PD-NC party. Relative to the PD-C-Clinic, patients in PD-C-Pro group had higher MDS-UPDRS-I, NMSS, NMSS3, HAMD, and HAMA scores, and were more likely to have RBD. CONCLUSION: Our results indicated that miR-29c seems to be an underlying cause for developing constipation in patients with PD and PD-C identifies a group of patients with more severe non-motor impairment, prominent neuropsychiatric disorders, and possible RBD conversion as well as a substandard quality of life. We further confirmed that there is a close relationship between symptoms representing the same pathological origin, especially constipation and RBD.

Control of Host-Matrix Morphology Enables Efficient Deep-Blue Organic Light-Emitting Devices.

Mixing a sterically bulky, electron-transporting host material into a conventional single host-guest emissive layer is demonstrated to suppress phase separation of the host matrix while increasing the efficiency and operational lifetime of deep-blue phosphorescent organic light-emitting diodes (PHOLEDs) with chromaticity coordinates of (0.14, 0.15). The bulky host enables homogenous mixing of the molecules comprising the emissive layer while suppressing single host aggregation; a significant loss channel of nonradiative recombination. By controlling the amorphous phase of the host-matrix morphology, the mixed-host device achieves a significant reduction in nonradiative exciton decay, resulting in 120 ± 6% increase in external quantum efficiency relative to an analogous, single-host device. In contrast to single host PHOLEDs where electrons are transported by the host and holes by the dopants, both charge carriers are conducted by the mixed host, reducing the probability of exciton annihilation, thereby doubling of the deep-blue PHOLED operational lifetime. These findings demonstrate that the host matrix morphology affects almost every aspect of PHOLED performance.

Theoretical Study on the Swelling Mechanism and Structural Stability of Ni3Al-LDH Based on Molecular Dynamics.

layered double hydroxide (LDH) as a kind of 2D layer material has a swelling phenomenon. Because swelling significantly affects the adsorption, catalysis, energy storage, and other application properties of LDHs, it is essential to study the interlayer spacing, structural stability, and ion diffusion after swelling. In this paper, a periodic computational model of Ni3Al-LDH is constructed, and the supramolecular structure, swelling law, stability, and anion diffusion properties of Ni3Al-LDH are investigated by molecular dynamics theory calculations. The results show that the interlayer water molecules of Ni3Al-LDH present a regular layered arrangement, combining with the interlayer anions by hydrogen bonds. As the number of water molecules increases, the hydrogen bond between the anion and the basal layer gradually weakens and disappears when the number of water molecules exceeds 32. The hydrogen bond between the anion and the water molecule gradually increases, reaching an extreme value when the number of water molecules is 16. The interlayer spacing of Ni3Al-LDH is not linear with the number of water molecules. The interlayer spacing increases slowly when the number of water molecules is more than 24. The maximum layer spacing is stable at around 19 Å. The interlayer spacing, binding energy, and hydration energy show an upper limit for swelling: the number of water molecules is 32. When the number of interlayer water molecules is 16, the water molecules' layer structure and LDH interlayer spacing are suitable for anions to obtain the maximum diffusion rate, 10.97 × 10-8 cm2·s-1.

First-Principles Study on Interlayer Spacing and Structure Stability of NiAl-Layered Double Hydroxides.

Interlayer spacing and structure stability of layered double hydroxides (LDHs) on their application performance in adsorption, ion exchange, catalysis, carrier, and energy storage is important. The effect of different interlayer anions on the interlayer spacing and structure stability of LDHs has been less studied, but it is of great significance. Therefore, based on density functional theory (DFT), the computational model with 10 kinds of anions intercalated Ni3Al-A-LDHs (A = Cl-, Br-, I-, OH-, NO3 -, CO3 2-, SO4 2-, HCOO-, C6H5SO3 -, C12H25SO3 -) and four Ni R Al-Cl-LDH models with different Ni2+/Al3+ ratios (R = 2, 3, 5, 8) were constructed to calculate and analyze interlayer spacing, structural stability, and their influence factors. It was found that the interlayer spacing order of Ni3Al-A-LDHs intercalated with different anions is OH- < CO3 2- < Cl- < Br- < I- < HCOO- < SO4 2- < NO3 - < C6H5SO3 - < C12H25SO3 -. The hydrogen bond network between the base layer and the interlayer anions affects the arrangement structure of the interlayer anions, which affects the interlayer spacing. For interlayer monatomic anions Cl-, Br-, and I- and the anion of comparable size in each direction SO4 2-, the interlayer spacing is positively correlated with the interlayer anion diameter. The larger difference between the long-axis and short-axis dimensions of the polyatomic anions results in the long axis of the anion being perpendicular to the basal layer, increasing interlayer spacing. The long-chain anion C12H25SO3 - intercalation system exhibits the largest layer spacing of 24.262 Å. As R value increases from 2 to 8, the interlayer spacing of Ni R Al-Cl-LDHs gradually increases from 7.964 to 8.124 Å. The binding energy order between the interlayer anion and basal layer is CO3 2- > SO4 2- > OH- > Cl- > Br- > I- > HCOO- > NO3 - > C12H25SO3 - > C6H5SO3 -. The smaller the interlayer spacing, the higher the binding energy and the stronger the structural stability of LDHs. The factors affecting structural stability mainly include the bond length and bond angle of the hydrogen bond and the charge interaction between the basal layer and interlayer anion. In the CO3 2- intercalated system, the hydrogen bond length exhibits the shortest of 1.95 Å and the largest bond angle of 163.68°. The density of states and energy band analysis show that the higher the number of charges carried by the anion, the stronger its ability to provide electrons to the basal layer.

Evaluation of coal seam floor water bursting in multi-aquifer Gequan coal mine, China.

A water-bursting evaluation of the coal seam floor is critical to ensure safety of coal mine production. The vulnerability index method based on AHP is selected for this study's evaluation method. Water pressure, measured specific yield, equivalent thickness of effective aquiclude, brittle rock thickness under mining pressure damage zone, distribution of faults, distribution of collapse column, distribution of endpoints, and the intersection of fault are taken as the evaluation index based on the analysis of geological data in the study area. The authors assessed the threat posed by the two aquifers in the lower portion of the coal seam. Separate evaluations were conducted on the Benxi and Ordovician limestone aquifers. The results' veracity was confirmed by comparing the obtained results to the water bursting point and a few boreholes. The evaluation results provide recommendations for the safe operation of coal mines.

A Three-Stage Magnetic Phase Transition Revealed in Ultrahigh-Quality van der Waals Bulk Magnet CrSBr.

van der Waals (vdW) magnets are receiving ever-growing attention nowadays due to their significance in both fundamental research on low-dimensional magnetism and potential applications in spintronic devices. The high crystalline quality of vdW magnets is the key to maintaining intrinsic magnetic and electronic properties, especially when exfoliated down to the two-dimensional limit. Here, ultrahigh-quality air-stable vdW CrSBr crystals are synthesized using the direct solid-vapor synthesis method. The high single crystallinity and spatial homogeneity have been thoroughly evidenced at length scales from submm to atomic resolution by X-ray diffraction, second harmonic generation, and scanning transmission electron microscopy. More importantly, specific heat measurements of ultrahigh-quality CrSBr crystals show three thermodynamic anomalies at 185, 156, and 132 K, revealing a stage-by-stage development of the magnetic order upon cooling, which is also corroborated with the magnetization and transport results. Our ultrahigh-quality CrSBr can further be exfoliated down to monolayers and bilayers easily, providing the building blocks of heterostructures for spintronic and magneto-optoelectronic applications.

Accelerable Self-Sintering of Solvent-Free Molybdenum/Wax Biodegradable Composites for Multimodally Transient Electronics.

Biodegradable conductive composites are key materials or components for printable transient electronics that can be fabricated in a low-cost and high-efficiency manner, thereby boosting their wide applications in biomedical engineering, hardware security, and environmental-friendly electronics. Continuous efforts in this area still lie in the development of strategies for highly conductive, safe, and reliable biodegradable conductive composite materials and devices. This paper introduces molybdenum/wax composites for multimodally printable transient electronics in which multiple transience modes including dissolution-induced degradation and thermally triggered degradation are available. Systematic experiments demonstrate several advantages and unique properties of this material system, including solvent-free fabrication, self-sintering behavior, and long-term and high conductivity via accelerable self-sintering treatment and rehealing capabilities. Notably, the immersion of molybdenum/wax composites in phosphate buffer solution can provide both positive effects (accelerated self-sintering-dominated) and negative effects (degradation-dominated) on their electrical conductivities. Mechanism analyses reveal the basis for balancing the degradation and accelerated self-sintering processes. The presented demonstrations foreshadow opportunities of the developed molybdenum/wax composites in rehealable electronics, on-demand smart transient electronics with multiple transience modes, and many other related unusual applications.