Dual-crosslinking gelatin-hyaluronic acid methacrylate based biomimetic PDAC desmoplastic niche enhances tumor-associated macrophages recruitment and M2-like polarization.

The tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) is characterized by deposition of desmoplastic matrix (including collagen and hyaluronic acid). And the interactions between tumor-associated macrophages (TAMs) and tumor cells play a crucial role in progression of PDAC. Hence, the appropriate model of tumor cell-macrophage interaction within the unique PDAC TME is of significantly important. To this end, a 3D tumor niche based on dual-crosslinking gelatin methacrylate and hyaluronic acid methacrylate hydrogels was constructed to simulate the desmoplastic tumor matrix with matching compressive modulus and composition. The bionic 3D tumor niche creates an immunosuppressive microenvironment characterized by the downregulation of M1 markers and upregulation of M2 markers in TAMs. Mechanistically, RNA-seq analysis revealed that the PI3K-AKT signaling pathway might modulate the phenotypic balance and recruitment of macrophages through regulating SELE and VCAM-1. Furthermore, GO and GSEA revealed the biological process of leukocyte migration and the activation of cytokine-associated signaling were involved. Finally, the 3D tumor-macrophage niches with three different ratios were fabricated which displayed increased M2-like polarization and stemness. The utilization of the 3D tumor niche has the potential to provide a more accurate investigation of the interplay between PDAC tumor cells and macrophages within an in vivo setting.

Transformation pathways of the carbon-containing group compounds during municipal sludge pyrolysis treatment.

Municipal sludge contains abundant amounts of carbon, with contents ranging from 14 % to 38 %. The various carbon-containing group compounds can be converted into beneficial products, but pollutants and greenhouse gases are also released through the municipal sludge pyrolysis process. Ascertaining the pathways by which carbon-containing group compounds is converted and transformed is crucial for addressing pollution concerns and promoting recycling. This study explored the transformation pathways of carbon-containing group compounds during the pyrolysis process of municipal sludge. The results showed that the three major carbon-containing group compounds including protein (61 %), cellulose (9 %), and hemicellulose (7 %), had significantly different pyrolysis temperature of 600 °C, 400 °C and 300 °C. In terms of gas pollution, most carbon was fully pyrolyzed into CO2. While the temperature raised up to 500 °C, a part of the CO2 converted into CO. Meanwhile, the various carbon-containing compounds exhibited distinct effects on gas production, which CH4 was produced more with cellulose and protein presenting in the sludge. When temperature increased to 700 °C, the 60 % of the carbon-containing group compounds were transformed into liquid and solid. The pyrolysis liquid in the low-temperature stage (30-300 °C) contained a relatively high aliphatics content and lower organooxygen species (OOSs) content (at 200 °C), suggesting a potential for resource utilization. The yield of CO in the gas rapidly increased as the temperature increased in the high-temperature stage (500-700 °C). The insights from this study hold practical implications for enhancing municipal sludge pyrolysis efficiency, reducing pollution, and facilitating more sustainable and resource-efficient practices.

Systematical Investigation of Flicker Noise in 14 nm FinFET Devices towards Stochastic Computing Application.

Stochastic computing (SC) is widely known for its high error tolerance and efficient computing ability of complex functions with remarkably simple logic gates. The noise of electronic devices is widely used to be the entropy source due to its randomness. Compared with thermal noise and random telegraph noise (RTN), flicker noise is favored by researchers because of its high noise density. Meanwhile, unlike using RRAM, PCRAM and other emerging memory devices as the entropy source, using logic devices does not require any additional process steps, which is significant for industrialization. In this work, we systematically and statistically studied the 1/f noise characteristics of 14 nm FinFET, and found that miniaturizing the channel area of the device or lowering the ambient temperature can effectively increase the 1/f noise density of the device. This is of great importance to improve the accuracy of the SC system and simplify the complexity of the stochastic number generator (SNG) circuit. At the same time, these rules of 1/f noise characteristics in FinFET devices can provide good guidance for our device selection in circuit design.

Matrix stiffness triggers chemoresistance through elevated autophagy in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) has a signature of extremely high matrix stiffness caused by a special desmoplastic reaction, which dynamically stiffens along with the pathological process. The poor prognosis and low five-year survival rate of PDAC are partly owing to chemoresistance triggered by substrate stiffness. Understanding the potential mechanisms of matrix stiffness causing PDAC chemoresistance is of great significance. In this study, methacrylated gelatin hydrogel was used as platform for PANC-1 and MIA-PaCa2 cell culture. The results indicated that compared to soft substrate, stiff substrate distinctively reduced the gemcitabine sensitivity of pancreatic cancer. Intriguingly, transmission electron microscopy, immunofluorescence staining, western blot and qRT-PCR assay showcased that the number of autophagosomes and the expression of LC3 were elevated. The observations indicate that matrix stiffness may regulate the autophagy level, which plays a vital role during chemoresistance. In brief, soft substrate exhibited low autophagy level, while the counterpart displayed elevated autophagy level. In order to elucidate the underlying interaction between matrix stiffness-mediated cell autophagy and chemoresistance, rescue experiments with rapamycin and chloroquine were conducted. We found that inhibiting cell autophagy dramatically increased the sensitivity of pancreatic cancer cells to gemcitabine in the stiff group, while promoting autophagy-driven chemoresistance in the soft group, demonstrating that matrix stiffness modulated chemoresistance via autophagy. Furthermore, RNA-seq results showed that miR-1972 may regulate autophagy level in response to matrix stiffness. Overall, our research shed light on the synergistic therapy of PDAC combined with gemcitabine and chloroquine, which is conducive to promoting a therapeutic effect.

A stable rhombohedral phase in ferroelectric Hf(Zr)1+xO2 capacitor with ultralow coercive field.

Hafnium oxide-based ferroelectric materials are promising candidates for next-generation nanoscale devices because of their ability to integrate into silicon electronics. However, the intrinsic high coercive field of the fluorite-structure oxide ferroelectric devices leads to incompatible operating voltage and limited endurance performance. We discovered a complementary metal-oxide semiconductor (CMOS)-compatible rhombohedral ferroelectric Hf(Zr)1+xO2 material rich in hafnium-zirconium [Hf(Zr)]. X-ray diffraction combined with scanning transmission electron microscopy reveals that the excess Hf(Zr) atoms intercalate within the hollow sites. We found that the intercalated atoms expand the lattice and increase the in-plane and out-of-plane stresses, which stabilize both the rhombohedral phase (r-phase) and its ferroelectric properties. Our ferroelectric devices, which are based on the r-phase Hf(Zr)1+xO2, exhibit an ultralow coercive field (~0.65 megavolts per centimeter). Moreover, we achieved a high endurance of more than 1012 cycles at saturation polarization. This material discovery may help to realize low-cost and long-life memory chips.

Biomimetic Microenvironmental Stiffness Boosts Stemness of Pancreatic Ductal Adenocarcinoma via Augmented Autophagy.

Pancreatic ductal adenocarcinoma (PDAC) features high recurrence rates and intensified lethality, accompanied by stiffening of the extracellular matrix (ECM) microenvironment, which is mainly due to the deposition, remodeling, and cross-linking of collagen. Boosted stemness plays an essential role during occurrence and progression, which indicates a poor prognosis. Therefore, it is of great importance to understand the effect of the underlying interaction of matrix stiffness and stemness on PDAC. For this purpose, a methacrylated gelatin (GelMA) hydrogel with tunable stiffness was applied for incubating MIA PaCa-2 and PANC-1 cells. The results demonstrated that compared to the soft group (5% GelMA, w/v), the expression of stemness-related genes (SOX2, OCT4, and NANOG) in the stiff group (10% GelMA, w/v) displayed pronounced elevation as well as sphere formation. Intriguingly, we also observed that matrix stiffness regulated autophagy of PDAC, which played a momentous role in stemness promotion. In order to clarify the underlying relationship between matrix stiffness-mediated cell autophagy and stemness, rescue experiments with rapamycin and chloroquine were conducted with transmission electron microscopy, immunofluorescence staining, sphere formation, and qRT-PCR assays to evaluate the level of stemness and autophagy. For exploring the molecular mechanism in depth, RNA-seq and differential expression of miRNAs were carried out, which may sensor and respond to matrix stiffness during the regulation of stemness and autophagy. In conclusion, we validated that blocking autophagy repressed the stemness induced by matrix stiffness in PDAC and provided a potential therapeutic strategy for this aggressive cancer.

Ultrasensitive enhanced Raman spectroscopy by hybrid surface-enhanced and interference-enhanced Raman scattering with metal-insulator-metal structures.

High-sensitivity, reproducible, and low-cost substrate has been a major obstacle for practical sensing application of surface-enhancement Raman scattering (SERS). In this work, we report a type of simple SERS substrate which is composed of metal-insulator-metal (MIM) structure of Ag nanoisland (AgNI)-SiO2-Ag film (AgF). The substrates are fabricated by only evaporation and sputtering processes, which are simple, fast and low-cost. By combining the hotspots and interference-enhanced effects in AgNIs and the plasmonic cavity (SiO2) between AgNIs and AgF, the proposed SERS substrate shows an enhancement factor (EF) of 1.83 × 108 with limit of detection (LOD) down to 10-17 mol/L for rhodamine 6 G (R6G) molecules. The EFs are ∼18 times higher than that of conventional AgNIs without MIM structure. In addition, the MIM structure shows excellent reproducibility with relative standard deviation (RSD) less than 9%. The proposed SERS substrate is fabricated only with evaporation and sputtering technique and the conventionally used lithographic methods or chemical synthesis are not required. This work provides a simple way to fabricate ultrasensitive and reproducible SERS substrates which show great promise for developing various biochemical sensors with SERS.

A comprehensive SERS, SEM and EDX study of individual atmospheric PM2.5 particles in Chengdu, China.

Characterization of atmospheric fine particulate matter (PM2.5) in large cities has important implications for the study of their sources and formation mechanisms, as well as in developing effective measures to control air pollution. Herein, we report a holistic physical and chemical characterization of PM2.5 by combining surface-enhanced Raman scattering (SERS) with scanning electron microscopy (SEM) and electron-induced X-ray spectroscopy (EDX). PM2.5 particles were collected in a suburban area of Chengdu, a large city in China with a population over 21 million. A special SERS chip composed of inverted hollow Au cone (IHAC) arrays was designed and fabricated to allow direct loading of PM2.5 particles. SERS and EDX were used to reveal the chemical composition, and particle morphologies were analyzed from SEM images. SERS data of atmospheric PM2.5 indicated qualitatively the presence of carbonaceous particulate matter, sulfate, nitrate, metal oxides and bioparticles. The EDX showed the presence of the elements C, N, O, Fe, Na, Mg, Al, Si, S, K, and Ca in the collected PM2.5. Morphology analysis showed that the particulates were mainly in the form of flocculent clusters, spherical, regular crystal shaped or irregularly shaped particles. Our chemical and physical analyses also revealed that the main sources of PM2.5 are automobile exhaust, secondary pollution caused by photochemical reactions in the air, dust, emission from nearby industrial exhaust, biological particles, other aggregated particles, and hygroscopic particles. SERS and SEM data collected during three different seasons showed that carbon-containing particles are the principal sources of PM2.5. Our study demonstrates that the SERS based technique, when combined with standard physicochemical characterization methods, is a powerful analytical tool to determine the sources of ambient PM2.5 pollution. Results obtained in this work may be valuable to the prevention and control of PM2.5 pollution in air.

Visualization and accuracy improvement of soil classification using laser-induced breakdown spectroscopy with deep learning.

Deep learning method is applied to spectral detection due to the advantage of not needing feature engineering. In this work, the deep neural network (DNN) model is designed to perform data mining on the laser-induced breakdown spectroscopy (LIBS) spectra of the ore. The potential of heat diffusion for an affinity-based transition embedding model is first used to perform nonlinear mapping of fully connected layer data in the DNN model. Compared with traditional methods, the DNN model has the highest recognition accuracy rate (75.92%). A training set update method based on DNN output is proposed, and the final model has a recognition accuracy of 85.54%. The method of training set update proposed in this work can not only obtain the sample labels quickly but also improve the accuracy of deep learning models. The results demonstrate that LIBS combined with the DNN model is a valuable tool for ore classification at a high accuracy rate.

Three-in-one customized bioink for islet organoid: GelMA/ECM/PRP orchestrate pro-angiogenic and immunoregulatory function.

Islet organoids open up new strategies for diabetes treatment and pancreatic tissue engineering. Digital light processing (DLP) bioprinting has been extensively applied to the construction of organoids due to its ability to provide precisely patterned scaffolds with fast printing time while specific tailored bioink is indispensable for islet organoid. Customized bioinks that meet different needs were created and frequently applied based on gelatin methacryloyl (GelMA) mixed with other ingredients. Decellularized extracellular matrix (ECM) retains many organic specific structural and functional components and is widespread utilized to reconstruct the native niche like environment. However, considerable cytokines and growth factors were inevitably lost during the decellularized process, while platelet rich plasma (PRP) contains a string of growth factors which often exerted pro-angiogenic role. Therefore, a customized specific bioink for constructing islet organoid based on GelMA, pancreatic ECM and PRP was prepared in our research. In vitro, tube formation assay, CD31 immunofluorescence and relative mRNA expression of vascular genes indicated that the bioink with distinctively promote angiogenesis potential. Macrophages polarization was also conducted, which exhibited superior expression of CD206 (M2 marker) and inferior expression of iNOS (M1 marker). 3D printed organoids maintain the activity of mouse islet ß-cells (MIN6) with enhanced glucose sensitivity. In vivo, the results of CD31, CD206 and iNOS immunofluorescence were consistent with that in vitro. In summary, we prepared and characterized specific custom-made bioink with orchestrating immune-regulation response indicated by abundant M2-polarized macrophages, attenuated inflammation, and promoted angiogenesis, which provides an underlying bioink for the fabrication of 3D printed islet organoid.

Hyaluronic acid methacrylate/pancreatic extracellular matrix as a potential 3D printing bioink for constructing islet organoids.

Islet transplantation has poor long-term efficacy because of the lack of extracellular matrix support and neovascularization; this limits its wide application in diabetes research. In this study, we develop a 3D-printed islet organoid by combining a pancreatic extracellular matrix (pECM) and hyaluronic acid methacrylate (HAMA) as specific bioinks. The HAMA/pECM hydrogel was validated in vitro to maintain islet cell adhesion and morphology through the Rac1/ROCK/MLCK signaling pathway, which helps improve islet function and activity. Further, in vivo experiments confirmed that the 3D-printed islet-encapsulated HAMA/pECM hydrogel increases insulin levels in diabetic mice, maintains blood glucose levels within a normal range for 90 days, and rapidly secretes insulin in response to blood glucose stimulation. In addition, the HAMA/pECM hydrogel can facilitate the attachment and growth of new blood vessels and increase the density of new vessels. Meanwhile, the designed 3D-printed structure was conducive to the formation of vascular networks and it promoted the construction of 3D-printed islet organoids. In conclusion, our experiments optimized the HAMA/pECM bioink composition and 3D-printed structure of islet organoids with promising therapeutic effects compared with the HAMA hydrogel group that can be potentially used in clinical applications to improve the effectiveness and safety of islet transplantation in vivo. STATEMENT OF SIGNIFICANCE: The extraction process of pancreatic islets can easily cause damage to the extracellular matrix and vascular system, resulting in poor islet transplantation efficiency. We developed a new tissue-specific bioink by combining pancreatic extracellular matrix (pECM) and hyaluronic acid methacrylate (HAMA). The islet organoids constructed by 3D printing can mimic the microenvironment of the pancreas and maintain islet cell adhesion and morphology through the Rac1/ROCK/MLCK signaling pathway, thereby improving islet function and activity. In addition, the 3D-printed structures we designed are favorable for the formation of new blood vessel networks, bringing hope for the long-term efficacy of islet transplantation.

Revisiting organic waste-source-dependent molecular-weight governing the characterization within humic acids liking to humic-reducing microorganisms in composting process.

Humic acids (HAs) coupled with humic-reducing microorganisms (HRMs) can facilitate contaminants reduction. Molecular-weight (MW) of HA governs the chemical and HRMs behavior. However, MW of HAs with chemical characteristics linking to HRMs in different wastes composting have never been investigated. Results from the HPSEC-UV analysis showed that composting significantly increased weight-average molecular weight (Mw) of HA with a broad range from 675 Da to 27983 Da, and governing heterogeneous chemical characteristics. In proteinaceous composts, MW< 4000 Da of HAs were greatly related to alkyl and carbonyl, while MW> 20000 Da of HAs were presented by oxygen-nitrogenous functional groups, methyl, and alkyl groups. For cellulosic composts, MW< 1500 Da and 4000-10000 Da of HAs were characterized by aliphatic ethers and aromatic groups. MW> 20000 Da of HAs were constructed by phenols, methoxy and nitrogen functional groups. In lignocellulosic composts, MW> 20000 Da of HAs were only characterized by aromatic groups. Furthermore, seven groups of HRMs adapted to the heterogeneous chemical characteristics within HAs ranked by MW were recognized. Consequently, the possible routes that composting properties response to the connections of HRMs-chemical structures-MW of HAs in proteinaceous, cellulosic and lignocellulosic composts were constructed, respectively. Our results can help to develop the fine classification-oriented approach for recycling utilization of organic wastes.

Effect of biochar derived from biogas residue on methane production during dry anaerobic fermentation of kitchen waste.

Kitchen wastes (KW) dramatically increasing with population and economy enhancing, and dry anaerobic fermentation was used to treat it. However, the large amount of biogas residue severely restricted the application of dry anaerobic fermentation, because the high total solid might lead to the system failure. Therefore, it is urgent to find appropriate way to improve the efficiency of dry anaerobic fermentation and reduce the great amount of biogas residue. In this study, a tentative experiment was conducted to investigate the effect of biochar prepared from biogas residue on the performance of dry anaerobic fermentation system. The results showed that almost half of the biogas residue was reduced and converted into biochar. At the presence of biochar, methane yield was 308.6 mL/gVS, which was 10.5% higher than that of control. Compared to the system without biochar, the highest volatile fatty acid (VFA) concentration was 19.3% higher and the percentage of acetate and valerate was 25.3％ and 12.8％, while it was 16.3% and 22.0% in the control, suggesting that biochar accelerated the degradation of VFA. Bacteria community diversity increased, Fastidiosipila and Proteiniphilum enriched at the presence of biochar, which might accelerate the hydrolysis and acidification of KW. Hydrogenotrophic methanogens was dominated and syntrophic acetate oxidation was the primary pathway to produce methane. This study developed a new recycle route for improving the efficiency of dry anaerobic fermentation while reducing the large amount of biogas residue generated from dry anaerobic fermentation.

Surface-enhanced Raman Scattering of Au-Ag bimetallic nanopillars fabricated using surface-plasmon lithography.

Arrays of gold-silver (Au-Ag) bimetallic nanopillars were fabricated by a newly developed surface-plasmon lithography (SPL) and their enhancement properties as surface-enhanced Raman scattering (SERS) substrates have been studied. We demonstrated that the SPL is a low-cost and high efficiency method for the fabrication of SERS substrates with both high sensitivity and reproducibility. The nanopillars showed a good response in the detection of methylene blue molecules at a low concentration of 1.0 × 10-11mol· l-1. The SERS enhancement factors (EFs) are on the orders of 107and the relative standard deviation of SERS intensity is <8% over an area of 50µm × 50µm. The EFs increase fast with the height increasing from 200 to 530 nm, then increase slowly when further increase the height of the nanopillars to 1100 nm. In addition, the Au-Ag bimetallic coating has shown much higher SERS enhancement than the coatings of either the pure Au or Ag. The excellent SERS enhancement and reproducibility of the Au-Ag coated nanopillars indicated that the fabricated SERS substrates can be used for the detection of biochemical molecules at trace level and the SPL is a promising method for fabrication of SERS substrates.

Long-Term Accuracy Enhancement of Binary Neural Networks Based on Optimized Three-Dimensional Memristor Array.

In embedded neuromorphic Internet of Things (IoT) systems, it is critical to improve the efficiency of neural network (NN) edge devices in inferring a pretrained NN. Meanwhile, in the paradigm of edge computing, device integration, data retention characteristics and power consumption are particularly important. In this paper, the self-selected device (SSD), which is the base cell for building the densest three-dimensional (3D) architecture, is used to store non-volatile weights in binary neural networks (BNN) for embedded NN applications. Considering that the prevailing issues in written data retention on the device can affect the energy efficiency of the system's operation, the data loss mechanism of the self-selected cell is elucidated. On this basis, we introduce an optimized method to retain oxygen ions and prevent their diffusion toward the switching layer by introducing a titanium interfacial layer. By using this optimization, the recombination probability of Vo and oxygen ions is reduced, effectively improving the retention characteristics of the device. The optimization effect is verified using a simulation after mapping the BNN weights to the 3D VRRAM array constructed by the SSD before and after optimization. The simulation results showed that the long-term recognition accuracy (greater than 105 s) of the pre-trained BNN was improved by 24% and that the energy consumption of the system during training can be reduced 25,000-fold while ensuring the same accuracy. This work provides high storage density and a non-volatile solution to meet the low power consumption and miniaturization requirements of embedded neuromorphic applications.

Coordination of bacterial biomarkers with the dominant microbes enhances triclosan biodegradation in soil amended with food waste compost and cow dung compost.

Increasing concerns regarding the micropollutant triclosan (TCS) derive from its potential threats to human health and ecological security. Compost addition have been verified to be effective in soil remediation, however, the biodegradation of TCS under compost amendment in soil remain unclear. This study investigated the removal of TCS in soils amended with food waste compost (FS), cow dung compost (CS) and sludge compost (SS), respectively, explored the key TCS-degraders and biological mechanisms of TCS removal. Compost addition significantly enhanced the removal of TCS (p < 0.05) in the order of FS > CS > SS. The dosage of 20% (w/w) was the most efficient one and the ultimate concentrations of TCS were decreased by 76.67%, 67.90% and 56.79% compared with CK, respectively. The abundance of key dominant bacterial genus (7 in FS and 4 in CS) and fungal genus (3 in FS and CS) was stimulated due to the increase of soil nutrient factors (including dissolved organic carbon, DOC; soil organic matter, SOM; ammonium nitrogen, NH4+; nitrate nitrogen, NO3-) and the decrease of pH. A negative correlation between these dominant microbes and TCS concentration indicated their potential effect on TCS degradation. A total of four bacterial biomarkers, namely Saccharomonospora, Aequorivita, Bacillaceae and Fodinicurvataceae (both at family level) were the key TCS-degraders. Structural equation model (SEM) indicated that the improvement of soil nutrient factors in FS and CS promoted TCS biodegradation by improving the activity of bacterial biomarkers, as while, the key dominant microbes showed good tolerance to TCS stress. However, there were no significant biological effects on TCS in SS group. Network analysis further confirmed that it was the coordination of bacterial biomarkers with the dominant microbes that enhanced TCS biodegradation in soil amended with food waste compost and cow dung compost.

Surface-enhanced Raman scattering with gold-coated silicon nanopillars arrays: The influence of size and spatial order.

Nanopillars have been extensively explored as promising substrates for surface-enhanced Raman scattering (SERS) owing to their high sensitivity and excellent reproducibility. Most of the researches have been focused on the fabrication methods of nanopillars, and the dependences of SERS effects on geometrical size and spatial order are rarely investigated. In this work, SERS properties of nanopillars with different sizes (115-185 nm) and spatial orders (square and rhombus orders) have been studied. The work has shown that the nanopillars not only have high enhancement capability and high signal reproducibility, but also the enhancement is insensitive to the size and spatial orders. The measured enhancement factors (EFs) are 2.3-4.0 × 106 and signal reproducibility (relative standard deviation, RSD) are âˆ¼ 5.2%-6.9%, which are among the best of the similar SERS substrates reported. The variation of SERS intensity was as low as approximately 4.8% with the variation of pillar size from 115, 135, 145, to 160 nm. The insensitiveness and high reproducibility have been ascribed to the combined excitation of localized surface plasmon resonance (LSPR) and propagating surface plasmons (SPPs) of the nanopillars. Optical properties of the nanopillars are studied both experimentally and numerically to understand the physics behind the SERS performance.

Classification technology of domestic waste from 2000 to 2019: a bibliometrics-based review.

Waste classification is to reduce solid waste and its associated environmental pollution. This paper applied bibliometrics to assess publications related to classification technology of domestic waste from 2000 to 2019. A total of 466 publications were retrieved. The results showed the number of citations and papers increased rapidly. The major publication type regarding waste classification technology is article and English is the primary language for academic communication. The research is multidisciplinary and interdisciplinary, and its research directions are mainly divided into "Engineering," "Environmental Sciences Economics," and "Chemistry." It was identified that Waste Management (85) published most of papers in this topic. Meanwhile, China (93) contributed the most of publications, followed by the USA (42), France (40), Japan (36), and Italy (28). European countries are in the leading position in the study of garbage classification technology. Plastics and waste metals were the existing focus of waste classification technology, and waste identification and classification has become an important classification method. In addition, we also summarized the current mainstream technology progress and possible research challenges.

A highly CMOS compatible hafnia-based ferroelectric diode.

Memory devices with high speed and high density are highly desired to address the 'memory wall' issue. Here we demonstrated a highly scalable, three-dimensional stackable ferroelectric diode, with its rectifying polarity modulated by the polarization reversal of Hf0.5Zr0.5O2 films. By visualizing the hafnium/zirconium lattice order and oxygen lattice order with atomic-resolution spherical aberration-corrected STEM, we revealed the correlation between the spontaneous polarization of Hf0.5Zr0.5O2 film and the displacement of oxygen atom, thus unambiguously identified the non-centrosymmetric Pca21 orthorhombic phase in Hf0.5Zr0.5O2 film. We further implemented this ferroelectric diode in an 8 layers 3D array. Operation speed as high as 20 ns and robust endurance of more than 109 were demonstrated. The built-in nonlinearity of more than 100 guarantees its self-selective property that eliminates the need for external selectors to suppress the leakage current in large array. This work opens up new opportunities for future memory hierarchy evolution.

Biochar-related studies from 1999 to 2018: a bibliometrics-based review.

Biochar has been paid great attentions during the last two decades, because of its resources potentials and environmental benefits. A bibliometric analysis was applied to assess the publications regarding the keyword biochar from the Web of Science database during the period of 1999 to 2018. A total of 8629 publications were obtained with a rapid increase of annual citations and number of papers. The research topics were diversified, which were mainly divided into "Environmental Sciences and Ecology," "Agriculture," and "Engineering." Bioresource Technology was the journal which published most of the relevant papers. China ranked first in the number of published papers, followed by the USA, Australia, UK, and Germany. Especially, China established close collaboration with the USA in joint publication. Analysis of the keywords indicated that biochar production, comparative sorption, soil-applied black carbon, and soil management were the main research hotspots of biochar. The burst detection reflected that the innovation of biochar production and the new application field of biochar was the future research trends. These results can provide insight into the research progress regarding biochar.