Detection of trace chlorine pollutants in recycled pulp using gas chromatography-tandem mass spectrometry with response surface-optimized carbon structure online catalysis.

RATIONALE: Chlorinated aromatics and alkanes are widely used for their flame retardancy, but they need to be monitored when used in recycled pulp. This paper reports the use of palladium acetate/activated carbon (Pa/Ac) activated by nitric acid as an online catalyst to determine chlorinated aromatics and chlorinated alkanes in recycled paper products using gas chromatography-tandem mass spectrometry (GC-MS/MS), which significantly improves the sensitivity of the method and remarkably lowers the detection limits. METHODS: The Pa/Ac catalyst was prepared using a self-made catalytic device and used as key to the online catalytic conversion of target chlorinated aromatic hydrocarbons and chlorinated alkanes for GC-MS/MS analysis. The response surface model was used to optimize catalytic conditions. Then GC-MS/MS in the multireaction monitoring mode with online catalysis was applied for the analysis of polychlorinated biphenyls, polychlorinated terphenyls, polychlorinated naphthalene, and chlorinated paraffins (CP) in recycled paper products. RESULTS: Compared with traditional methods, the Pa/Ac catalyst can transform chlorinated aromatic hydrocarbons into aromatic hydrocarbons through dechlorination hydrogenation, thus lowering the detection limit of the GC-MS/MS method significantly. It can transform paraffin chloride into the corresponding alkane to better distinguish short-chain, medium-chain, or long-chain CPs. Online catalytic conversion significantly improved the sensitivity and reproducibility (88.7%-113.1%) of the method. Tissue samples with various concentration levels of chlorinated aromatics and chlorinated alkanes were tested. The linearity range of the reduced target compounds in the reduction product solution was 0.02-1.00 µg/ml (R2  > 0.995). The quantitative detection limit was 0.03-0.05 µg/kg, and relative standard deviation was less than 6.9%. CONCLUSION: This study was the first to introduce the Pa/Ac catalytic device as an online catalytic unit in the determination of chlorinated aromatics and chlorinated alkanes using the GC-MS/MS method. The target compounds were converted into alkanes and aromatic hydrocarbons with unchanged carbon structures, and the method could achieve a low detection limit with no need for high-end methods such as GC-chemical ionization ion source (CI)-MS or high-resolution mass spectrometry. These methods are suitable for the determination of chlorine pollutants in recycled paper and its raw materials.

Topology Optimization Method of a Cavity Receiver and Built-In Net-Based Flow Channels for a Solar Parabolic Dish Collector.

The design of a thermal cavity receiver and the arrangement of the fluid flow layout within it are critical in the construction of solar parabolic dish collectors, involving the prediction of the thermal-fluid physical field of the receiver and optimization design. However, the thermal-fluid analysis coupled with a heat loss model of the receiver is a non-linear and computationally intensive solving process that incurs high computational costs in the optimization procedure. To address this, we implement a net-based thermal-fluid model that incorporates heat loss analysis to describe the receiver's flow and heat transfer processes, reducing computational costs. The physical field results of the net-based thermal-fluid model are compared with those of the numerical simulation, enabling us to verify the accuracy of the established thermal-fluid model. Additionally, based on the developed thermal-fluid model, a topology optimization method that employs a genetic algorithm (GA) is developed to design the cavity receiver and its built-in net-based flow channels. Using the established optimization method, single-objective and multi-objective optimization experiments are conducted under inhomogeneous heat flux conditions, with objectives including maximizing temperature uniformity and thermal efficiency, as well as minimizing the pressure drop. The results reveal varying topological characteristics for different optimization objectives. In comparison with the reference design (spiral channel) under the same conditions, the multi-objective optimization results exhibit superior comprehensive performance.

Expression of N-Terminal Cysteine Aß42 and Conjugation to Generate Fluorescent and Biotinylated Aß42.

Fluorescent derivatives of the ß-amyloid peptides (Aß) are valuable tools for studying the interactions of Aß with cells. Facile access to labeled expressed Aß offers the promise of Aß with greater sequence and stereochemical integrity, without impurities from amino acid deletion and epimerization. Here, we report methods for the expression of Aß42 with an N-terminal cysteine residue, Aß(C1-42), and its conjugation to generate Aß42 bearing fluorophores or biotin. The methods rely on the hitherto unrecognized observation that expression of the Aß(MC1-42) gene yields the Aß(C1-42) peptide, because the N-terminal methionine is endogenously excised by Escherichia coli. Conjugation of Aß(C1-42) with maleimide-functionalized fluorophores or biotin affords the N-terminally labeled Aß42. The expression affords ∼14 mg of N-terminal cysteine Aß from 1 L of bacterial culture. Subsequent conjugation affords ∼3 mg of labeled Aß from 1 L of bacterial culture with minimal cost for labeling reagents. High-performance liquid chromatography analysis indicates the N-terminal cysteine Aß to be >97% pure and labeled Aß peptides to be 94-97% pure. Biophysical studies show that the labeled Aß peptides behave like unlabeled Aß and suggest that labeling of the N-terminus does not substantially alter the properties of the Aß. We further demonstrate applications of the fluorophore-labeled Aß peptides by using fluorescence microscopy to visualize their interactions with mammalian cells and bacteria. We anticipate that these methods will provide researchers convenient access to useful N-terminally labeled Aß, as well as Aß with an N-terminal cysteine that enables further functionalization.

Collective topo-epitaxy in the self-assembly of a 3D quantum dot superlattice.

Epitaxially fused colloidal quantum dot (QD) superlattices (epi-SLs) may enable a new class of semiconductors that combine the size-tunable photophysics of QDs with bulk-like electronic performance, but progress is hindered by a poor understanding of epi-SL formation and surface chemistry. Here we use X-ray scattering and correlative electron imaging and diffraction of individual SL grains to determine the formation mechanism of three-dimensional PbSe QD epi-SL films. We show that the epi-SL forms from a rhombohedrally distorted body centred cubic parent SL via a phase transition in which the QDs translate with minimal rotation (~10°) and epitaxially fuse across their {100} facets in three dimensions. This collective epitaxial transformation is atomically topotactic across the 103-105 QDs in each SL grain. Infilling the epi-SLs with alumina by atomic layer deposition greatly changes their electrical properties without affecting the superlattice structure. Our work establishes the formation mechanism of three-dimensional QD epi-SLs and illustrates the critical importance of surface chemistry to charge transport in these materials.

A Reusable CNT-Supported Single-Atom Iron Catalyst for the Highly Efficient Synthesis of C-N Bonds.

C-N bond formation is regarded as a very useful and fundamental reaction for the synthesis of nitrogen-containing molecules in both organic and pharmaceutical chemistry. Noble-metal and homogeneous catalysts have frequently been used for C-N bond formation, however, these catalysts have a number of disadvantages, such as high cost, toxicity, and low atom economy. In this work, a low-toxic and cheap iron complex (iron ethylene-1,2-diamine) has been loaded onto carbon nanotubes (CNTs) to prepare a heterogeneous single-atom catalyst (SAC) named Fe-Nx /CNTs. We employed this SAC in the synthesis of C-N bonds for the first time. It was found that Fe-Nx /CNTs is an efficient catalyst for the synthesis of C-N bonds starting from aromatic amines and ketones. Its catalytic performance was excellent, giving yields of up to 96 %, six-fold higher than the yields obtained with noble-metal catalysts, such as AuCl3 /CNTs and RhCl3 /CNTs. The catalyst showed efficacy in the reactions of thirteen aromatic amine substrates, without the need for additives, and seventeen enaminones were obtained. High-angle annular dark-field scanning transmission electron microscopy in combination with X-ray absorption spectroscopy revealed that the iron species were well dispersed in the Fe-Nx /CNTs catalyst as single atoms and that Fe-Nx might be the catalytic active species. This Fe-Nx /CNTs catalyst has potential industrial applications as it could be cycled seven times without any significant loss of activity.

Personalized Nanotherapy by Specifically Targeting Cell Organelles To Improve Vascular Hypertension.

Ciliopathies caused by abnormal function of primary cilia include expanding spectrum of kidney, liver, and cardiovascular disorders. There is currently no treatment available for patients with cilia dysfunction. Therefore, we generated and compared two different (metal and polymer) cilia-targeted nanoparticle drug delivery systems (CTNDDS), CT-DAu-NPs and CT-PLGA-NPs, for the first time. These CTNDDS loaded with fenoldopam were further compared to fenoldopam-alone. Live-imaging of single-cell-single-cilium analysis confirmed that CTNDDS specifically targeted to primary cilia. While CTNDDS did not show any advantages over fenoldopam-alone in cultured cells in vitro, CTNDDS delivered fenoldopam more superior than fenoldopam-alone by eliminating the side effect of reflex tachycardia in murine models. Although slow infusion was required for fenoldopam-alone in mice, bolus injection was possible for CTNDDS. Though there were no significant therapeutic differences between CT-DAu-NPs and CT-PLGA-NPs, CT-PLGA-NPs tended to correct ciliopathy parameters closer to normal physiological levels, indicating CT-PLGA-NPs were better cargos than CT-DAu-NPs. Both CTNDDS showed no systemic adverse effect. In summary, our studies provided scientific evidence that existing pharmacological agent could be personalized with advanced nanomaterials to treat ciliopathy by targeting cilia without the need of generating new drugs.

Simultaneous Quantitative Analysis of Six Isothiazolinones in Water-Based Adhesive Used for Food Contact Materials by High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS).

In this study, a target analytical approach using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was developed to simultaneously determine six isothiazolinones containing 2-Methylisothiazol-3(2H)-one (MI), 5-Chloro-2-methyl-4-isothiazolin-3-one (CMI), 1,2-benzisothiazolin-3-one (BIT), 2-Octyl-3(2H)-isothiazolinone (OIT), Dichlorooctylisothiazolinone (DCOIT), and 2-methyl-1,2-benzisothiazolin-3-one (MBIT) in water-based adhesive used for food contact materials. The main factors affecting extraction efficiency such as extraction method, extraction time, extraction solvent, and solid-liquid ratio have been evaluated by using real adhesive samples. Multiple-reaction monitoring (MRM) was used for the qualitative and quantitative analyses of targeted isothiazolinones. This method was demonstrated as an effective and reliable technique for detecting multiple isothiazolinones with satisfactory recoveries (81.5~107.3%), and the limits of detection (LOD) and quantification (LOQ) were obtained at a low level. This method was validated and applied to the determination of six isothiazolinones in commercial water-based adhesives. The present results revealed that these adhesives contained a combination of isothiazolinones (BIT, MI, CMI, and MBIT) with the concentration ranging from 2.27 to 123.5 mg/kg. To our knowledge, it is the first time it has been reported that MBIT was detected in water-based adhesives used for food contact materials, which requires a further investigation for its migration to food and the risk to human health.

Numerical analysis of flow induced noise propagation in supercavitating vehicles at subsonic speeds.

Flow supercavitation begins when fluid is accelerated over a sharp edge, usually at the nose of an underwater vehicle, where phase change occurs and causes low density gaseous cavity to gradually envelop the whole object (supercavity) and thereby enabling higher speeds of underwater vehicles. The process of supercavity inception/development by means of "natural cavitation" and its sustainment through ventilated cavitation result in turbulence and fluctuations at the water-vapor interface that manifest themselves as major sources of hydrodynamic noise. Therefore in the present context, three main sources are investigated, namely, (1) flow generated noise due to turbulent pressure fluctuations around the supercavity, (2) small scale pressure fluctuations at the vapor-water interface, and (3) pressure fluctuations due to direct impingement of ventilated gas-jets on the supercavity wall. An understanding of their relative contributions toward self-noise is very crucial for the efficient operation of high frequency acoustic sensors that facilitate the vehicle's guidance system. Qualitative comparisons of acoustic pressure distribution resulting from aforementioned sound sources are presented by employing a recently developed boundary integral method. By using flow data from a specially developed unsteady computational fluid dynamics solver for simulating supercavitating flows, the boundary-element method based acoustic solver was developed for computing flow generated sound.

Indirect estimation of pediatric reference interval via density graph deep embedded clustering.

Establishing reference intervals (RIs) for pediatric patients is crucial in clinical decision-making, and there is a critical gap of pediatric RIs in China. However, the direct sampling technique for establishing RIs is resource-intensive and ethically challenging. Indirect estimation methods, such as unsupervised clustering algorithms, have emerged as potential alternatives for predicting reference intervals. This study introduces deep graph clustering methods into indirect estimation of pediatric reference intervals. Specifically, we propose a Density Graph Deep Embedded Clustering (DGDEC) algorithm, which incorporates a density feature extractor to enhance sample representation and provides additional perspectives for distinguishing different levels of health status among populations. Additionally, we construct an adjacency matrix by computing the similarity between samples after feature enhancement. The DGDEC algorithm leverages the adjacency matrix to capture the interrelationships between patients and divides patients into different groups, thereby estimating reference intervals for the potential healthy population. The experimental results demonstrate that when compared to other indirect estimation techniques, our method ensures the predicted pediatric reference intervals in different age and gender groups are closer to the true values while maintaining good generalization performance. Additionally, through ablation experiments, our study confirms that the similarity between patients and the multi-scale density features of samples can effectively describe the potential health status of patients.

Characterization and elimination efficiency of volatile organic compounds in mechanically recycled polyethylene terephthalate at various recycling stages.

The recycling of polyethylene terephthalate (PET) stands as an effective strategy for mitigating plastic pollution and reducing resource waste. The study aimed to investigate the characterization and elimination efficiency of volatile organic compounds (VOCs) present in rPET at various recycling stages using comprehensive two-dimensional gas chromatography-quadrupole-time-of-flight-mass spectrometry coupled with chemometrics. The results revealed that 52, 135, 95, 44, and 33 VOCs, mostly classified into three chemical groups, were tentatively identified in virgin - PET (v-PET), cold water washed - rPET (C-rPET), decontaminated - rPET (D-rPET), melt-extruded - rPET (M-rPET), and solid-state polycondensation - rPET (S-rPET), respectively. Regarding the VOCs with high and median detection frequencies, fatty acyls showed the highest elimination efficiency (100 % and 92 %), followed by organooxygen compounds (81 % and 99 %), others (97 % and 95 %), and benzene and substituted derivatives (82 % and 95 %) in term of HS-SPME. Following the recycling process, there was a general decrease in the concentration of almost all VOCs, as evidenced by the substantial reduction of o-Xylene, hexanoic acid, octanal, and D-limonene from 18.11, 22.43, 30.74, and 7.41 mg/kg to 0, 0, 3.97, and 0 mg/kg, respectively. However, it was noteworthy that the VOCs identified in the samples were not completely extracted, owing to the limitations of HS-SPME. Furthermore, chemometrics analysis indicated significant discrimination among VOCs from vPET, C-rPET, D-rPET, and M-rPET, while indistinct differences were observed between M-rPET and S-rPET. This study contributes to the enhancement of the recycling process and emphasizes the importance of safeguarding consumer health in terms of elimination of VOCs.

Development and evaluation of a disulfidoptosis-related lncRNA index for prognostication in clear cell renal cell carcinoma.

Background: This study introduces a novel prognostic tool, the Disulfidoptosis-Related lncRNA Index (DRLI), integrating the molecular signatures of disulfidoptosis and long non-coding RNAs (lncRNAs) with the cellular heterogeneity of the tumor microenvironment, to predict clinical outcomes in patients with clear cell renal cell carcinoma (ccRCC). Methods: We analyzed 530 tumor and 72 normal samples from The Cancer Genome Atlas (TCGA), employing k-means clustering based on disulfidoptosis-associated gene expression to stratify ccRCC samples into prognostic groups. lncRNAs correlated with disulfidoptosis were identified and used to construct the DRLI, which was validated by Kaplan-Meier and receiver operating characteristic curves. We utilized single-cell deconvolution analysis to estimate the proportion of immune cell types within the tumor microenvironment, while the ESTIMATE and TIDE algorithms were employed to assess immune infiltration and potential response to immunotherapy. Results: The Disulfidoptosis-Related lncRNA Index (DRLI) effectively stratified ccRCC patients into high and low-risk groups, significantly impacting survival outcomes (P < 0.001). High-risk patients, marked by a unique lncRNA profile associated with disulfidoptosis, faced worse prognoses. Single-cell analysis revealed marked tumor microenvironment heterogeneity, especially in immune cell makeup, correlating with patient risk levels. In prognostic predictions, DRLI outperformed traditional clinical indicators, achieving AUC values of 0.779, 0.757, and 0.779 for 1-year, 3-year, and 5-year survival in the training set, and 0.746, 0.734, and 0.750 in the validation set. Notably, while the constructed nomogram showed exceptional predictive capability for short-term prognosis (AUC = 0.877), the DRLI displayed remarkable long-term predictive accuracy, with its AUC value reaching 0.823 for 10-year survival, closely approaching the nomogram's performance. Conclusions: The study introduces the DRLI as a groundbreaking molecular stratification tool for ccRCC, enhancing prognostic precision and potentially guiding personalized treatment strategies. This advancement is particularly significant in the context of long-term survival predictions. Our findings also elucidate the complex interplay between disulfidoptosis, lncRNAs, and the immune microenvironment in ccRCC, offering a comprehensive perspective on its pathogenesis and progression. The DRLI and the nomogram together represent significant strides in ccRCC research, highlighting the importance of molecular-based assessments in predicting patient outcomes.

Potential safety concerns of volatile constituents released from coffee-ground-blended single-use biodegradable drinking straws: A chemical space perspective.

Incorporating spent coffee grounds into single-use drinking straws for enhanced biodegradability also raises safety concerns due to increased chemical complexity. Here, volatile organic compounds (VOCs) present in coffee ground straws (CGS), polylactic acid straws (PLAS), and polypropylene straws (PPS) were characterized using headspace - solid-phase microextraction and migration assays, by which 430 and 153 VOCs of 10 chemical categories were identified by gas chromatography - mass spectrometry, respectively. Further, the VOCs were assessed for potential genetic toxicity by quantitative structure-activity relationship profiling and estimated daily intake (EDI) calculation, revealing that the VOCs identified in the CGS generally triggered the most structural alerts of genetic toxicity, and the EDIs of 37.9% of which exceeded the threshold of 0.15 µg person-1 d-1, also outnumbering that of the PLAS and PPS. Finally, 14 VOCs were prioritized due to their definite hazards, and generally higher EDIs or detection frequencies in the CGS. Meanwhile, the probability of producing safer CGS was also illustrated. Moreover, it was uncovered by chemical space that the VOCs with higher risk potentials tended to gather in the region defined by the molecular descriptor related to electronegativity or octanol/water partition coefficient. Our results provided valuable references to improve the chemical safety of the CGS, to promote consumer health, and to advance the sustainable development of food contact materials.

Characterization, hazard identification, and risk assessment of volatile organic compounds in Poly(butylene adipate-co-terephthalate)-based food contact articles.

The chemical safety of poly (butylene adipate-co-terephthalate) (PBAT) based food contact articles (FCAs) has aroused increasing toxicological concerns in recent years, but the chemical characterization and associated risk assessment still remain inadequate as it fails to elucidate the distribution pattern and discern the potential genotoxic and carcinogenic hazards of the identified substances. Herein, the volatile organic compounds (VOCs) in 50 batches of PBAT-based FCAs of representative categories and 10 batches of PLA and PBAT pellets were characterized, by which 237 VOCs of 10 chemical categories were identified and exhibited characteristic distribution patterns in the chemical spaces derived from their molecular descriptors. Chemical hazards associated with the identified VOCs were discerned by a hazard-driven classification scheme integrating hazard-related knowledge from multiple publicly available sources, and 34 VOCs were found to bear genotoxic or carcinogenic hazards and to feature higher average molecular weight than the other VOCs. Finally, the Risk and hazard quotient (HQ) calculated as the metrics of risk suggested that all identified VOCs posed acceptable risks (Risk<10-4 or HQ < 1), whereas oxolane, butyrolactone, N,N-dimethylacetamide, 2-butoxyethanol, benzyl alcohol, and 1,2,3-trichloropropane posed non-negligible (Risk>10-6) genotoxic or carcinogenic risk and thus should be of prioritized concern to promote the chemical safety of PBAT-based FCAs.

A full-scale house fly (Diptera: Muscidae) larvae bioconversion system for value-added swine manure reduction.

Manure produced from confined animal farms can threaten public and environmental health if not managed properly. Herein, a full-scale commercial bioconversion operation in DeQing County, China for value-added swine manure reduction using house fly, Musca domestica L., larvae is reported. The greenhouse-assisted larvae bioreactor had a maximum daily treatment capacity of 35 m(3) fresh raw manure per day. The bioconversion process produced a fresh larvae yield of 95-120 kg m(3) fresh raw manure. This process provided an alternative animal foodstuff (having 56.9 and 23.8% protein and total fat as dry matter, respectively), as well as captured nutrients for agricultural re-utilization. Bioconversion reduced odour emission (characterized by 3-methylindole) and the Escherichia coli (E. coli) index by 94.5 and 92.0%, respectively, and reductions in total weight, moisture and total Kjeldahl nitrogen in solids were over 67.2, 80.0 and 76.0%, respectively. Yearly profit under this trial period ranged from US$33.4-46.1 per m(3). It is concluded that swine manure larvae bioconversion technology with subsequent production of value-added bio-products can be a promising avenue when considering a programme to reduce waste products in an intensive animal production system.

Chemometrics-based Discrimination of Virgin and Recycled Acrylonitrile-Butadiene-Styrene Plastics Toys via Non-targeted Screening of Volatile Substances.

Owing to the growing emphasis on child safety, it is greatly urgent to identify and assess the unknown compounds and discriminate the recycled materials for plastic toys. In this study, gas chromatography mass spectrometry coupled with static headspace has been optimized by response surface methodology for non-targeted screening of unknown volatiles in acrylonitrile-butadiene-styrene (ABS) plastic toys. Optimum conditions for static headspace were 120 °C for extraction temperature and 48 min for extraction time. A total of 83 volatiles in 11 categories were qualitatively identified by matching the NIST database library, retention index and standard materials. Considering high positive rate and potential toxicity, high-risk volatiles in ABS plastic toys were listed and traced for safety pre-warning. Moreover, the differential volatiles between virgin and recycled ABS plastics were screened out by orthogonal partial least-squares discrimination analysis. Principal component analysis, hierarchical cluster analysis and linear discrimination analysis were employed to successfully discriminate recycled ABS plastic toys based on the differential volatiles. The proposed strategy represents an effective and promising analytical method for non-targeted screening and risk assessment of unknown volatiles and discrimination of recycled materials combining with various chemometric techniques for children's plastic products to safeguard children's health.

A nomogram based on the preoperative neutrophil-to-lymphocyte ratio to distinguish sarcomatoid renal cell carcinoma from clear cell renal cell carcinoma.

Objective: Our study aimed to assess the predictive value of the preoperative neutrophil-to-lymphocyte ratio(NLR) in distinguishing sarcomatoid renal cell carcinoma (SRCC) from clear cell renal cell carcinoma(CCRCC) and to developing a nomogram based on the preoperative NLR and other factors to distinguish SRCC from CCRCC. Materials and methods: The database involved 280 patients, including 46 SRCC and 234 CCRCC. logistic analysis was conducted to select the variables associated with identifying SRCC preoperatively, and subgroup analysis was used to further validate the ability of NLR with preoperative identification of SRCC.In addition, The data were randomly separated into a training cohort(n=195) and a validation cohort(n=85). And an NLR-based nomogram was plotted based on the logistic analysis results. The nomogram was evaluated according to its discrimination, consistency, and clinical benefits. Results: Multivariate analysis indicated that NLR, flank pain, tumor size, and total cholesterol(TC) were independent risk factors for identifying SRCC. The results of subgroup analysis showed that higher NLR was associated with a higher probability of SRCC in most subgroups. The area under the curve(AUC) of the training and validation cohorts were 0.801 and 0.738, respectively. The results of the calibration curve show high consistency between predicted and actual results. Decision Curve Analysis(DCA) showed clinical intervention based on the model was beneficial over most of the threshold risk range. Conclusion: NLR is a potential indicator for preoperative differentiation of SRCC and CCRCC, and the predictive model constructed based on NLR has a good predictive ability. The new model could provide suggestions for the early identification of SRCC.

Synaptic Resistor Circuits Based on Al Oxide and Ti Silicide for Concurrent Learning and Signal Processing in Artificial Intelligence Systems.

Neurobiological circuits containing synapses can process signals while learning concurrently in real time. Before an artificial neural network (ANN) can execute a signal-processing program, it must first be programmed by humans or trained with respect to a large and defined data set during learning processes, resulting in significant latency, high power consumption, and poor adaptability to unpredictable changing environments. In this work, a crossbar circuit of synaptic resistors (synstors) is reported, each synstor integrating a Si channel with an Al oxide memory layer and Ti silicide Schottky contacts. Individual synstors are characterized and analyzed to understand their concurrent signal-processing and learning abilities. Without any prior training, synstor circuits concurrently execute signal processing and learning in real time to fly drones toward a target position in an aerodynamically changing environment faster than human controllers, and with learning speed, performance, power consumption, and adaptability to the environment significantly superior to an ANN running on computers. The synstor circuit provides a path to establish power-efficient intelligent systems with real-time learning and adaptability in the capriciously mutable real world.

Occurrence of volatile contaminants in recycled poly(ethylene terephthalate) by HS-SPME-GC×GC-QTOF-MS combined with chemometrics for authenticity assessment of geographical recycling regions.

A comparison was performed on various methods detecting the volatile contaminants (VCs) in recycled poly(ethylene terephthalate) (rPET) flakes, the results demonstrated that head-space solid phase micro-extraction combined with comprehensive two-dimensional gas chromatograph-tandem quadrupole-time-of-flight mass spectrometry (HS-SPME-GC×GC-QTOF-MS) was a sensitive, effective, accurate method, and successfully applied to analyze 57 rPET flakes collected from different recycling plants in China. A total of 212 VCs were tentatively identified, and the possible source were associated with plastic, food, and cosmetics. 45 VCs are classified as high-priority compounds with toxicity level IV or V and may pose a risk to human health. Combined chemometrics for further analysis revealed that significant differences among these three geographical recycling regions. 6, 7, and 6 volatile markers were chosen based on VIP values and S-plot among plant1 plant 2 and plant 3, respectively. The markers differed significantly between recycled rPET samples in three geographical recycling regions based on chemometrics analysis. The initial classification rate and cross-validation accuracy were 100% on the identified VCs. These significant differences demonstrate that a systematic study is needed to obtain a comprehensive data on the contamination of rPET for food contact applications in China.