An Improved Dynamic Contact Model for Mass–Spring and Finite Element Systems Based on Parametric Quadratic Programming Method

<div><p>Abstract An improved dynamic contact model for mass-spring and finite element systems is proposed in this paper. The proposed model avoids the numerical troubles of spurious high-frequency oscillations for mass-spring and finite element systems in dynamic contact problems by using the parametric quadratic programming technique. The iterative process for determination of contact states are not required for each time step in the proposed method, as the contact states are transformed into the base exchanges in the solution of a standard quadratic programming problem. The proposed methodology improves stability and has good convergence behavior for dynamic contact problems. Numerical results demonstrate the validity of the proposed method.</p></div

Occurrence and Temporal Trends of Benzotriazole UV Stabilizers in Mollusks (2010–2018) from the Chinese Bohai Sea Revealed by Target, Suspect, and Nontarget Screening Analysis

Benzotriazole UV stabilizers (BZT-UVs), including 2-(3,5-di-tert-amyl-2-hydroxyphenyl)benzotriazole (UV-328) that is currently under consideration for listing under the Stockholm Convention, are applied in many commodities and industrial products. However, limited information is available on the interannual variation of their environmental occurrence. In this study, an all-in-one strategy combining target, suspect, and nontarget screening analysis was established to comprehensively explore the temporal trends of BZT-UVs in mollusks collected from the Chinese Bohai Sea between 2010 and 2018. Significant residue levels of the target analytes were determined with a maximum total concentration of 6.4 × 103 ng/g dry weight. 2-(2-Hydroxy-3-tert-butyl-5-methyl-phenyl)-5-chloro-benzotriazole (UV-326), 5-chloro-2-(3,5-di-tert-butyl-2-hydroxyphenyl)benzotriazole (UV-327), and 2-(2-hydroxy-5-methylphenyl) benzotriazole (UV-P) were the predominant analogues, and UV-328 was the most frequently detected BZT-UV with a detection frequency (DF) of 87%. Whereas five biotransformation products and six impurity-like BZT-UVs were tentatively identified, their low DFs and semi-quantified concentrations suggest that the targeted analytes were the predominant BZT-UVs in the investigated area. A gradual decrease in the total concentrations of BZT-UVs was observed, accompanied by downward trends of the abundant compounds (e.g., UV-326 and UV-P). Consequently, the relative abundance of UV-327 increased because of its consistent environmental presence. These results suggest that continuous monitoring and risk assessment of BZT-UVs other than UV-328 are of importance in China

An Integrated Workflow Assisted by In Silico Predictions To Expand the List of Priority Polycyclic Aromatic Compounds

The limited information in existing mass spectral libraries hinders an accurate understanding of the composition, behavior, and toxicity of organic pollutants. In this study, a total of 350 polycyclic aromatic compounds (PACs) in 9 categories were successfully identified in fine particulate matter by gas chromatography high resolution mass spectrometry. Using mass spectra and retention indexes predicted by in silico tools as complementary information, the scope of chemical identification was efficiently expanded by 27%. In addition, quantitative structure–activity relationship models provided toxicity data for over 70% of PACs, facilitating a comprehensive health risk assessment. On the basis of extensive identification, the cumulative noncarcinogenic risk of PACs warranted attention. Meanwhile, the carcinogenic risk of 53 individual analogues was noteworthy. These findings suggest that there is a pressing need for an updated list of priority PACs for routine monitoring and toxicological research since legacy polycyclic aromatic hydrocarbons (PAHs) contributed modestly to the overall abundance (18%) and carcinogenic risk (8%). A toxicological priority index approach was applied for relative chemical ranking considering the environmental occurrence, fate, toxicity, and analytical availability. A list of 39 priority analogues was compiled, which predominantly consisted of high-molecular-weight PAHs and alkyl derivatives. These priority PACs further enhanced source interpretation, and the highest carcinogenic risk was attributed to coal combustion

An Integrated Workflow Assisted by In Silico Predictions To Expand the List of Priority Polycyclic Aromatic Compounds

The limited information in existing mass spectral libraries hinders an accurate understanding of the composition, behavior, and toxicity of organic pollutants. In this study, a total of 350 polycyclic aromatic compounds (PACs) in 9 categories were successfully identified in fine particulate matter by gas chromatography high resolution mass spectrometry. Using mass spectra and retention indexes predicted by in silico tools as complementary information, the scope of chemical identification was efficiently expanded by 27%. In addition, quantitative structure–activity relationship models provided toxicity data for over 70% of PACs, facilitating a comprehensive health risk assessment. On the basis of extensive identification, the cumulative noncarcinogenic risk of PACs warranted attention. Meanwhile, the carcinogenic risk of 53 individual analogues was noteworthy. These findings suggest that there is a pressing need for an updated list of priority PACs for routine monitoring and toxicological research since legacy polycyclic aromatic hydrocarbons (PAHs) contributed modestly to the overall abundance (18%) and carcinogenic risk (8%). A toxicological priority index approach was applied for relative chemical ranking considering the environmental occurrence, fate, toxicity, and analytical availability. A list of 39 priority analogues was compiled, which predominantly consisted of high-molecular-weight PAHs and alkyl derivatives. These priority PACs further enhanced source interpretation, and the highest carcinogenic risk was attributed to coal combustion

Graded-Band-Gap Zinc–Tin Oxide Thin-Film Transistors with a Vertically Stacked Structure for Wavelength-Selective Photodetection

Filter-free wavelength-selective photodetectors have garnered significant attention due to the growing demand for smart sensors, artificial intelligence, the Internet of Everything, and so forth. However, the challenges associated with large-scale preparation and compatibility with complementary metal-oxide-semiconductor (CMOS) technology limit their wide-ranging applications. In this work, we address the challenges by constructing vertically stacked graded-band-gap zinc–tin oxide (ZTO) thin-film transistors (TFTs) specifically designed for wavelength-selective photodetection. The ZTO thin films with various band gaps are fabricated via atomic layer deposition (ALD) by varying the ALD cycle ratios of zinc oxide (ZnO) and SnO2. The ZTO film with a small Sn ratio exhibits a decreased band gap, and the resultant TFT shows a degraded performance, which can be attributed to the Sn4+ dopant introducing a series of deep-state energy levels in the ZnO band gap. As the ratio of Sn increases further, the band gap of the ZTO also increases, and the mobility of the ZTO TFT increases up to 30 cm2/V s, with a positive shift of the threshold voltage. The photodetectors employing ZTO thin films with distinct band gaps show different spectral responsivities. Then, vertically stacked ZTO (S-ZTO) thin films, with gradient band gaps increasing from the bottom to the top, have been successfully deposited using consecutive ALD technology. The S-ZTO TFT shows decent performance with a mobility of 18.4 cm2/V s, a threshold voltage of 0.5 V, an on–off current ratio higher than 107, and excellent stability under ambient conditions. The resultant S-ZTO TFT also exhibits obviously distinct photoresponses to light at different wavelength ranges. Furthermore, a device array of S-ZTO TFTs demonstrates color imaging by precisely reconstructing patterned illuminations with different wavelengths. Therefore, this work provides CMOS-compatible and structure-compact wavelength-selective photodetectors for advanced and integrable optoelectronic applications

Additional file 1 of GBDT_KgluSite: An improved computational prediction model for lysine glutarylation sites based on feature fusion and GBDT classifier

Additional file 1: Table S1. Performance of different feature representation