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A series of morpholine salt volatile corrosion inhibitors (VCIs) were synthesized via solid-phase chemical reactions. The corrosion inhibition performance was assessed using evaporation weight loss, VCI capability, and corrosion weight loss tests. The corrosion inhibition mechanisms of the morpholine salt VCIs for carbon steel in atmospheric conditions were explored through electrochemical testing under thin film electrolytes, X-ray photoelectron spectroscopy (XPS), and computational simulations. Morpholine carbonate exhibited higher volatility. Corrosion weight loss tests showed an >85% reduction for steel treated with morpholine benzoate or morpholine carbonate. The inhibitors' inhibition mechanism, elucidated through X-ray photoelectron spectroscopy (XPS) and computational simulations, revealed that morpholine carbonate and benzoate form protective layers via physical and chemical adsorption on the steel surface, coordinating with iron atoms through nitrogen and oxygen atoms. Quantum chemical calculations demonstrated that morpholine carbonate had stronger adsorption energy and electron transfer capabilities, indicating superior corrosion inhibition performance over morpholine benzoate. [ABSTRACT FROM AUTHOR]

This study utilized several coupled approaches to create powerful algorithms for forecasting the compressive strength (Cs) of concretes that include metakaolin (MK) and fly ash (FA). For this purpose, three various methods were considered, named random forests (RF), Categorical boosting model (CB), and extreme gradient boosting (XGB) by considering the seven most influential input variables. It was tried to divide the concrete components to binder value (B) to achieve the non-dimensional input variables. Herein, the cutting-edge Tasmanian devil Optimization (TDO) algorithm was linked with RF, XGB, and CB for the purpose of determining the optimal values of hyperparameters (named TD - CB, TD - RF, and TD - XG). It is worth mentioning that developing the mentioned algorithms optimized with TD to estimate the mechanical properties of the concrete containing several important admixtures can be recognized as this study’s contribution to practical applications. The findings indicate that the algorithms possess a notable capacity to precisely forecast the Cs of concrete, which includes MK and FA, with R2 bigger than roughly 0.97. The lower value of OBJ comprehensive index belonged to the TD - CB at 1.5762, followed by TD - XG at 1.9943 and then 2.3317 related to TD - RF with almost 70% reduction. The sensitivity analysis demonstrated that the prediction of Cs is highly influenced by all input parameters, which are higher than 0.8659, but a higher influence from MK/B at 0.9548. [ABSTRACT FROM AUTHOR]

Noble metal nanoporous materials hold great potential in the field of catalysis, owing to their high open structures and numerous low coordination surface sites. However, the formation of porous nanoparticles is restricted by particle size. Herein, we utilized a Pt1Bi2 intermetallic nanocatalyst to develop a dealloying approach for preparing nanoparticles with a bi-continuous porous and core–shell structure and proposed a mechanism for the formation of pores. The particle size used to form the porous structure can be <10 nm, which enhances the nanocatalyst's performance for the oxygen reduction reaction (ORR). This study provides a new understanding of the formation of porous materials via a dealloying approach. [ABSTRACT FROM AUTHOR]

In soybeans (Glycine max (L.) Merr.), their growth periods, DSF (days of sowing-to-flowering), and DFM (days of flowering-to-maturity) are determined by their required accumulative day-length (ADL) and active temperature (AAT). A sample of 354 soybean varieties from five world eco-regions was tested in four seasons in Nanjing, China. The ADL and AAT of DSF and DFM were calculated from daily day-lengths and temperatures provided by the Nanjing Meteorological Bureau. The improved restricted two-stage multi-locus genome-wide association study using gene–allele sequences as markers (coded GASM-RTM-GWAS) was performed. (i) For DSF and its related ADLDSF and AATDSF, 130–141 genes with 384–406 alleles were explored, and for DFM and its related ADLDFM and AATDFM, 124–135 genes with 362–384 alleles were explored, in a total of six gene–allele systems. DSF shared more ADL and AAT contributions than DFM. (ii) Comparisons between the eco-region gene–allele submatrices indicated that the genetic adaptation from the origin to the geographic sub-regions was characterized by allele emergence (mutation), while genetic expansion from primary maturity group (MG)-sets to early/late MG-sets featured allele exclusion (selection) without allele emergence in addition to inheritance (migration). (iii) Optimal crosses with transgressive segregations in both directions were predicted and recommended for breeding purposes, indicating that allele recombination in soybean is an important evolutionary drive. (iv) Genes of the six traits were mostly trait-specific involved in four categories of 10 groups of biological functions. GASM-RTM-GWAS showed potential in detecting directly causal genes with their alleles, identifying differential trait evolutionary drives, predicting recombination breeding potentials, and revealing population gene networks. [ABSTRACT FROM AUTHOR]