Mcallisterstephansen7767

The objective of this study was to develop a robust prediction model for the infinite dilution activity coefficients (γ ∞) of organic molecules in diverse ionic liquid (IL) solvents. Y-27632 supplier Electrostatic, hydrogen bond, polarizability, molecular structure, and temperature terms were used in model development. A feed-forward model based on artificial neural networks was developed with 34,754 experimental activity coefficients, a combination of 195 IL solvents (88 cations and 38 anions), and 147 organic solutes at a temperature range of 298 to 408 K. The root mean squared error (RMSE) of the training set and test set was 0.219 and 0.235, respectively. The R 2 of the training set and the test set was 0.984 and 0.981, respectively. The applicability domain was determined through a Williams plot, which implied that water and halogenated compounds were outside of the applicability domain. The robustness test shows that the developed model is robust. The web server supports using the developed prediction model and is freely available at https//preadmet.bmdrc.kr/activitycoefficient_mainpage/prediction/.In this study, we develop the mechanical metamaterial-enabled piezoelectric nanogenerators in the gyro-structure, which is reported as a novel green energy solution to generate electrical power under quasi-static excitations (i.e., less then 1 Hz) such as in the ocean environment. The plate-like mechanical metamaterials are designed with a hexagonal corrugation to improve their mechanical characteristics (i.e., effective bending stiffnesses), and the piezoelectric trips are bonded to the metaplates. The piezo-metaplates are placed in the sliding cells to obtain the post-buckling response for energy harvesting under low-frequency ocean motions. The corrugated mechanical metamaterials are fabricated using the three-dimensional additive manufacturing technique and are bonded with polyvinylidene fluoride strips, and the nanogenerator samples are investigated under the quasi-static loading. Theoretical and numerical models are developed to obtain the electrical power, and satisfactory agreements are observed. Optimization is conducted to maximize the generated electrical power with respect to the geometric consideration (i.e., changing the corrugation pattern of the mechanical metamaterials) and the material consideration (i.e., changing the mechanical metamaterials to anisotropic). In the end, we consider the piezoelectric nanogenerators as a potential green solution for the energy issues in other fields.The advanced exergy analysis can identify the improved potential of each component and the interaction among components of the refining processes. In this work, a new gasoline absorption-stabilization process (GASP) is proposed for better energy utilization considering the absorption process intensification, which can be further explained using exergy analysis. Both conventional and new GASPs are simulated in PRO/II, which are verified with the actual plant operation data. The energy performance of both conventional and new GASPs is evaluated through the advanced exergy analysis. The exergy efficiencies of conventional and new GASPs are 65.04 and 71.44%, respectively. In addition, the total exergy destruction rates are 7.79 and 6.01 MW, respectively. The total exergy destructions of 46.37 and 40.73% can be reduced, respectively. Though the stabilizer has the largest exergy destruction in both the processes, the air cooler for the rich gas in the new GASP has the largest potential for reducing exergy destruction, which is different from the conventional GASP. Furthermore, a sensitivity analysis of the new GASP is performed to study the effects of newly added operation and design parameters on the conventional and advanced exergy analyses of the absorber.Halloysite nanotubes (HNT) and ball-milled biochar (BC) incorporated biocompatible mesoporous adsorbents (HNT-BC@Alg) were synthesized for adsorption of aqueous heavy-metal ions. HNT-BC@Alg outperformed the BC, HNT, and BC@Alg in removing cadmium (Cd), copper (Cu), nickel (Ni), and lead (Pb). Mesoporous structure (∼7.19 to 7.56 nm) of HNT-BC@Alg was developed containing an abundance of functional groups induced from encapsulated BC and tubular HNT, which allowed heavy metals to infiltrate and interact with the adsorbents. Siloxane groups from HNT, oxygen-containing functional groups from BC, and hydroxyl and carboxyl groups from alginate polymer play a significant role in the adsorption of heavy-metal ions. The removal percentage of heavy metals was recorded as Pb (∼99.97 to 99.05%) > Cu (∼95.01 to 90.53%) > Cd (∼92.5 to 55.25%) > Ni (∼80.85 to 50.6%), even in the presence of 0.01/0.001 M of CaCl2 and Na2SO4 as background electrolytes and charged organic molecule under an environmentally relevant concentratiotion.By using first-principle calculations combined with the non-equilibrium Green's function approach, we studied the spin caloritronic properties of zigzag graphene nanoribbons with a nanobubble at the edge (NB-ZGNRs). The thermal spin-polarized currents can be induced by a temperature difference, and the spin Seebeck effect is found in the nanoribbon. The spin polarization, magnetoresistance, and Seebeck coefficients are discussed, which are strongly affected and can be tuned by the geometrical strain. Moreover, some novel spin caloritronic devices are designed, such as a device that generates bidirectional perfect spin currents and thermally induced giant magnetoresistances. Our results open up the possibility of tuning the spin caloritronic properties of the NB-ZGNR-based devices by changing the elastic strain on the graphene nanobubble.Herein, we report the green synthesis of copper-zirconium bimetallic nanoparticles (Cu-Zr BNPs) from aqueous solutions using Azadirachta indica leaf extract as a reducing and stabilizing agent. The CuO, ZrO2 NP, and Cu-Zr BNP samples were characterized by X-ray diffraction and Fourier transform infrared (FTIR) spectroscopy, and the morphologies of the samples were analyzed by high-resolution transmission electron microscopy (HR-TEM) with selected area electron diffraction analysis (SAED). The synthesized Cu-Zr BNPs have been employed as efficient catalysts for the selective N-methylation of aromatic and aliphatic amines with dimethyl carbonate. The effect of process conditions on the percentage conversion of benzylamine with dimethyl carbonate as a model reaction has been investigated. The Cu-Zr bimetallic nanoparticle catalytic system in a 12 molar ratio was able to convert amines into the corresponding N-methylated amines with a selectivity up to 91% at 180 °C in 4 h. The analysis of catalytic reusability confirmed that the reported heterogeneous catalyst can be used for five consecutive cycles without much loss in activity.