Utilization of Molecular Simulation Software Gaussian 03 to Design Absorbent for CO2 Capture

AbstractA preliminary study on the interaction between molecules of absorbent for CO2 absorption was undertaken using Gaussian 03 molecular simulation software. The results indicate that the molecular interaction energy has strong correlations with Henry's constant. The lower interaction energy between molecules, solvent molecules form an “associated complex” more stability, and therefore the worse the effect of CO2 absorption

A single-cell analysis of the molecular lineage of chordate embryogenesis

Progressive unfolding of gene expression cascades underlies diverse embryonic lineage development. Here, we report a single-cell RNA sequencing analysis of the complete and invariant embryonic cell lineage of the tunicate Ciona savignyi from fertilization to the onset of gastrulation. We reconstructed a developmental landscape of 47 cell types over eight cell cycles in the wild-type embryo and identified eight fate transformations upon fibroblast growth factor (FGF) inhibition. For most FGF-dependent asymmetric cell divisions, the bipotent mother cell displays the gene signature of the default daughter fate. In convergent differentiation of the two notochord lineages, we identified additional gene pathways parallel to the master regulator T/Brachyury. Last, we showed that the defined Ciona cell types can be matched to E6.5-E8.5 stage mouse cell types and display conserved expression of limited number of transcription factors. This study provides a high-resolution single-cell dataset to understand chordate early embryogenesis and cell lineage differentiation

In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning

Cracks and keyhole pores are detrimental defects in alloys produced by laser directed energy deposition (LDED). Laser-material interaction sound may hold information about underlying complex physical events such as crack propagation and pores formation. However, due to the noisy environment and intricate signal content, acoustic-based monitoring in LDED has received little attention. This paper proposes a novel acoustic-based in-situ defect detection strategy in LDED. The key contribution of this study is to develop an in-situ acoustic signal denoising, feature extraction, and sound classification pipeline that incorporates convolutional neural networks (CNN) for online defect prediction. Microscope images are used to identify locations of the cracks and keyhole pores within a part. The defect locations are spatiotemporally registered with acoustic signal. Various acoustic features corresponding to defect-free regions, cracks, and keyhole pores are extracted and analysed in time-domain, frequency-domain, and time-frequency representations. The CNN model is trained to predict defect occurrences using the Mel-Frequency Cepstral Coefficients (MFCCs) of the lasermaterial interaction sound. The CNN model is compared to various classic machine learning models trained on the denoised acoustic dataset and raw acoustic dataset. The validation results shows that the CNN model trained on the denoised dataset outperforms others with the highest overall accuracy (89%), keyhole pore prediction accuracy (93%), and AUC-ROC score (98%). Furthermore, the trained CNN model can be deployed into an in-house developed software platform for online quality monitoring. The proposed strategy is the first study to use acoustic signals with deep learning for insitu defect detection in LDED process.Comment: 36 Pages, 16 Figures, accepted at journal Additive Manufacturin

Boosting the performance of single-atom catalysts via external electric field polarization

Single-atom catalysts represent a unique catalytic system with high atomic utilization and tunable reaction pathway. Despite current successes in their optimization and tailoring through structural and synthetic innovations, there is a lack of dynamic modulation approach for the single-atom catalysis. Inspired by the electrostatic interaction within specific natural enzymes, here we show the performance of model single-atom catalysts anchored on two-dimensional atomic crystals can be systematically and efficiently tuned by oriented external electric fields. Superior electrocatalytic performance have been achieved in single-atom catalysts under electrostatic modulations. Theoretical investigations suggest a universal “onsite electrostatic polarization” mechanism, in which electrostatic fields significantly polarize charge distributions at the single-atom sites and alter the kinetics of the rate determining steps, leading to boosted reaction performances. Such field-induced on-site polarization offers a unique strategy for simulating the catalytic processes in natural enzyme systems with quantitative, precise and dynamic external electric fields

unsteadymotionofasingledropletinsurfactantsolutions

A numerical investigation of the unsteady motion of a deformed drop released freely in another quiescent liquid contaminated by surfactant is presented in this paper. The finite difference method was used to solve numerically the coupled time-dependent Navier-Stokes and convective-diffusion equations in a body-fitted orthogonal coordinate system. Numerical simulation was conducted on the experimental cases, in which MIBK drops with the size ranging from 1.24 mm to 1.97 mm. rose and accelerated freely in pure water and in dilute sodium dodecyl sulphate (SDS) aqueous solution. The applicability of the numerical scheme was validated by the agreement between the simulation results and the experimental data. Both the numerical and experimental results showed that the velocity-time profile exhibited a maximum rising velocity for drops in SDS solutions, which was close to the terminal velocity in pure water, before it dropped down to a steady-state value. The effect of the sorption kinetics of surfactant on the accelerating motion was also evaluated. It is also suggested that introduction of virtual mass force into the formulation improved obviously the precision of numerical simulation of transient drop motion

CO2 capture by improved hot potash process

AbstractGlobal climate warming caused by emission of greenhouse gas including CO2 is one of serious problems nowadays. In an effort to mitigate CO2 emissions, one of most effectively clean energy plan is to produce power from coal using the integrated gasification combined cycle (IGCC). However, the cost of existing CO2 capture technologies is still too high. Utilization of large-solubility and low-cost absorbent for CO2 capture in IGCC can effectively reduce the electricity price increase caused by addition of CO2 removal unit. As it needs to trap CO2 before combustion under high pressure in IGCC absorption is considered to be a better choice.HPP (Hot Potash Process) uses aqueous solution of potassium carbonate as the absorbent. Compared to physical solvent absorption method Rectisol and Selexol, HPP has relatively low investment and relatively high CO2 recovery. Even in comparison with other chemical absorbent amine method HPP still has advantages as good chemical stability and low vapor pressure.In this paper several activators piperidine, piperozine, pyrazine, morpholine, imidazole, N-hydroxyethyl piperozine, Naminoethyl piperozine, AMP was tested respectively at 70 °C. As a result, piperidine activation works best, followed by N-(2-hydroxyethyl)piperazine, N-(2-aminoethyl) piperazine, 2-amino-2-methyl-1 -propanol and piperazine, pyrazine and imidazole is at its worst. Among them, N-(2-hydroxyethyl)piperazine is less volatile, more stable and suitable as the activator. Absorbing capacity and absorbing rate of CO2 in carbonate aqueous solution with HPZ increases by 5% or more than those with PZ.An improved HPP process is presented adopting the new activator. In this process two de-absorption two columns is designed operating at different pressure. This makes it possible to reuse the heat of condensation during high pressure de-sorption in reboiler of low pressure de-sorption. By preliminary calculating the novel process can save energy consumption obviously. The steam consumption, cooling water consumption and power consumption declines by 43.30%, 31.81% and 10.57%, respectively. It is expected to develop a low-cost technology for capture CO2 from IGCC in the future

Non-phosgene synthesis of isocyanates based on CO2: Synthesis of methyl N-phenyl carbamate through coupling route with lead compound catalysts

The synthesis of methyl N-phenyl carbamate (MPC), the key intermediate for the non-phosgene synthesis of isocyanates based on CO2, was studied from the reaction of dimethyl carbonate and N,N'-diphenyl urea under pressure. A variety of solid catalysts were screened, which showed lead compounds such as PbO, PbO2, PbCO3, and 2PbCO(3)center dot Pb(OH)(2) had excellent catalytic activity. The characterization of XRD showed that the screened lead compound catalysts after reaction were changed into the same lead compound with the group -PbOH. With the increase of recycling times of the used lead compound catalysts, the selectivity of MPC and conversion of DPU were still about 99%. And the characterization of XRD and FRIR showed that new lead compound, which was produced with the increase of recycling times of the used lead compound catalysts, was also a lead compound with -PbOH. So the above results indicated that the real lead catalyst was the compound containing -PbOH. A possible reaction mechanism was discussed with the lead compound catalysts. (C) 2009 Elsevier B.V. All rights reserved