Detecting pore size distribution of activated carbon by low-field nuclear magnetic resonance

In this study, the transverse relaxation time (T₂) of activated carbon (AC) in different relative environment humidity was detected firstly by low-field nuclear magnetic resonance (LFNMR). The pore size (diameter) of AC distributions was calculated by the relationship between T₂ and surface relaxation rate (ρ), where ρ was obtained by the detection of nine porous materials with known pore size. The results showed that the pore size distributions of AC calculated by ρ < 0.19 nm/ms were in good agreement with that obtained by nitrogen adsorption method and proved that LFNMR as a new detection method was feasible for characterizing AC pore size distribution.     

Revealing the Effect of Surface Composition on Multiwalled Carbon Nanotubes Supported Pt-Fe Alloy Electrocatalysts for Methanol Oxidation Performance

The designs of efficient and inexpensive Pt-based catalysts for methanol oxidation reaction (MOR) are essential to boost the commercialization of direct methanol fuel cells. Here, the highly catalytic performance PtFe alloys supported on multiwalled carbon nanotubes (MWCNTs) decorating nitrogen-doped carbon (NC) have been successfully prepared via co-engineering of the surface composition and electronic structure. The Pt₁Fe₃@NC/MWCNTs catalyst with moderate Fe³⁺ feeding content (0.86 mA/mg_Pt) exhibits 2.26-fold enhancement in MOR mass activity compared to pristine Pt/C catalyst (0.38 mA/mg_Pt). Furthermore, the CO oxidation initial potential of Pt₁Fe₃@NC/MWCNTs catalyst is lower relative to Pt/C catalyst (0.71 V and 0.80 V). Benefited from the optimal surface compositions, the anti-corrosion ability of MWCNT, strong electron interaction between PtFe alloys and MWCNTs and the N-doped carbon (NC) layer, the Pt₁Fe₃@NC/MWCNTs catalyst presents an improved MOR performance and anti-CO poisoning ability. This study would open up new perspective for designing efficient electrocatalysts for the DMFCs field.     

Rice husk silica as a sustainable filler in the tire industry

In this paper, we studied commercially available precipitated rice husk silica (RHS) with conventional precipitated silica, which has nearly the same surface area, and replaced part of the carbon black with RHS and conventional silica in a basic tread formulation. All formulations were mixed with the same amount of filler during the study. Silica was used at 15, 30 and 50 phr loading, and part of the carbon black was replaced by silica. Compound curing characteristics, physical properties, rebound resilience, heat generation, abrasion loss, dynamic properties and morphology were analyzed. The results indicated that RHS demonstrated compound properties comparable to those of conventional silica. As part of the carbon black was replaced with conventional silica, a slower cure rate, higher rebound resilience, lower heat generation, lower abrasion loss, and lower tan delta were observed with no significant change in physical properties, but some changes in physical properties were observed using one way ANOVA analysis. We found the same trend when replacing part of the carbon black with RHS, such as a slower cure rate, higher rebound resilience, lower heat generation, lower abrasion loss, and lower tan delta with no significant change in physical properties, but some changes in physical properties were observed using one way ANOVA. This sustainable material could be used to replace conventional silica in tire compounding, as well as to replace a portion of carbon black with RHS for improved heat build-up, rolling resistance, and abrasion loss.     

Effect of sodium dodecyl sulfate on CO2 and H2S absorption enhancement of functionalized multiwall carbon nanotubes in water: Experimental study and empirical model

A single bubble absorption column was used to examine the effect of hydrodynamic on carbon dioxide (CO₂) and hydrogen sulfide (H₂S) absorption in pure water and water-based nanofluids dispersed with neat, and OH and NH₂ functionalized multiwall carbon nanotubes (MWCNTs). Sodium dodecyl sulfate (SDS) was used as a surfactant and stabilizer. The maximum absorption of CO₂ and H₂S were found to be 0.0038 mmol/m²·s and 0.056 mmol/m²·s using NH₂-MWCNTs /nanofluid with 0.5 wt% content, respectively. The diffusion coefficients of gases into the nanofluids were computed by using an equation attained based on Dankwert’s theory. A last, an empirical correlation was proposed to determine the Sherwood number for the absorption of the aforementioned gases into the nanofluids.     

Mechanism of BPh3-Catalyzed N-Methylation of Amines with CO2 and Phenylsilane: Cooperative Activation of Hydrosilane

BPh₃ catalyzes the N-methylation of secondary amines and the C-methylenation (methylene-bridge formation between aromatic rings) of N,N-dimethylanilines or 1-methylindoles in the presence of CO₂ and PhSiH₃; these reactions proceed at 30–40 °C under solvent-free conditions. In contrast, B(C₆F₅)₃ shows little or no activity. ¹¹B NMR spectra suggested the generation of [HBPh₃]⁻. The detailed mechanism of the BPh₃-catalyzed N-methylation of N-methylaniline ( 1 ) with CO₂ and PhSiH₃ was studied by using DFT calculations. BPh₃ promotes the conversion of two substrates (N-methylaniline and CO₂) into a zwitterionic carbamate to give three-component species [Ph(Me)(H)N⁺CO₂⁻⋅⋅⋅BPh₃]. The carbamate and BPh₃ act as the nucleophile and Lewis acid, respectively, for the activation of PhSiH₃ to generate [HBPh₃]⁻, which is used to produce key CO₂-derived species, such as silyl formate and bis(silyl)acetal, essential for the N-methylation of 1 . DFT calculations also suggested other mechanisms involving water for the generation of [HBPh₃]⁻ species.     

Bifurcation analysis of visual angle model with anticipated time and stabilizing driving behavior

In the light of the visual angle model (VAM), an improved car-following model considering driver's visual angle, anticipated time and stabilizing driving behavior is proposed so as to investigate how the driver's behavior factors affect the stability of the traffic flow. Based on the model, linear stability analysis is performed together with bifurcation analysis, whose corresponding stability condition is highly fit to the results of the linear analysis. Furthermore, the time-dependent Ginzburg-Landau (TDGL) equation and the modified Korteweg-de Vries (mKdV) equation are derived by nonlinear analysis, and we obtain the relationship of the two equations through the comparison. Finally, parameter calibration and numerical simulation are conducted to verify the validity of the theoretical analysis, whose results are highly consistent with the theoretical analysis.     

Chemical bonding in representative astrophysically relevant neutral,cation, and anion HCnH chains

Most existing studies assign a polyynic and cumulenic character of chemical bonding in carbon-based chains relying on values of the bond lengths. Building on our recent work, in this paper we add further evidence on the limitations of such an analysis and demonstrate the significant insight gained via natural bond analysis. Presently reported results include atomic charges, natural bond order and valence indices obtained from ab initio computations for representative members of the astrophysically relevant neutral and charged HC_2k/2k+1H chain family. They unravel a series of counter-intuitive aspects and/or help naive intuition in properly understanding microscopic processes, e.g., electron removal from or electron attachment to a neutral chain. Demonstrating that the Wiberg indices adequately quantify the chemical bonding structure of the HC_2k/2k+1H chains—while the often heavily advertised Mayer indices do not—represents an important message conveyed by the present study.     

桉树杂交种与其亲本的近红外光谱判别

研究桉树控制授粉后目标性状的基因作用方式是探索其基因重组规律的重要内容。常规的数量统计分析精度往往不高,而DNA分析的专业要求高,且费时费力。该研究利用近红外光谱(NIRs)研究不同基因型桉树杂交种、亲本及杂交种与亲本间近红外光谱信息的关系,探索NIRs用于桉树杂交种与其亲本判别的可行性和准确性。以控制授粉的桉树亲本及其杂交F1代材料为对象,每种基因型从各自田间试验分别选取10个单株,采集树冠中上部新鲜健康叶片。用手持式近红外仪Phazir Rx(1624)采集桉树杂交种与其亲本叶片的NIRs信息。每单株选10片完全生理成熟的健康叶片,避开叶脉扫描其正面光谱5次,以50条NIRs信息的均值代表单个叶片的NIRs信息,最终每个基因型获得10条NIRs信息。对原始NIRs采用二阶多项式S.G一阶导数预处理。预处理后的NIRs用于多元统计分析,首先对桉树杂交亲本和子代样本进行主成分分析(PCA),直观展示不同基因型的分类情况。然后运用簇类独立软模式(SIMCA)和偏最小二乘判别分析(PLS-DA)两种有监督的判别模式验证NIRs用于桉树杂交种与其亲本树种的分类判别效果。PCA结果显示,不同的亲本间、杂交种间及杂交种与亲本间样本的主因子得分可以清晰地将各基因型分开。SIMCA模式判别分析中,桉树杂交种样本到亲本PCA模型的样本距离显示,待判别样本能够形成单独的聚类,且能直观反映两者的遗传相似。PLS-DA判别结果显示,桉树杂交亲本的PLS模型能通过预测其杂交子代的响应变量将其与亲本准确分开。结果表明,桉树叶片的NIRs信息可以准确地反映桉树杂交子代遗传信息的传递规律,NIRs判别模型可以准确地将各种基因型予以区分。因此,NIRs信息不仅可用于桉树杂交种和纯种的定性判别,还可以分析桉树基因重组过程中加性遗传效应的大小,从而为桉树遗传基础分析及其育种改良研究提供理论支撑。     

A probabilistic approach to spectral analysis of growth-fragmentation equations

The growth-fragmentation equation describes a system of growing and dividing particles, and arises in models of cell division, protein polymerisation and even telecommunications protocols. Several important questions about the equation concern the asymptotic behaviour of solutions at large times: at what rate do they converge to zero or infinity, and what does the asymptotic profile of the solutions look like? Does the rescaled solution converge to its asymptotic profile at an exponential speed? These questions have traditionally been studied using analytic techniques such as entropy methods or splitting of operators. In this work, we present a probabilistic approach: we use a Feynman–Kac formula to relate the solution of the growth-fragmentation equation to the semigroup of a Markov process, and characterise the rate of decay or growth in terms of this process. We then identify the Malthus exponent and the asymptotic profile in terms of a related Markov process, and give a spectral interpretation in terms of the growth-fragmentation operator and its dual.