Blends of Bio-Based Poly(Limonene Carbonate) with Commodity Polymers

In this study, blends of the bio-based poly(limonene carbonate) (PLimC) with different commodity polymers are investigated in order to explore the potential of PLimC toward generating more sustainable polymer materials by reducing the amount of petro- or food-based polymers. PLimC is employed as minority component in the blends. Next to the morphology and thermal properties of the blends the impact of PLimC on the mechanical properties of the matrix polymers is studied. The interplay of incompatibility and zero-shear melt viscosity contrast determines the blend morphology, leading for all blends to a dispersed droplet morphology for PLimC. Blends with polymers of similar structure to PLimC (i.e., aliphatic/aromatic polyester) show the best performance with respect to mechanical properties, whereas blends with polystyrene or poly(methyl methacrylate) are too brittle and polyamide 12 blends show very low elongations at break. In blends with Ecoflex (poly(butylene adipate-co-terephthalate)) and Arnitel EM400 (copoly(ether ester)) with poly(butylene terephthalate) hard and polytetrahydrofuran soft segments) a threefold increase in E-modulus can be achieved, while keeping the elongation at break at reasonable high values of ≈200%, making these blends highly interesting for applications.     

Corrosion behaviors of carbon steel induced by life activities of Phaeodactylum tricornutum in a marine environment

Microbiologically influenced corrosion induced by bacteria has been studied for many years. Corrosion is known to be sensitive to the presence of microalgae, such as Phaeodactylum tricornutum. However, the life activity of P. tricornutum that influences the general and localized corrosion of carbon steel is not fully understood. The current study uses a combination of immersion tests and electrochemical experiments with a detailed surface characterization to reveal the naturally formed corrosion products with/without the presence of P. tricornutum. The results show that samples suffer from pitting corrosion and the averaged pit depths are approximately 15 μm under a light–dark cycle condition or a 24-h constant light condition. Meanwhile, the corrosion products are mainly comprised of γ-FeOOH and Fe₃O₄ in a constant light condition. However, γ-FeOOH, Fe₃O₄, and FeCO₃ are found in a light–dark cycle. This study proposes the fundamental mechanisms of the effect of P. tricornutum life activities on the corrosion performance of Q235 carbon steel, to fulfill the knowledge gaps of the presence of microalgae inducing the general and pitting corrosion of carbon steel.     

Effect of in-flight particle behavior on the morphology of flame sprayed Er2O3 splats

The morphology and microstructure of splats impact the comprehensive capability of a new coating methodology called chelate flame spraying (CFS). This study addresses the quantitative characterization of the spread morphologies of flame sprayed Er₂O₃ splats directly deposited under different spray conditions on aluminum alloy substrates with a mirror finish. The influence of the in-flight particle temperature and velocity, carrier gas type, and carrier gas ratio on the solidification mechanism of molten droplets was investigated. Image analysis methods were employed to identify single splats from the morphology observed with field-emission scanning electron microscopy (FE-SEM). In addition, Er₂O₃ films were synthesized on an Al–Mg alloy (A5052) substrate using N₂ or O₂ as the carrier gas. When O₂ was used as the carrier gas, 109-μm-thick films were deposited on the A5052 substrate. The cross-sectional porosity of the films was 3.8%. In contrast, films with 101-μm thickness were synthesized on the A5052 substrate when N₂ was used as the carrier gas. The cross-sectional porosity of these films was 13.8%. The results showed that the carrier gas type (N₂) and carrier gas ratio had a significant effect on the flattening behavior of the molten droplets. A spraying method combined with multidimensional modes is proposed to control the morphology of the splats.     

Revealing cracking and breakage behaviours of gibbsite particles

Mitigating gibbsite particle cracking and breakage during industrial alumina production can increase the quality of smelter grade alumina product by reducing the ultrafine particle content. Therefore, it is essential to investigate the particle cracking during static calcination and the breakage of calcined gibbsite particles under external force. In this work, we investigated the impact of the calcination ramping rate and the crystallite size on gibbsite particle cracking during static calcination. A slow ramping rate and a large pristine crystallite size tend to increase particle cracking. Apart from the study of particle cracking behaviour, we also investigated the breakage of calcined gibbsite particle under external force. Cracks on the particle surface can initiate breakage within the crystallite and along the grain boundary under external force. The breakage within crystallite occurs as the cleavage of the crystallite, while the breakage along the grain boundary leads to the shedding of a whole crystallite. We further explored the factors influencing the strength of calcined gibbsite particles. With increasing calcination temperature, the strength of particle increases when gibbsite converts to boehmite, and then decreases when boehmite converts into amorphous alumina. Particles containing smaller crystallites and calcined with fast ramping rates exhibit higher resistance to breakage.     

不同细颗粒含量甲烷水合物沉积物三轴剪切试验研究

海域试开采区域含水合物沉积物的粒度分析结果表明水合物沉积物骨架由粗、细颗粒混合构成,通过开展多组低温、高压三轴排水剪切试验研究细颗粒含量和密度对含甲烷水合物沉积物和无水合物沉积物的强度和变形特性的影响。试验结果表明,含水合物沉积物抗剪强度及剪胀性都随细粒含量提高而显著增强。这是由于细颗粒含量增加改变了颗粒间水合物的样貌和分布特征,形成了由水合物包裹着粗颗粒-细颗粒的团簇状集合体。然而,细颗粒含量对无水合物沉积物的强度和变形特性的影响却表现出相反趋势。另外,含水合物沉积物的剪胀关系可以使用修正剑桥模型中的剪胀关系式进行描述。结果表明,剪胀关系的拟合曲线依赖于水合物饱和度的大小。通过对比研究发现,天然水合物和实验室合成水合物试样在较高饱和度时的峰值摩擦角大小及其伴随水合物饱和度的增长趋势存在差异,这种差异主要来源于水合物在沉积物骨架颗粒孔隙中不同的赋存模式及分布特征。     

水力空化改质对重质原油沥青质及性质的影响

利用水力空化过程产生局部的高温、高压、高射流以及强大的剪切力等极端化学物理条件改质处理沙特重质原油，试验结果表明：沙特重质原油经过水力空化改质后粘度由13.61降低至7.22mm2/s，残碳由7.16%降低至6.48%，实沸点蒸馏后减压渣油降低1个百分点。进一步采用APPI FT-IR MS、XRD、FT-IR、SEM和粒度分布等技术研究了水力空化改质对沙重原油分子组成，沥青质团聚体微晶结构、沥青质胶束粒径分布、沥青质官能团、沥青质形貌等方面的影响，从分子角度阐述空化改质重油的机理。研究结果表明：水力空化改质后沙重原油分子量分布、芳烃类化合物缔合作用变小；沥青质对低DBE化合物吸附性能降低；沥青质团聚体微晶结构更加松散；沥青质胶束粒度分布降低；沥青质分子相互团聚作用力减弱。进一步考察了水力空化改质前后减压渣油延迟焦化性能，改质处理后焦炭产率降低1.85个百分点，液体收率和气体产率分别增加1.52和0.33个百分点，水力空化改质对沥青质性质、结构特点的改善能够有效的提高其加工性能。     

Gluten–starch interface characteristics and wheat dough rheology—Insights from hybrid artificial systems

Referring to the total surface existing in wheat dough, gluten–starch interfaces are a major component. However, their impact on dough rheology is largely unclear. Common viewpoints, based on starch surface modifications or reconstitution experiments, failed to show unambiguous relations of interface characteristics and dough rheology. Observing hybrid artificial dough systems with defined particle surface functionalization gives a new perspective. Since surface functionalization standardizes particle–polymer interfaces, the impact on rheology becomes clearly transferable and thus, contributes to a better understanding of gluten–starch interfaces. Based on this perspective, the effect of particle/starch surface functionality is discussed in relation to the rheological properties of natural wheat dough and modified gluten–starch systems. A competitive relation of starch and gluten for intermolecular interactions with the network-forming polymer becomes apparent during network development by adsorption phenomena. This gluten–starch adhesiveness delays the beginning of non-linearity under large deformations, thus contributing to a high deformability of dough. Consequently, starch surface functionality affects the mechanical properties, starting from network formation and ending with the thermal fixation of structure.     

Morphological study of thin films: Simulation and experimental insights using horizontal visibility graph

We studied the morphological nature of various thin films such as silicon carbide (SiC), diamond (C), germanium (Ge), and gallium nitride (GaN) on silicon substrate Si(100) using the pulsed laser deposition (PLD) method and Monte Carlo simulation. We, for the first time, systematically employed the visibility algorithm graph to meticulously study the morphological features of various PLD grown thin films. These thin-film morphologies are investigated using random distribution, Gaussian distribution, patterned heights, etc. The nature of the interfacial height of individual surfaces is examined by a horizontal visibility graph (HVG). It demonstrates that the continuous interfacial height of the silicon carbide, diamond, germanium, and gallium nitride films are attributed to random distribution and Gaussian distribution in thin films. However, discrete peaks are obtained in the brush and step-like morphology of germanium thin films. Further, we have experimentally verified the morphological nature of simulated silicon carbide, diamond, germanium, and gallium nitride thin films were grown on Si(100) substrate by pulsed laser deposition (PLD) at elevated temperature. Various characterization techniques have been used to study the morphological, and electrical properties which confirmed the different nature of the deposited films on the Silicon substrate. Decent hysteresis behavior has been confirmed by current-voltage (IV) measurement in all the four deposited films. The highest current has been measured for GaN at ～60 nA and the lowest current in SiC at ～30 nA level which is quite low comparing with the expected signal level (μA). The HVG technique is suitable to understand surface features of thin films which are substantially advantageous for the energy devices, detectors, optoelectronic devices operating at high temperatures.     

Microstructure and mechanical properties of 3D-printed nano-silica reinforced alumina cores

Ceramic cores are an important component in the preparation of hollow turbine blades for aero-engines. Compared with traditional hot injection technology, 3D printing technology overcomes the disadvantages of a long production cycle and the difficulty in producing highly complex ceramic cores. The ceramic cores of hollow turbine blades require a high bending strength at high temperatures, and nano-mineralizers greatly improve their strength. In this study, nano-silica-reinforced alumina-based ceramic cores were prepared, and the effects of nanopowder content on the microstructure and properties of the ceramic cores were investigated. Alumina-based ceramic cores contained with nano-silica were prepared using the vat photopolymerization 3D printing technique and sintered at 1500 °C. The results showed that the linear shrinkage of ceramic cores first increased and then decreased as the nano-silica powder content increased, and the bending strength showed the same trend. The fracture mode changed from intergranular to transgranular. The open porosity and bulk density fluctuated slightly. The weight loss rate was approximately 20%. When the nano-silica content was 3%, the bending strength reached a maximum of 46.2 MPa and 26.1 MPa at 25 °C and 1500 °C, respectively. The precipitation of the glass phase, change in the fracture mode of the material, pinning crack of nanoparticles, and reduction of fracture energy due to the interlocking of cracks, were the main reasons for material strengthening. The successful preparation of 3D printed nano-silica reinforced alumina-based ceramic cores is expected to promote the preparation of high-performance ceramic cores with complex structures of hollow turbine blades.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.