Hybrid Nanoscopy of Hybrid Nanomaterials

The combination of complementary techniques to characterize materials at the nanoscale is crucial to gain a more complete picture of their structure, a key step to design and fabricate new materials with improved properties and diverse functions. Here it is shown that correlative atomic force microscopy (AFM) and localization‐based super‐resolution microscopy is a useful tool that provides insight into the structure and emissive properties of fluorescent β‐lactoglobulin (βLG) amyloid‐like fibrils. These hybrid materials are made by functionalization of βLG with organic fluorophores and quantum dots, the latter being relevant for the production of 1D inorganic nanostructures templated by self‐assembling peptides. Simultaneous functionalization of βLG fibers by QD655 and QD525 allows for correlative AFM and two‐color super‐resolution fluorescence imaging of these hybrid materials. These experiments allow the combination of information about the topography and number of filaments that compose a fibril, as well as the emissive properties and nanoscale spatial distribution of the attached fluorophores. This study represents an important step forward in the characterization of multifunctionalized hybrid materials, a key challenge in nanoscience.     

Use of 3D printing for biofuel production: efficient catalyst for sustainable biodiesel production from wastes

This work deals with the sustainable biodiesel production from low-cost renewable feedstock (waste and non-edible oils) using a heterogeneous catalyst constituted by potassium loaded on an amorphous aluminum silicate naturally occurring as volcanic material (pumice). The main challenge to biodiesel production from low-quality oils (used oils and greases) is the high percentage of free fatty acids (FFAs) and water in the feedstock that causes undesirable side reactions. The catalytic materials studied were tested in the transesterification reaction when using low-quality oils containing a high proportion of free fatty acids (FFAs) and water. Results indicated that the amount of acid and basic sites on the catalytic surface increases upon increasing potassium loading in the catalyst, displaying better performance for biodiesel production. Indeed, the modification of the aluminum silicate substrate upon potassium incorporation results in a catalytic material containing both acidic and basic sites, which are responsible for both triglycerides transesterification and FFA esterification reactions. The studied catalyst not only showed good performance in the biodiesel production reaction but also good tolerance to FFA and water contained in the feedstock for biodiesel production. The catalytic material was microstructured by 3D printing in order to design a catalytic stirring system with high mechanical strength, efficient and reusable. The use of 3D printing in biofuel production is a novelty that brings good solutions for catalyst production.     

How can Cleaner Production practices contribute to meet ISO 14001 requirements? Critical analysis from a survey with industrial companies

The companies’ needs to adopt changes in their way of production to maximize the environmental performance required by their stakeholders, and at the same time, to maximize their economic and market performance, have made them seek for environmental strategies and certifications. In this sense, the Cleaner Production and the Environmental Management System based on ISO 14001 have been, respectively, presented, since the main objective of this research is to identify and analyze Cleaner Production contributions to comply with ISO 14001 requirements. For such, a survey research has been carried out in Brazilian industrial companies certified by ISO 14001. We have identified the main performance factors by leading practices and variables of Cleaner Production that contribute to the compliance with the standard requirements by companies. Thus, it has been noted that Cleaner Production is an important strategy for the preparation of companies for certification as well as for improving their environmental performance.     

Probabilistic crack trajectory analysis by a dimension reduction method

This paper proposes a novel analysis method of stochastic crack trajectory based on a dimension reduction approach. The developed method allows efficiently estimating the statistical moments, probability density function and cumulative distribution function of the crack trajectory for cracked elastic structures considering the randomness of the loads, material properties and crack geometries. First, the traditional dimension reduction method is extended to calculate the first four moments of the crack trajectory, in which the responses are eigenvectors rather than scalars. Then the probability density function and cumulative distribution function of the crack trajectory can be obtained using the maximum entropy principle constrained by the calculated moments. Finally, the simulation of the crack propagation paths is realized by using the scaled boundary finite element method. The proposed method is well validated by four numerical examples performed on varied cracked structures. It is demonstrated that this method outperforms the Monte Carlo simulation in terms of computational efficiency, and in the meanwhile, it has an acceptable computational accuracy.     

An efficient uncertainty propagation method for parameterized probability boxes

In the response analysis of uncertain structural models with limited information, parameterized p-boxes are used to quantify the uncertain variables. In this study, a new technique is developed to compute the probability bounds of the structural response. Monotonicity analysis is performed on probability transformations of the random variables, revealing the relations between the interval distribution parameters and probability bounds of the structural response. Based on the monotonicity analysis, an algorithm for parameterized p-boxes is developed for computing the structural response. Three numerical examples are investigated to demonstrate the effectiveness of the proposed method.     

Cross-property connections for copper–graphite composites

Copper–graphite composite materials in the range of 0–10 vol% of carbon phase were prepared from the mixture of copper and graphite powders by hot isostatic pressing. The microstructure, mechanical (tensile strength, elongation to fracture) and physical (electrical and thermal conductivity) properties of composite samples were investigated, and the cross-property connections were calculated. It was shown that electrical and thermal conductivity cross-property (Lorenz number) is almost constant and increases only slightly (no more than 10 % increase was observed). This implies that in the investigated composition range the Lorenz number of a copper–graphite composite system behaves according to Franz–Wiedemann law for pure metals at constant temperature. On the contrary, the conductivity to tensile strength cross-property connections showed significant linear increase (over 200 % in the investigated composition range) for both electrical conductivity and thermal conductivity of composite materials. The cross-property connections of conductivity to the elongation to fracture exhibit a nonlinear dependence on the volume fraction of graphite.