Utilizing Iron's Attractive Chemical and Magnetic Properties in Microrocket Design,Extended Motion,and Unique Performance

All‐in‐one material for microrocket propulsion featuring acid‐based bubble generation and magnetic guidance is presented. Electrochemically deposited iron serves as both a propellant, toward highly efficient self‐propulsion in acidic environments, and as a magnetic component enabling complete motion control. The new microrockets display longer lifetime and higher propulsion efficiency compared to previously reported active metal zinc‐based microrockets due to the chemical properties of iron and the unique structure of the microrockets. These iron‐based microrockets also demonstrate unique and attractive cargo towing and autonomous release capabilities. The latter is realized upon loss of the magnetic properties due to acid‐driven iron dissolution. More interestingly, these bubble‐propelled microrockets assemble via magnetic interactions into a variety of complex configurations and train structures, which enrich the behavior of micromachines. Modeling of the magnetic forces during the microrocket assembly and cargo capture confirms these unique experimentally observed assembly and cargo‐towing behaviors. These findings provide a new concept of blending propellant and magnetic components into one, toward simplifying the design and fabrication of artificial micro/nanomachines, realizing new functions and capabilities for a variety of future applications.     

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.     

Differential Electrochemical Conductance Imaging at the Nanoscale

Electron transfer in proteins is essential in crucial biological processes. Although the fundamental aspects of biological electron transfer are well characterized, currently there are no experimental tools to determine the atomic‐scale electronic pathways in redox proteins, and thus to fully understand their outstanding efficiency and environmental adaptability. This knowledge is also required to design and optimize biomolecular electronic devices. In order to measure the local conductance of an electrode surface immersed in an electrolyte, this study builds upon the current–potential spectroscopic capacity of electrochemical scanning tunneling microscopy, by adding an alternating current modulation technique. With this setup, spatially resolved, differential electrochemical conductance images under bipotentiostatic control are recorded. Differential electrochemical conductance imaging allows visualizing the reversible oxidation of an iron electrode in borate buffer and individual azurin proteins immobilized on atomically flat gold surfaces. In particular, this method reveals submolecular regions with high conductance within the protein. The direct observation of nanoscale conduction pathways in redox proteins and complexes enables important advances in biochemistry and bionanotechnology.     

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.     

Heavy metal removal from simulated wastewater using electrochemical technology: optimization of copper electrodeposition in a membraneless fluidized bed electrode

Heavy metal removal from industrial wastewaters has been intensively studied, since it is well known that they can cause severe problems to human health and aquatic life, even at very low concentrations. In this work, it was demonstrated that electrodeposition in fluidized bed electrode (FBE) can be efficiently employed to remove metal ions from solution, avoid contamination, and recover the metal. Copper electrodeposition from diluted solutions was efficiently performed using a membraneless FBE. The average current efficiency (ACE), average energy consumption (AEC), and space–time yield (AY) was optimized taking into account the operational and process variables. It was noted that for all response variables studied, the raise of supporting electrolyte concentration (C _s) contributed to improvements in the process. The operational conditions current (I) and bed expansion (E) determined the values of CE, Y, and EC under activated control, but the initial copper concentration (C ₀) determined how long the electrodeposition process will work under activated or mass transfer control, thus affecting the average values of CE, Y, and EC. Considering C ₀ of 500 mg L^?1, copper can be optimally recovered with ACE >60 %, AY >38 kg h^?1 m^?3, and AEC <4.0 kWh kg^?1 by applying the lowest I and the highest levels of E and C _s. It was concluded that the electrochemical technology using a membraneless FBE reactor is economically competitive and be applied for the treatment of wastewaters contaminated with copper or other metals.     

Inverse analysis procedure to determine flow stress and friction data for finite element modeling of machining

This paper describes an inverse procedure to determine the constitutive constants and the friction conditions in the machining processes using Finite Elements (FE) simulations. In general, the FE modeling of machining processes is an effective tool to analyze the materials machinability under different cutting conditions. However, the use of reliable rheological and friction models represents the basis of a correct numerical investigation. The presented inverse procedure was based on the numerical results obtained using a commercial FE code and was developed considering a specific optimization problem, in which the objective functions that have to be minimized is the experimental/numerical error. This problem was performed by a routine developed in a commercial optimization software. In order to verify the goodness and the robustness of the methodology, it was applied on a Super Duplex Stainless Steel (SDSS) and on an Austenitic Stainless Steel (AUSS) orthogonal machining processes. This work, then, was focused on the identification of the Johnson-Cook (JC) coefficients (A,B,C, n and m) and on the calibration of a Coulomb friction model, in the specific cases of the SAF2507 SDSS and of an AISI 316 Based AUSS Alloy (AISI 316 ASBA). The identification phases were performed considering forces and temperatures experimental data, collected in two specific experimental tasks in which different orthogonal cutting tests were carried out under different cutting parameters conditions.