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Several decades after the invention of the rechargeable Li‐ion battery, countless innovations from both the research and industry communities have led to placing the secondary battery at the heart of the electrification revolution in recent years. Mathematical and numerical models have been trusted companions in advancing the technology to help guide design improvements or to gain insight when physical measurements are impossible to perform. Starting with the breakthrough porous electrode theory (PET) model proposed by Newman and co‐workers in 1975 (Newman and Tiedemann, AIChE Journal, 1975, 21, 25–41), many authors have improved the formulation from a variety of perspectives. The novel aspects of the model we propose in this paper expand on this long stream of PET formulations and aim to address modeling needs that, to the authors' knowledge, have not been yet considered. The proposed formulation is characterized by the following concurrent features: (1) a full 3D description of the macroscale behavior and 1D microscale in spherical coordinates (Pseudo 4D formulation [P4D]) accounting for geometric details of the cell architecture such as imperfect spiral jellyrolls in cylindrical cells; (2) multiple concurrent particle chemistries to model the microscale lithiation/delithiation behavior at every macroscale element integration point, leading to a multiscale (FE2$$ {\mathrm{FE}}^2 $$) approach; (3) a fully coupled thermal‐electrochemical‐mechanical stress interaction due to lithiation/delithiation induced swelling and external confinement; (4) spatially‐dependent porosity evolutions due to swelling of the particles in the porous electrodes; (5) electrolyte flow in the porous regions and overfill spaces via Darcy‐based flow including partial saturation of the active regions; (6) detailed descriptions of individual battery components such as the electrodes, separator, and current collectors with the possibility of "connecting" the different components through contact definitions; (7) fully linearized macro‐microscale coupling behavior allowing for large time increments in an implicit time integration scheme for a scalable and computationally effective numerical solution. A number of numerical examples including validation against experimental data are performed to demonstrate the predictive power of the proposed model and its efficiency for industrial applications. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced polymer composites have been used in Big Area Additive Manufacturing (BAAM) to decrease the distortion during the printing process and increase functional stiffness. These materials are also important for additively manufactured autoclave tooling which expands when exposed to the high temperatures of the operational cycle, causing the dimensions of the mold to differ from the targeted design. Since the reinforcing fibers generally align during the extrusion process, the thermal expansion of the composite along the deposition direction is restrained by fibers, whereas the thermal expansion perpendicular to the bead is largely unconstrained. This leads to an anisotropic expansion of the material that is dependent upon the local deposition path, which may be tortuous and complex. To obtain an accurate final part geometry during the autoclave process, a computational prediction of the thermal expansion of a tool is required to account for the complex extrusion deposition directions. A multi-step approach is presented that accounts for (1) anisotropic thermal expansion of the extruded bead, (2) the complex deposition directions, and (3) internal geometry determined by slicing software. The thermal expansion coefficient in the deposition direction and perpendicular to the deposition direction were measured at multiple locations in the test specimen. A revised model geometry was generated to achieve the target dimensions when accounting for thermal expansion. [ABSTRACT FROM AUTHOR]

The present study is reporting the influence of the chelating/combustion agents on the magnetic properties of Zn ferrite. Six chelating/combustion agents, citric acid, egg white, tartaric acid, glycine, glucose and urea, were used to obtain monophase zinc nanoferrite via a sol-gel auto-combustion method. The samples were subjected to a comparative study of structural features and magnetic properties by means of infrared spectroscopy, X-ray diffractometry, scanning electron microscopy and vibrating sample magnetometry. Significant influence of fuel and combustion mode was observed in the magnetic behavior of as-obtained samples. Values of the structural parameters were discovered to vary as a function of fuel choice, and to obtain crystallite size between 38 and 62 nm, inversion degree between 0.239 and 0.807, lattice parameter between 8.4125 and 8.4432 Å. The optimization of sol-gel method synthesis of zinc ferrite nanoparticles by chosing the appropriate fuel is providing structural and magnetic properties of zinc nanoferrite as potential materials to be used in biomedical applications. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

This paper presents a simplified algorithm for the profiling of the rack gear tool to generate the active profile associated with rolling centrodes. The algorithm is based on the enveloping surfaces principles and reduces the computational problem by proposing an approximate representation of tool’s profile using only three or four points on the profile to be generated by using Bezier representations of the surfaces. The algorithm computes the coefficients of a Bezier substitution polynomial instead of computing hundreds of points on the active profile. This simplifies the solution methodology and requires only a limited number of points along the profile to be generated. The algorithm is computationally efficient and can also be used in the case when the active profile to be generated is physically measured at a few points. Examples include mill tools, splined shafts, and gears. [ABSTRACT FROM AUTHOR]