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Abstract Battery production cost models are critical for evaluating the cost competitiveness of different cell geometries, chemistries, and production processes. To address this need, we present a detailed bottom-up approach for calculating the full cost, marginal cost, and levelized cost of various battery production methods. Our approach ensures comparability across research fields and industries, reflecting capital and imputed interest costs. We showcase the model with case studies of a prismatic PHEV2 hardcase cell and a cylindrical 4680 cell in four different chemistries. Our publicly available browser-based modular tool incorporates up-to-date parameters derived from literature and expert interviews. This work enables researchers to quickly assess the production cost implications of new battery production processes and technologies, ultimately advancing the goal of reducing the cost of electrified mobility.

Filamentous microorganisms exhibit a complex macro-morphology constituted of branched and cross-linked hyphae. Fully resolved mechanical models of such mycelial compounds rely heavily on accurate input data for mechanical properties of individual hyphae. Due to their irregular shape and high adaptability to environmental factors, the measurement of these intrinsic properties remains challenging. To overcome previous shortcomings of microfluidic bending tests, a novel system for the precise measurement of the individual bending stiffness of fungal hyphae is presented in this study. Utilizing two-photon polymerization, microfluidic molds were fabricated with a multi-material approach, enabling the creation of 3D cell traps for spore immobilization. Unlike previous works applying the methodology of microfluidic bending tests, the hyphae were deflected in the vertical center of the microfluidic channel, eliminating the adverse influence of nearby walls on measurements. This lead to a significant increase in measurement yield compared to the conventional design. The accuracy and reproducibility of bending tests was ensured through validation of the measurement flow using micro-particle image velocimetry. Our results revealed that the bending stiffness of hyphae of Aspergillus niger is approximately three to four times higher than that reported for Candida albicans hyphae. At the same time, the derived longitudinal Young’s Modulus of the hyphal cell wall yields a comparable value for both organisms. The methodology established in this study provides a powerful tool for studying the effects of cultivation conditions on the intrinsic mechanical properties of single hyphae. Applying the results to resolved numerical models of mycelial compounds promises to shed light on their response to hydrodynamic stresses in biotechnological cultivation, which influences their expressed macro-morphology and in turn, product yields.

Abstract Innovative soft robotic grippers, such as granular grippers, enable the automated handling of a wide spectrum of different geometries, increasing the flexibility and robustness of industrial production systems. Granular grippers vary in their design as well as in their configuration, which affects the specific characteristics and capabilities regarding grippable objects. Relevant aspects are the selection of granulates and membranes, as they affect the deformability. This influences the achievable gripping forces, which vary with the gripped objects geometry. On the basis of experimental studies, the modeling of interpolations as well as through experimental validations, the present research investigates the influences of different configurations on the achievable gripping forces for a specific concept of an innovative vacuum-based granular gripper. Specifically, the focus lies on design as well as configuration parameters, which could influence the achievable gripping force. Influencing parameters are determined based on a literature review of similar gripping concepts. Various adjustment possibilities are identified, such as materials of granulates or membranes. The possible configuration options are experimentally analyzed with a one-factor-at-a-time approach. The possibility of modelling the effects of their interrelations on the achievable gripping force is examined with approaches for linear models and compared to interpolations based on Machine Learning. Especially the granulate filling level and the membrane configuration exhibit the largest influences, which were best predicted with the approach based on artificial neural networks. A selection of an optimized gripper configuration for a specified object set as well as possible further developments such as a continuous expandability of the approaches and integrations with simulations are discussed. As a result of these analyses, this research provides methodologies for an optimized selection of a gripper configuration for an improved object-specific achievable gripping force and allows for more efficient handling processes with the examined type of vacuum-based granular gripper.

Since the early 2010s, after decades of premature excitement and disillusionment, the field of artificial intelligence (AI) is experiencing exponential growth, with massive real-world applications and high adoption rates both in daily life and in industry. In particle technology, there are already many examples of successful AI applications, for predictive modeling, process control and optimization, fault recognition, even for mechanistic modeling. However, in comparison to its still untapped potential and to other industries, further expansion in adoption rates and, consequently, gains in productivity, efficiency, and cost reduction are still possible. This review article is intended to introduce AI and its application scenarios and provide an overview and examples of current use cases of different aspects and unit operations in particle technology, such as grinding, extrusion, synthesis, characterization, or scale-up. In addition, hybrid modeling approaches are presented with examples of the intelligent combination of different methods to reduce data requirements and achieve beneficial synergies. Finally, an outlook for future opportunities is given, depicting promising approaches, currently being in the conception or implementation phase.

Future industrial applications of microparticle fractionation with deterministic lateral displacement (DLD) devices are hindered by exceedingly low throughput rates. To enable the necessary high-volume flows, high flow velocities as well as high aspect ratios in DLD devices have to be investigated. However, no experimental studies have yet been conducted on the fractionation of bi-disperse suspensions containing particles below 10 µm with DLD at a Reynolds number (Re) above 60. Furthermore, devices with an aspect ratio of more than 4:1, which require advanced microfabrication, are not known in the DLD literature. Therefore, we developed a suitable process with deep reactive ion etching of silicon and anodic bonding of a glass lid to create pressure-resistant arrays. With a depth of 120 µm and a gap of 23 µm between posts, a high aspect ratio of 6:1 was realized, and devices were investigated using simulations and fractionation experiments. With the two-segmented array of 3° and 7° row shifts, critical diameters of 8 µm and 12 µm were calculated for low Re conditions, but it was already known that vortices behind the posts can shift these values to lower critical diameters. Suspensions with polystyrene particles in different combinations were injected with an overall flow rate of up to 15 mL/min, corresponding to Re values of up to 90. Suspensions containing particle combinations of 2 µm with 10 µm as well as 5 µm with 10 µm were successfully fractionated, even at the highest flow rate. Under these conditions, a slight widening of the displacement position was observed, but there was no further reduction in the critical size as it was for Re = 60. With an unprecedented fractionation throughput of nearly 1 L per hour, entirely new applications are being developed for chemical, pharmaceutical, and recycling technologies.

Abstract Due to their high ionic conductivity, sulfidic solid electrolytes are considered to have great potential as a key element of solid‐state batteries. Such batteries could offer safety, thermal stability, and high energy densities. A key requirement is the scalable production of separators and electrodes, taking into account the high demands the moisture‐sensitive material imposes on the surrounding atmosphere. Therefore, in this publication we will demonstrate the establishment of an extrusion process under argon atmosphere for the continuous production of separator and cathode suspensions. After systematically investigating the influence of the process parameters speed, temperature and mass flow on the adhesive strength, ionic conductivity and capacity, the obtained knowledge is used for the fabrication of improved layers. The Li3PS4 based separators show a comparatively high ionic conductivity of 0.036 mS cm−1 (conductivity of pure solid electrolyte: 0.05 mS cm−1), the cells reach specific capacities of up to 156 mAh g−1 in the 1st cycle.

Understanding of generation, extent and location of thermomechanical stress in small-scale (< 3 g) ram and twin-screw melt-extrusion is crucial for mechanistic correlations to the stability of protein particles (lysozyme and BSA) in PEG-matrices. The aim of the study was to apply and correlate experimental and numerical approaches (1D and 3D) for the evaluation of extrusion process design on protein stability. The simulation of thermomechanical stress during extrusion raised the expectation of protein degradation and protein particle grinding during extrusion, especially when TSE was used. This was confirmed by experimental data on protein stability. Ram extrusion had the lowest impact on protein unfolding temperatures, whereas TSE showed significantly reduced unfolding temperatures, especially in combination with kneading elements containing screws. In TSE, the mechanical stress in the screws always exceeded the shear stress in the die, while mechanical stress within ram extrusion was generated in the die, only. As both extruder designs revealed homogeneously distributed protein particles over the cross section of the extrudates for all protein-loads (20–60%), the dispersive power of TSE revealed not to be decisive. Consequently, the ram extruder would be favored for the production of stable protein-loaded extrudates in small scale.

Abstract To achieve the commercialization of solid‐state‐batteries (SSBs), solid electrolyte properties need to be further improved. The hybrid solid electrolyte (HSE) approach is expected to combine the favorable properties of different solid electrolyte classes and is therefore systematically investigated. Mixing low amounts of thiophosphate or oxide filler particles (FP) into a polyethylene oxide (PEO) polyethylene glycol (PEG) and lithium salt bis(trifluoromethane)sulfonimide (LiTFSI) matrix cannot improve the electrochemical properties. Silanization of the thiophosphate FPs significantly increases the ionic conductivity to 0.1 mS cm−1 at room temperature compared to 0.017 mS cm−1 for a pure PEO solid electrolyte. Moreover, a correlation between the intrinsic conductivity of the FPs and the resulting conductivity of the HSE is observed. Also, the functionalization is successfully transferred to oxide FPs. In addition to an equally significant increase in ionic conductivity, a strong influence of the crystallite size of the FPs on the resulting ionic conductivity of the HSE was found. The discovered effect of FP surface structure on overall HSE conductivity indicates a participation of the FP surface in ion transport and emphasizes the need for tailored filler design in HSE applications.