Processing Parameters for Selective Laser Sintering or Melting of Oxide Ceramics

In this chapter, we present a detailed introduction to the factors which influence laser powder bed fusion (LPBF) on oxide ceramics. These factors can be in general divided in three main categories: laser-related factors (wavelength, power, scanning speed, hatch distance, scan pattern, beam diameter, etc.), powder- and material-related factors (flowability, size distribution, shape, powder deposition, thickness of deposited layers, etc.), and other factors (pre- or post-processing, inert gas atmosphere, etc.). The process parameters directly affect the amount of energy delivered to the surface of the thin layer and the energy density absorbed by the powders; therefore, decide the physical and mechanical properties of the built parts, such as relative density, porosity, surface roughness, dimensional accuracy, strength, etc. The parameter-property relation is hence reviewed for the most studied oxide ceramic materials, including families from alumina, silica, and some ceramic mixtures. Among those parameters, reducing temperature gradient which decreases the thermal stresses is one of the key factors to improve the ceramic quality. Although realizing crack-free ceramics combined with a smooth surface is still a major challenge, through optimizing the parameters, it is possible for LPBF processed ceramic parts to achieve properties close to those of conventionally produced ceramics

The impact of thermoelectric leg geometries on thermal resistance and power output

Thermoelectric devices enable direct, solid-state conversion of heat to electricity and vice versa. Rather than designing the shape of thermoelectric units or legs to maximize this energy conversion, the cuboid shape of these legs has instead remained unchanged in large part because of limitations in the standard manufacturing process. However, the advent of additive manufacturing (a technique in which freeform geometries are built up layer-by-layer) offers the potential to create unique thermoelectric leg geometries designed to optimize device performance. This work explores this new realm of novel leg geometry by simulating the thermal and electrical performance of various leg geometries such as prismatic, hollow, and layered structures. The simulations are performed for two materials, a standard bismuth telluride material found in current commercial modules and a higher manganese silicide material proposed for low cost energy conversion in high-temperature applications. The results include the temperature gradient and electrical potential developed across individual thermoelectric legs as well as thermoelectric modules with 16 legs. Even simple hollow and layered leg geometries result in larger temperature gradients and higher output powers than the traditional cuboid structure. The clear dependence of thermal resistance and power output on leg geometry provides compelling motivation to explore additive manufacturing of thermoelectric devices

Predicting Thermoelectric Power Factor of Bismuth Telluride During Laser Powder Bed Fusion Additive Manufacturing

An additive manufacturing (AM) process, like laser powder bed fusion, allows for the fabrication of objects by spreading and melting powder in layers until a freeform part shape is created. In order to improve the properties of the material involved in the AM process, it is important to predict the material characterization property as a function of the processing conditions. In thermoelectric materials, the power factor is a measure of how efficiently the material can convert heat to electricity. While earlier works have predicted the material characterization properties of different thermoelectric materials using various techniques, implementation of machine learning models to predict the power factor of bismuth telluride (Bi2Te3) during the AM process has not been explored. This is important as Bi2Te3 is a standard material for low temperature applications. Thus, we used data about manufacturing processing parameters involved and in-situ sensor monitoring data collected during AM of Bi2Te3, to train different machine learning models in order to predict its thermoelectric power factor. We implemented supervised machine learning techniques using 80% training and 20% test data and further used the permutation feature importance method to identify important processing parameters and in-situ sensor features which were best at predicting power factor of the material. Ensemble-based methods like random forest, AdaBoost classifier, and bagging classifier performed the best in predicting power factor with the highest accuracy of 90% achieved by the bagging classifier model. Additionally, we found the top 15 processing parameters and in-situ sensor features to characterize the material manufacturing property like power factor. These features could further be optimized to maximize power factor of the thermoelectric material and improve the quality of the products built using this material.Comment: 8 pages, 2 figures, 2 tables, accepted at Data Science for Smart Manufacturing and Healthcare workshop (DS2-MH) at SIAM International Conference on Data Mining (SDM23) conferenc

Process-microstructure relationship of laser processed thermoelectric material Bi2Te3

Additive manufacturing allows fabrication of custom-shaped thermoelectric materials while minimizing waste, reducing processing steps, and maximizing integration compared to conventional methods. Establishing the process-structure-property relationship of laser additive manufactured thermoelectric materials facilitates enhanced process control and thermoelectric performance. This research focuses on laser processing of bismuth telluride (Bi2Te3), a well-established thermoelectric material for low temperature applications. Single melt tracks under various parameters (laser power, scan speed and number of scans) were processed on Bi2Te3 powder compacts. A detailed analysis of the transition in the melting mode, grain growth, balling formation, and elemental composition is provided. Rapid melting and solidification of Bi2Te3 resulted in fine-grained microstructure with preferential grain growth along the direction of the temperature gradient. Experimental results were corroborated with simulations for melt pool dimensions as well as grain morphology transitions resulting from the relationship between temperature gradient and solidification rate. Samples processed at 25 W, 350 mm/s with 5 scans resulted in minimized balling and porosity, along with columnar grains having a high density of dislocations

Additive Manufacturing of Bulk Thermoelectric Architectures: A Review

Additive manufacturing offers several opportunities for thermoelectric energy harvesting systems. This new manufacturing approach enables customized leg geometries, minimized thermal boundary resistances, less retooling, reduced thermoelectric material waste, and strong potential to manipulate microstructure for higher values of figure of merit. Although additive manufacturing has been used to fabricate thin thermoelectric films, there has been comparatively limited demonstrations of additive manufacturing for bulk thermoelectric structures. This review provides insights about the current progress of bulk thermoelectric material and device additive manufacturing. Each additive manufacturing technique used to produce bulk thermoelectric structures is discussed in detail along with future directions and challenges

Laser Powder Bed Fusion of Bismuth Telluride: Process-Structure-Property Relationships

Thermoelectric generators possess a vast potential for waste heat recovery. Yet, the traditional fabrication methods of thermoelectric structures suffer from material loss and are limited to planar geometries. As a solution, laser additive manufacturing of thermoelectric materials has attracted considerable attention. In this research, the process-structure-property relationship of laser processed bulk bismuth telluride parts has been explored. Under constant laser power and scan speed, the effects of variation in scan pattern, number of scans, hatch spacing and layer height on the microstructural and thermoelectric properties were investigated. It was concluded that the laser powder bed fusion enables formation of intensive interfaces with preferential grain growth and certain scan patterns result in enhancement in relative density and thermoelectric properties.Mechanical Engineerin

Cost Scaling of a Real-World Exhaust Waste Heat Recovery Thermoelectric Generator: A Deeper Dive

Cost is equally important to power density or efficiency for the adoption of waste heat recovery thermoelectric generators (TEG) in many transportation and industrial energy recovery applications. In many cases the system design that minimizes cost (e.g., the $/W value) can be very different than the design that maximizes the system's efficiency or power density, and it is important to understand the relationship between those designs to optimize TEG performance-cost compromises. Expanding on recent cost analysis work and using more detailed system modeling, an enhanced cost scaling analysis of a waste heat recovery thermoelectric generator with more detailed, coupled treatment of the heat exchangers has been performed. In this analysis, the effect of the heat lost to the environment and updated relationships between the hot-side and cold-side conductances that maximize power output are considered. This coupled thermal and thermoelectric treatment of the exhaust waste heat recovery thermoelectric generator yields modified cost scaling and design optimization equations, which are now strongly dependent on the heat leakage fraction, exhaust mass flow rate, and heat exchanger effectiveness. This work shows that heat exchanger costs most often dominate the overall TE system costs, that it is extremely difficult to escape this regime, and in order to achieve TE system costs of$1/W it is necessary to achieve heat exchanger costs of $1/(W/K). Minimum TE system costs per watt generally coincide with maximum power points, but Preferred TE Design Regimes are identified where there is little cost penalty for moving into regions of higher efficiency and slightly lower power outputs. These regimes are closely tied to previously-identified low cost design regimes. This work shows that the optimum fill factor Fopt minimizing system costs decreases as heat losses increase, and increases as exhaust mass flow rate and heat exchanger effectiveness increase. These findings have profound implications on the design and operation of various thermoelectric (TE) waste heat 3 recovery systems. This work highlights the importance of heat exchanger costs on the overall TEG system costs, quantifies the possible TEG performance-cost domain space based on heat exchanger effects, and provides a focus for future system research and development efforts

Sterically Stabilized Multilayer Graphene Nanoshells for Inkjet Printed Resistors

In the field of printed electronics, there is a pressing need for printable resistors, particularly ones where the resistance can be varied without changing the size of the resistor. This work presents ink synthesis and printing results for variable resistance, inkjet-printed patterns of a novel and sustainable carbon nanomaterial—multilayer graphene nanoshells. Dispersed multilayer graphene nanospheres are sterically stabilized by a surfactant (Triton X100), and no post-process is required to achieve the resistive functionality. A surface tension-based adsorption analysis technique is used to determine the optimal surfactant dosage, and a geometric model explains the conformation of adsorbed surfactant molecules. The energetic interparticle potentials between approaching particles are modeled to assess and compare the stability of sterically and electrostatically stabilized multilayer graphene nanoshells. The multilayer graphene nanoshell inks presented here show a promising new pathway toward sustainable and practical printed resistors that achieve variable resistances within a constant areal footprint without post-processing