Development of a Process for Thermal and Mechanical Modelling of Screw-Driven Pellets Extrusion

The overall goal of the thesis project is to develop a process for thermal and mechanical modelling of the screw-driven pellets extrusion process, and applying the model results to design extruder temperature and flow rate controllers. The proposed extruder is designed for metal 3D printing. The device demonstrates great potential in tackling some of the major issues faced by the metal additive manufacturing community. It eliminates the use of metal powder for workplace and workers safety. It is able to produce end-use parts with industrial grade mechanical and microstructural properties. It utilizes low cost metal-loaded polymer pellets as feedstock. However, the application is only possible when the extruder has an accurate and responsive control system. Design of the extruder controller depends on a thorough understanding of the extrusion process. While a variety of polymer extrusion models exist in literature, most of them approximate the feedstock as a Newtonian fluid and make simplified assumptions about the pressure and temperature profile of the feedstock. The accuracy of the results are not sufficient for 3D printer control. Even less literature exists studying the extrusion process of metal injection molding machines, as an accurate flow control is not necessary for injection molding processes. To fill the gap in literature, the objectives of the thesis involve developing a heat transfer and a flow rate model that realistically characterize the screw-based extrusion process, and applying the models to design a comprehensive extruder temperature and flow rate control system. The models are validated with the existing extruder prototype and PLA feedstock pellets. While the model details might be different for different materials and extruder geometries, the modelling process should be universally applicable to all kinds of feedstock, including metal-loaded polymer pellets. A heat transfer model is proposed for the extruder prototype using a finite volume method. The goal of the model is to simulate the extruder and the feedstock temperature distribution given the heating and cooling system input. The model divides the extruder and the feedstock into 36 different control volumes. Conservation of energy and multi-node heat transfer equations are used to simulate the heat transfer between each control volume. The model is able to predict the extruder and the feedstock temperatures within 5°C compared to the experiment data. The model can be used to optimize the heater and cooling water input to provide an ideal thermal processing condition for the feedstock. A steady state output mass flow rate model is developed based on a simplified polymer extrusion model from literature. It incorporates a shear rate dependent polymer viscosity model and a calibrated feedstock pressure profile to increase model accuracy. The feedstock temperature distribution simulated in the heat transfer model is used to calculate various temperature dependent material properties. The model yields a logarithmic-like relationship between output mass flow rate and screw rotation speed. It reduces the error in the original simplified model by more than 50%. A post flow model is developed upon the steady state flow rate model results. The process utilizes a polymer compressibility model and the calculated extruder operating pressures to predict the amount of leaked extrudate after the screw stops rotating. A controller is proposed to add screw retraction at the end of each extrusion to eliminate post flow. It reduces the amount of leaked extrudate by more than 90%, as shown in the experiment. Finally a dynamic output mass flow rate model is presented. A first-order approximation is used to model the dynamic response of output flow rate with respect to change of screw rotation speeds. Results from both the steady state flow rate model and experiments are used to determine the constants within the dynamic model. A proportional controller is proposed to dynamically control the output mass flow rate. Further experiments need to be performed to design and validate the controller. The thesis is successful in developing a process for modelling and controlling desktop screw extruder. The post flow model and the dynamic flow rate model provide valuable insights on how to accurately control the extruder output for 3D printing applications. In the future, the modelling process can be applied to feedstock materials, and serve as a general guidelines for future screw extruder design

Automated Few-shot Classification with Instruction-Finetuned Language Models

A particularly successful class of approaches for few-shot learning combines language models with prompts -- hand-crafted task descriptions that complement data samples. However, designing prompts by hand for each task commonly requires domain knowledge and substantial guesswork. We observe, in the context of classification tasks, that instruction finetuned language models exhibit remarkable prompt robustness, and we subsequently propose a simple method to eliminate the need for handcrafted prompts, named AuT-Few. This approach consists of (i) a prompt retrieval module that selects suitable task instructions from the instruction-tuning knowledge base, and (ii) the generation of two distinct, semantically meaningful, class descriptions and a selection mechanism via cross-validation. Over $12$ datasets, spanning $8$ classification tasks, we show that AuT-Few outperforms current state-of-the-art few-shot learning methods. Moreover, AuT-Few is the best ranking method across datasets on the RAFT few-shot benchmark. Notably, these results are achieved without task-specific handcrafted prompts on unseen tasks.Comment: EMNLP2023 Finding

Performance prediction and regression analysis of scroll expander based on response surface methodology

The Organic Rankine Cycle (ORC) plays a pivotal role in the domain of renewable energy, adeptly harnessing thermal energy from sources such as solar and geothermal to generate electrical power. Central to this system is the scroll expander, whose operational efficacy directly influences the ORC's overall efficiency. This study initiates with a detailed numerical analysis of the impact of various operational parameters on both the steady and transient output performance of the scroll expander. Following this, a sophisticated performance prediction model is developed employing the response surface methodology. The model boasts high coefficients of determination, R2,values of 0.9967 and 0.9916, respectively, underscoring its superior predictive accuracy. Further, this model delves into the complex interactions among operational parameters and their consequent effects on the expander's performance. Validation of this predictive model is achieved through rigorous testing on an experimental platform designed for the ORC low-temperature waste heat power generation system. The discrepancies between predicted and actual performance measurements fall within a commendable margin of 15 %, affirming the model's robustness in forecasting scroll expander performance. The culmination of this research furnishes a novel and efficacious optimization strategy, establishing a robust theoretical foundation and offering fresh insights for the enhancement and prediction of scroll expander performance. This not only underscores the innovation of the approach but also its practical applicability in advancing the efficiency of renewable energy systems

Nocardioides silvaticus Li & Shi & Zhang & Wang 2019, SP. NOV.

DESCRIPTION OF NOCARDIOIDES SILVATICUS SP. NOV. Nocardioides silvaticus sp. nov. (sil.va′ ti.cus. L. masc. adj. silvaticus belonging to a forest). Cells are Gram-stain-positive, strictly aerobic, rod-shaped, approximately 0.8–1.3 µm long and 0.3–0.4 µm wide, and non-motile. Colonies grown on R2A agar are creamcoloured, circular, smooth, raised and 1–2 mm in diameter after incubation for 3 days. The growth temperature and pH range on R2A agar are 20–42 Ǫ C (optimum, 37 Ǫ C) and pH 7–9 (optimum, pH 7). It can tolerate salt up to 5 % NaCl (optimum without addition of NaCl). Catalase is positive but oxidase is negative. Negative for H 2 S production, indole production, methyl red production and Voges–Proskauer test. Hydrolyses casein and DNA, but not gelatin, starch, cellulose, Tween 20, Tween 40, Tween 60 and Tween 80. As sole carbon sources, sucrose, fructose, cysteine, propionate, valerate, 3-hydroxybutyric acid, acetate, 3-hydroxy benzoate, L- serine, potassium gluconate and aesculin ferric citrate are utilized, but maltose, arabinose, glucose, celllobiose, rhamnose, sorbose, D- galactose, mannitol, sorbitol, D- ribose, seignette salt, L- proline, L- arginine, sarcosine, malic acid, sodium citrate and phenylalaline are not. For acid production, D- ribose, arabinose and xylose are positive, but glucose, cellobiose, rhamnose, sucrose, ribose, fructose, lactose, D-galactose, maltose, mannitol, sorbitol, sorbose and inositol are negative. Positive for alkaline phosphatase, esterase C4, esterase lipaes C8, valine arylamidase, leucine arylamidase, cysteine, trypsin, acid phosphatase, naphthol-AS-BI-phosphohydrolase, b- glucosidase and a- glucosidase, but negative for lipase C14, a - chymotrypsin, a- galactosidase, b-galactosidase, b- glucuronidase, N -acetyl-b- glucosaminidase, a- mannosidase and a- fucosidase activities. The main respiratory quinone is meanquinone-8(H4). The major components of cellular fatty acids are iso-C, C 17:1 ! 8 c, C, C 17:1 ! 6 c and C 17: 0 10-methyl (TBSA). The polar lipids were diphosphatidylglycerol, phosphatidylglycerol, four unknown phospholipids and one unknown lipid. The cellwall peptidoglycan contains LL- diaminopimelic acid. 16: 0 17: 0 The type strain is S-34 T (= KCTC 49137 T = CCTCC AB 2018079 T), isolated from soil at Xinxiang Forest Ecology Park in Henan Province, PR China. The DNA G+C content of strain S-34 T was 71.2 %. The accession numbers of the 16S rRNA gene sequence and genome sequence of strain S-34 T are MH 341589 and QGDD 00000000, respectively.Published as part of Li, Chan, Shi, Kaixiang, Zhang, Yuxiao & Wang, Gejiao, 2019, Nocardioides silvaticus sp. nov., isolated from forest soil, pp. 68-73 in International Journal of Systematic and Evolutionary Microbiology 69 (1) on pages 72-73, DOI: 10.1099/ijsem.0.003079, http://zenodo.org/record/604863

A Hybrid Na//K+-Containing Electrolyte//O2 Battery with High Rechargeability and Cycle Stability

Na-O2 and K-O2 batteries have attracted extensive attention in recent years. However, the parasitic reactions involving the discharge product of NaO2 or K anode with electrolytes and the severe Na or K dendrites plague their rechargeability and cycle stability. Herein, we report a hybrid Na//K+-containing electrolyte//O2 battery consisting of a Na anode, 1.0 M of potassium triflate in diglyme, and a porous carbon cathode. Upon discharging, KO2 is preferentially produced via oxygen reduction in the cathode with Na+ stripped from the Na anode, and reversely, the KO2 is electrochemically decomposed with Na+ plated back onto the anode. The new reaction pathway can circumvent the parasitic reactions involving instable NaO2 and active K anode, and alternatively, the good stability and conductivity of KO2 and stable Na stripping/plating in the presence of K+ enable the hybrid battery to exhibit an average discharge/charge voltage gap of 0.15 V, high Coulombic efficiency of >96%, and superior cycling stability of 120 cycles. This will pave a new pathway to promote metal-air batteries

Terahertz Refractive Index Sensor Based on Enhanced Extraordinary Optical Transmission

This paper presents a structure for refractive index sensors in the terahertz (THz) band. The THZ sensor is studied in simulation, utilizing the strong local electromagnetic field intensity produced by the enhanced extraordinary optical transmission. Depending on the different sensing positions of the sensor, their sensing basis is also different, such as Mie scattering, surface plasmon polaritons, etc. The sensing sensitivity based on Mie scattering can reach 51.56 GHz/RIU; meanwhile the sensing sensitivity based on surface plasmon polaritons is only 5.13 GHz/RIU. The sensor can also detect the thickness of the analyte, with the lowest detectable height of 0.2 µm. Additionally, we find that the sensitivity can be increased by replacing the silicon particle with the analyte