Accurate temperature measurements on semiconductor devices.

Self-heating can have a detrimental effect on the performance and reliability of high power microwave devices. In this work, the thermal performance of the gallium arsenide (GaAs) Gunn diode was studied. Infrared (IR) thermal microscopy was used to measure the peak operating temperature of the graded-gap structured device. Temperature measurements were experimentally validated using micro-thermocouple probing and compared to values obtained from a standard 1D thermal resistance model. Thermal analysis of the conventionally structured Gunn diode was also undertaken using high resolution micro-Raman temperature profiling, IR thermal microscopy and electro/thermal finite element modeling. The accuracy of conventional IR temperature measurements, made on semiconductor devices, was investigated in detail. Significant temperature errors were shown to occur in IR temperature measurements made on IR transparent semiconductors layers and low emissivity/highly reflective metals. A new technique, employing spherical carbon microparticles, was developed to improve the measurement accuracy on such surfaces. The new ‘IR microparticle’ technique can be used with existing IR microscopes and potentially removes the need to coat a device with a high emissivity layer, which causes damage and heat spreading

Estimativa de Estados e Parâmetros para Microtrocadores de Calor Utilizando Filtros de Partículas

Este trabalho descreve um estudo de problema inverso aplicado a um microdissipador de calor de nanocompósito com microcanais. O código da simulação criado no software Fluent (ANSYS) foi verificado por um outro código apresente na literatura e validado por dados experimentais gerados por uma câmera por infravermelho. Os parâmetros que influenciam o problema em questão foram obtidos através de análises de sensibilidade. As influências das velocidades do fluido nas temperaturas de todos os pontos da superfície externa do microtrocador de calor foram adquiridas através de uma outra análise de sensibilidade. Os resultados da análise de problemas inversos foram alcançados através da interação dos software Matlab e Fluent (ANSYS) onde esse último software gerou os resultados do problema direto que foram utilizados pelo Matlab que contém o código do cálculo do filtro de partículas SIR. Através desse método, as velocidades do fluido e o campo de temperatura do microtrocador de calor foram estimados

The effect of plasma welding and carbides presence on the occurrence of cracks and micro-cracks

Presented in this paper is the effect of plasma welding (hardfacing) and carbides presence on the occurrence of cracks and micro-cracks in the welded layer. The reasons behind this phenomenon were analyzed and explained. In addition, the plasma welding technology with all the necessary data such as welding parameters is shown for the case of a non-damaged tooth of a machine used for milling of marble. Welded layer with a significant amount of tungsten-carbide was applied onto new, non-damaged tooth in order to improve the characteristics of the surface layer of the base material, by increasing its hardness which leads to increasing of wear resistance and impact toughness. After welding, tooth was cut using an electrical discharge machining (EDM) for the purpose of examinations of the ap-plied surface layer in different locations throughout welded joint. Macro and micro-structure analysis aided in determining the characteristics of the surface layer. The nature and causes of cracks and micro-cracks were analyzed, in order to provide a better solution to avoid cracks occurrences, as well as in determining of their potential effect on the integri-ty of the tooth as a whole

Advances on Mechanics, Design Engineering and Manufacturing III

This open access book gathers contributions presented at the International Joint Conference on Mechanics, Design Engineering and Advanced Manufacturing (JCM 2020), held as a web conference on June 2–4, 2020. It reports on cutting-edge topics in product design and manufacturing, such as industrial methods for integrated product and process design; innovative design; and computer-aided design. Further topics covered include virtual simulation and reverse engineering; additive manufacturing; product manufacturing; engineering methods in medicine and education; representation techniques; and nautical, aeronautics and aerospace design and modeling. The book is organized into four main parts, reflecting the focus and primary themes of the conference. The contributions presented here not only provide researchers, engineers and experts in a range of industrial engineering subfields with extensive information to support their daily work; they are also intended to stimulate new research directions, advanced applications of the methods discussed and future interdisciplinary collaborations

Predicting melt pool behaviour in LPBF through high fidelity modelling

Empirical process parameter optimisation for laser powder bed fusion (LPBF) is a long, arduous process that inefficiently locates process parameters that may or may not be optimal. It is often circumstantial; meaning it is dependent on the thermodynamic regime at a given location within a component. In order to obtain mastery of this process we must control the energy distribution delivered to the melt pool. Reducing the porosity and cracking of components made through LPBF is still the largest barrier for entry in high integrity applications. Optimising laser power and speed are considered two of the most influential factors in LPBF, which drive track consolidation, reducing porosity. These parameters though, are difficult to link to desirable melt pool properties, without extensive experimental testing. Controlling the process via surface temperature has been shown to substantially improve processing, as well as provide a more direct link with the process. However, no literature examines which melt pool temperatures are optimal in producing highly dense components. The primary novelty in this work is the derivation and validation of a novel optimisation method that monitors and modulates peak melt pool temperatures by varying the laser power administered to the melt pool through computational modelling. Understanding optimal melt pool peak temperatures is a valuable approach since increasingly, machine tools are able to monitor surface temperature and, in the future, attenuate energy density accordingly. This work provides a framework in which porosity and cracking defects can be eliminated through optimal process parameter calculations. This process parameter optimisation utilises high performance computing facilities to simulate LPBF at small time durations, with high resolution. This aspect has been shown to be critical in providing detailed information for the evaluation of cracking behaviours and the prediction of optimal processing conditions. This work makes use of a ‘high fidelity model’ to accurately and precisely measure and evaluate conditions within LPBF, in addition to providing a platform for the process optimisation to run from. Model fidelity here describes the exactness of the degree to which something is copied or produced. For this model, this involves including fundamental physics that describe how photons in the laser beam are reflected and absorbed into the metal surface, rather than using approximations to generalise the heat input. For example, a low fidelity heat source would use a volumetric approach to heat the metal powder particles. This includes assumptions as to the absorptivity of the powder bed, how deep that particular laser would heat the powder bed, and therefore would have a larger error when comparing the temperature on the powder surface to experiments. A high fidelity heat source, that will be used in this work, replicates reality to a higher degree, so that temperatures can be modelled with greater accuracy. In this instance, ray tracing has been proven in literature to accurately reflect the behaviour of photons interacting with the metal surface, so that the absorptivity of the metal is not approximated, but calculated using the Fresnel equations [1]. A high fidelity model does not have to be non-linear, but often is due to temperature dependant properties. In this work, complex physical phenomena such as: melting and solidification, buoyancy effects, surface tension, temperature dependant surface tension (Marangoni flow), vaporisation phenomena including recoil pressure and evaporation flux, melt pool flow and variable absorptivity from the Fresnel equations, and a stochastic powder bed are used to replicate LPBF through numerical modelling. The model is designed to be flexible and user friendly, to allow the modification of every aspect of the laser, powder and other process conditions. Three main research chapters are presented in this work, along with an extensive literature review covering the complex nature of LPBF, combined with a methodology to create a high fidelity model to simulate this process. Results have been validated with four different validation experimental to model comparisons. These validations include; Validation against a continuous laser system for 316L stainless steel in conduction mode Validation against a continuous laser system for 316L stainless steel in keyhole mode Validation against a ramp up laser profile for 316L stainless steel Validation against a pulsed laser system for AA204 for two different parameter sets. These results include validation with a variable pulsed laser system for 316L stainless steel, to ensure that the model can be used with variable laser conditions, as well as a more typical continuous wave laser. In order to replicate LPBF single track deposition of high strength aluminium alloy AA2024, a revised refractive index was tailored to experimental conditions. Literature shows how literature values of absorptivity of aluminium do not represent the measured behaviour in LPBF. For the first time, this work combines a revised refractive index to simulate absorptivity of AA2024, whilst keeping a high fidelity ray tracing heat source. This allows for detailed analysis of the development of porosity, which is vital in determining track consolidation. The main body of this work comprises of a predictive framework for LPBF parameter optimisation. This framework has been proven for two different material systems, 316L stainless steel and AA2024. Using an inverse solution, a link is created between laser power and melt pool temperature, allowing for stable melt pools to be established and maintained throughout a single track deposition. Links have been established with surface temperature and common LPBF defects, such as a lack of fusion defects and keyhole porosity. A new parameter, P-ratio, has been derived and shown to work as a single processing variable that LPBF can be optimised too. P-ratio has proven to be independent of laser speed, and provides a constant recoil pressure to the surface of a melt pool to ensure track consolidation. This work uses a case study on AA2024, to validate the inverse solution with a second material system. The inverse solution correctly identifies a laser power at a set point distance and exposure time that gives the highest density, compared to samples validated in experimental conditions. Additionally, the model has successfully demonstrated its use in measuring and evaluating cracking for high strength aluminium alloy, AA2024. Data generated by the model clearly shows differences between cracked and crack free parameter sets. Large differences in cooling rates and temperature gradients show that the main drivers for cracking in LPBF can be evaluated with the high fidelity model. Results from this work will be used to predict and eliminate cracking in high strength aluminium alloys