Accurate understanding of the behavior of commercial-off-the-shelf electrical devices is important in many applications. This paper discusses methods for the principled statistical analysis of electrical device data. We present several recent successful efforts and describe two current areas of research that we anticipate will produce widely applicable methods. Because much electrical device data is naturally treated as functional, and because such data introduces some complications in analysis, we focus on methods for functional data analysis.
7th IEEE Electron Devices Technology and Manufacturing Conference: Strengthen the Global Semiconductor Research Collaboration After the Covid-19 Pandemic, EDTM 2023
This paper presents an assessment of electrical device measurements using functional data analysis (FDA) on a test case of Zener diode devices. We employ three techniques from FDA to quantify the variability in device behavior, primarily due to production lot and demonstrate that this has a significant effect in our data set. We also argue for the expanded use of FDA methods in providing principled, quantitative analysis of electrical device data.
7th IEEE Electron Devices Technology and Manufacturing Conference: Strengthen the Global Semiconductor Research Collaboration After the Covid-19 Pandemic, EDTM 2023
Accurate characterization of electrical device behavior is a key component of developing accurate electrical models and assessing reliability. Measurements characterizing an electrical device can be produced from current-voltage (I-V) sweeps. We introduce the pairwise midpoint method (PMM) for estimating the mean of a functional data set and apply it to I-V sweeps from a Zener diode. Comparisons indicate that the PMM is a viable method for describing the mean behavior of a functional data set.
Measurements performed on a population of electronic devices reveal part-to-part variation due to manufacturing process variation. Corner models are a useful tool for the designers to bound the effect of this variation on circuit performance. To accurately simulate the circuit level behavior, compact model parameters for devices within a circuit must be calibrated to experimental data. However, determination of the bounding data for corner model calibration is difficult, primarily because available tolerance bound calculation methods only consider variability along one dimension and, do not adequately consider the variabilities across both the current and voltage axes. This paper presents the demonstration of a novel functional data analysis approach to generate tolerance bounds on these two types of variability separately and these bounds are then transformed to be used in corner model calibration.
Privat, Aymeric; Barnaby, Hugh J.; Adell, Phillipe C.; Tolleson, B.S.; Wang, Y.; Davis, P.; Buchheit, Thomas E.
A multiscale modeling platform that supports the “virtual” qualification of commercial-off-the-shelf parts is presented. The multiscale approach is divided into two modules. The first module generates information related to the bipolar junction transistor gain degradation that is a function of fabrication process, operational, and environmental inputs. The second uses this information as inputs for radiation-enabled circuit simulations. The prototype platform described in this paper estimates the total ionizing dose and dose rate responses of linear bipolar integrated circuits for different families of components. The simulation and experimental results show good correlation and suggest this platform to be a complementary tool within the radiation-hardness assurance flow. Finally, the platform may reduce some of the costly reliance on testing for all systems.
Nominal behavior selection of an electronic device from a measured dataset is often difficult. Device characteristics are rarely monotonic and choosing the single device measurement which best represents the center of a distribution across all regions of operation is neither obvious nor easy to interpret. Often, a device modeler uses a degree of subjectivity when selecting nominal device behavior from a dataset of measurements on a group of devices. This paper proposes applying a functional data approach to estimate the mean and nominal device of an experimental dataset. This approach was applied to a dataset of electrical measurements on a set of commercially available Zener diodes and proved to more accurately represent the average device characteristics than a point-wise calculation of the mean. It also enabled an objective method for selecting a nominal device from a dataset of device measurements taken across the full operating region of the Zener diode.
Nominal behavior selection of an electronic device from a measured dataset is often difficult. Device characteristics are rarely monotonic and choosing the single device measurement which best represents the center of a distribution across all regions of operation is neither obvious nor easy to interpret. Often, a device modeler uses a degree of subjectivity when selecting nominal device behavior from a dataset of measurements on a group of devices. This paper proposes applying a functional data approach to estimate the mean and nominal device of an experimental dataset. This approach was applied to a dataset of electrical measurements on a set of commercially available Zener diodes and proved to more accurately represent the average device characteristics than a point-wise calculation of the mean. It also enabled an objective method for selecting a nominal device from a dataset of device measurements taken across the full operating region of the Zener diode.
This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.
Sealing glasses are ubiquitous in high pressure and temperature engineering applications, such as hermetic feed-through electrical connectors. A common connector technology are glass-to-metal seals where a metal shell compresses a sealing glass to create a hermetic seal. Though finite-element analysis has been used to understand and design glass-to-metal seals for many years, there has been little validation of these models. An indentation technique was employed to measure the residual stress on the surface of a simple glass-to-metal seal. Recently developed rate- dependent material models of both Schott 8061 and 304L VAR stainless steel have been applied to a finite-element model of the simple glass-to-metal seal. Model predictions of residual stress based on the evolution of material models are shown. These model predictions are compared to measured data. Validity of the finite- element predictions is discussed. It will be shown that the finite-element model of the glass-to-metal seal accurately predicts the mean residual stress in the glass near the glass-to-metal interface and is valid for this quantity of interest.
Predicting the residual stress which develops during fabrication of a glass-to-metal compression seal requires material models that can accurately predict the effects of processing on the sealing glass. Validation of the predictions requires measurements on representative test geometries to accurately capture the interaction between the seal materials during a processing cycle required to form the seal, which consists of a temperature excursion through the glass transition temperature of the sealing glass. To this end, a concentric seal test geometry, referred to as a short cylinder seal, consisting of a stainless steel shell enveloping a commercial sealing glass disk has been designed, fabricated, and characterized as a model validation test geometry. To obtain data to test/validate finite element (FE) stress model predictions of this geometry, spatially-resolved residual stress was calculated from the measured lengths of the cracks emanating from radially positioned Vickers indents in the glass disk portion of the seal. The indentation crack length method is described, and the spatially-resolved residual stress determined experimentally are compared to FE stress predictions made using a nonlinear viscoelastic material model adapted to inorganic sealing glasses and an updated rate dependent material model for 304L stainless steel. The measurement method is a first to achieve a degree of success for measuring spatially resolved residual stress in a glass-bearing geometry and a favorable comparison between measurements and simulation was observed.
We present a new, non-destructive electrical technique, Power Spectrum Analysis (PSA). PSA as described here uses off-normal biasing, an unconventional way of powering microelectronics devices. PSA with off-normal biasing can be used to detect subtle differences between microelectronic devices. These differences, in many cases, cannot be detected by conventional electrical testing. In this paper, we highlight PSA applications related to aging and counterfeit detection.
In this work, a crystal plasticity-finite element (CP-FE) model is used to investigate the effects of microstructural variability at a notch tip in tantalum single crystals and polycrystals. It is shown that at the macroscopic scale, the mechanical response of single crystals is sensitive to the crystallographic orientation while the response of polycrystals shows relatively small susceptibility to it. However, at the microscopic scale, the local stress and strain fields in the vicinity of the crack tip are completely determined by the local crystallographic orientation at the crack tip for both single and polycrystalline specimens with similar mechanical field distributions. Variability in the local metrics used (maximum von Mises stress and equivalent plastic strain at 3% deformation) for 100 different realizations of polycrystals fluctuates by up to a factor of 2-7 depending on the local crystallographic texture. Comparison with experimental data shows that the CP model captures variability in stress-strain response of polycrystals that can be attributed to the grain-scale microstructural variability. This work provides a convenient approach to investigate fluctuations in the mechanical behavior of polycrystalline materials induced by grain morphology and crystallographic orientations.
A series of Ti-rich Ni-Ti-Pt ternary alloys with 13 to 18 at. pct Pt were processed by vacuum arc melting and characterized for their transformation behavior to identify shape memory alloys (SMA) that undergo transformation between 448 K and 498 K (175 °C and 225 °C) and achieve recoverable strain exceeding 2 pct. From this broader set of compositions, three alloys containing 15.5 to 16.5 at. pct Pt exhibited transformation temperatures in the vicinity of 473 K (200 °C), thus were targeted for more detailed characterization. Preliminary microstructural evaluation of these three compositions revealed a martensitic microstructure with small amounts of Ti2(Ni,Pt) particles. Room temperature mechanical testing gave a response characteristic of martensitic de-twinning followed by a typical work-hardening behavior to failure. Elevated mechanical testing, performed while the materials were in the austenitic state, revealed yield stresses of approximately 500 MPa and 3.5 pct elongation to failure. Thermal strain recovery characteristics were more carefully investigated with unbiased incremental strain-temperature tests across the 1 to 5 pct strain range, as well as cyclic strain-temperature tests at 3 pct strain. The unbiased shape recovery results indicated a complicated strain recovery path, dependent on prestrain level, but overall acceptable SMA behavior within the targeted temperature and recoverable strain range.
In this report, we present a multi-scale computational model to simulate plastic deformation of tantalum and validating experiments. In atomistic/ dislocation level, dislocation kink- pair theory is used to formulate temperature and strain rate dependent constitutive equations. The kink-pair theory is calibrated to available data from single crystal experiments to produce accurate and convenient constitutive laws. The model is then implemented into a BCC crystal plasticity finite element method (CP-FEM) model to predict temperature and strain rate dependent yield stresses of single and polycrystalline tantalum and compared with existing experimental data from the literature. Furthermore, classical continuum constitutive models describing temperature and strain rate dependent flow behaviors are fit to the yield stresses obtained from the CP-FEM polycrystal predictions. The model is then used to conduct hydro- dynamic simulations of Taylor cylinder impact test and compared with experiments. In order to validate the proposed tantalum CP-FEM model with experiments, we introduce a method for quantitative comparison of CP-FEM models with various experimental techniques. To mitigate the effects of unknown subsurface microstructure, tantalum tensile specimens with a pseudo-two-dimensional grain structure and grain sizes on the order of millimeters are used. A technique combining an electron back scatter diffraction (EBSD) and high resolution digital image correlation (HR-DIC) is used to measure the texture and sub-grain strain fields upon uniaxial tensile loading at various applied strains. Deformed specimens are also analyzed with optical profilometry measurements to obtain out-of- plane strain fields. These high resolution measurements are directly compared with large-scale CP-FEM predictions. This computational method directly links fundamental dislocation physics to plastic deformations in the grain-scale and to the engineering-scale applications. Furthermore, direct and quantitative comparisons between experimental measurements and simulation show that the proposed model accurately captures plasticity in deformation of polycrystalline tantalum.
This report provides a detailed characterization Tri-lab Tantalum (Ta) plate jointly purchased from HCStark Inc. by Sandia, Los Alamos and Lawrence Livermore National Laboratories. Data in this report was compiled from series of material and properties characterization experiments carried out at Sandia (SNL) and Los Alamos (LANL) Laboratories through a leveraged effort funded by the C2 campaign. Results include microstructure characterization detailing the crystallographic texture of the material and an increase in grain size near the end of the rolled plate. Mechanical properties evaluations include, compression cylinder, sub-scale tension specimen, micohardness and instrumented indentation testing. The plate was found to have vastly superior uniformity when compare with previously characterized wrought Ta material. Small but measurable variations in microstructure and properties were noted at the end, and at the top and bottom edges of the plate.
Crystallographic slip planes in body centered cubic (BCC) metals are not fully understood. In polycrystals, there are additional confounding effects from grain interactions. This paper describes an experimental investigation into the effects of grain orientation and neighbors on elastic–plastic strain accumulation. In situ strain fields were obtained by performing digital image correlation (DIC) on images from a scanning electron microscope (SEM) and from optical microscopy. These strain fields were statistically compared to the grain structure measured by electron backscatter diffraction (EBSD). Spearman rank correlations were performed between effective strain and six microstructural factors including four Schmid factors associated with the <111> slip direction, grain size, and Taylor factor. Modest correlations (~10%) were found for a polycrystal tension specimen. The influence of grain neighbors was first investigated by re-correlating the polycrystal data using clusters of similarly-oriented grains identified by low grain boundary misorientation angles. Second, the experiment was repeated on a tantalum oligocrystal, with through-thickness grains. Much larger correlation coefficients were found in this multicrystal due to the dearth of grain neighbors and subsurface microstructure. Finally, a slip trace analysis indicated (in agreement with statistical correlations) that macroscopic slip often occurs on {110}<111> slip systems and sometimes by pencil glide on maximum resolved shear stress planes (MRSSP). These results suggest that Schmid factors are suitable for room temperature, quasistatic, tensile deformation in tantalum as long as grain neighbor effects are accounted for.
The goal of this LDRD project is to develop a rapid first-order experimental procedure for the testing of advanced cladding materials that may be considered for generation IV nuclear reactors. In order to investigate this, a technique was developed to expose the coupons of potential materials to high displacement damage at elevated temperatures to simulate the neutron environment expected in Generation IV reactors. This was completed through a high temperature high-energy heavy-ion implantation. The mechanical properties of the ion irradiated region were tested by either micropillar compression or nanoindentation to determine the local properties, as a function of the implantation dose and exposure temperature. In order to directly compare the microstructural evolution and property degradation from the accelerated testing and classical neutron testing, 316L, 409, and 420 stainless steels were tested. In addition, two sets of diffusion couples from 316L and HT9 stainless steels with various refractory metals. This study has shown that if the ion irradiation size scale is taken into consideration when developing and analyzing the mechanical property data, significant insight into the structural properties of the potential cladding materials can be gained in about a week.
Mudstone mechanical testing is often limited by poor core recovery and sample size, preservation and preparation issues, which can lead to sampling bias, damage, and time-dependent effects. A micropillar compression technique, originally developed by Uchic et al. 2004, here is applied to elasto-plastic deformation of small volumes of mudstone, in the range of cubic microns. This study examines behavior of the Gothic shale, the basal unit of the Ismay zone of the Pennsylvanian Paradox Formation and potential shale gas play in southeastern Utah, USA. Precision manufacture of micropillars 5 microns in diameter and 10 microns in length are prepared using an ion-milling method. Characterization of samples is carried out using: dual focused ion - scanning electron beam imaging of nano-scaled pores and distribution of matrix clay and quartz, as well as pore-filling organics; laser scanning confocal (LSCM) 3D imaging of natural fractures; and gas permeability, among other techniques. Compression testing of micropillars under load control is performed using two different nanoindenter techniques. Deformation of 0.5 cm in diameter by 1 cm in length cores is carried out and visualized by a microscope loading stage and laser scanning confocal microscopy. Axisymmetric multistage compression testing and multi-stress path testing is carried out using 2.54 cm plugs. Discussion of results addresses size of representative elementary volumes applicable to continuum-scale mudstone deformation, anisotropy, and size-scale plasticity effects. Other issues include fabrication-induced damage, alignment, and influence of substrate.
Shock testing was performed on a selected commercial-off-the-shelf - MicroElectroMechanical System (COTS-MEMS) accelerometer to determine the margin between the published absolute maximum rating for shock and the 'measured' level where failures are observed. The purpose of this testing is to provide baseline data for isolating failure mechanisms under shock and environmental loading in a representative device used or under consideration for use within systems and assemblies of the DOD/DOE weapons complex. The specific device chosen for this study was the AD22280 model of the ADXL78 MEMS Accelerometer manufactured by Analog Devices Inc. This study focuses only on the shock loading response of the device and provides the necessary data for adding influence of environmental exposure to the reliability of this class of devices. The published absolute maximum rating for acceleration in any axis was 4000 G for this device powered or unpowered. Results from this study showed first failures at 8000 G indicating a margin of error of two. Higher shock level testing indicated that an in-plane, but off-axis acceleration was more damaging than one in the sense direction.
Shape memory alloys (SMAs) are metals that exhibit large recoverable strains and exert large forces with tremendous energy densities. The behavior of SMAs is thermomechanically coupled. Their response to temperature is sensitive to their loading condition and their response to loading is sensitive to their thermal condition. This coupled behavior is not to be circumvented, but to be confronted and understood, since it is what manifests SMA's superior clamping performance. To reasonably characterize the coupled behavior of SMA clamping rings used in safety mechanisms, we conduct a series of experiments on SMA samples. The results of the tests will allow increased fidelity in modeling and failure analysis of parts.
Instrumented indentation has yielded mixed results when used to measure surface residual stresses in metal films. Relative to metals, many glasses and ceramics have a low modulus-to-yield strength (E/σ y) ratio. The advantage of this characteristic for measuring residual stress using instrumented indentation is demonstrated by a series of comparative spherical and conical tip finite element simulations. Two cases are considered: (i) a material with E/σ y= 24 - similar to glass and (ii) a material with E /σy = 120 - similar to metal films. In both cases, compressive residual stress shifts the simulated load-displacement response toward increasing hardness, irrespective of tip geometry. This shift is shown to be entirely due to pile up for the "metal" case, but primarily due to the direct influence of the residual stress for the "glass" case. Hardness changes and load-displacement curve shifts are explained by using the spherical cavity model. Supporting experimental results on stressed glasses are provided.
Instrumented indentation has yielded mixed results when used to measure surface residual stresses in metal films. Relative to metals, many glasses and ceramics have a low modulus-to-yield strength (E/sy) ratio. The advantage of this characteristic for measuring residual stress using instrumented indentation is demonstrated by a series of comparative spherical and conical tip finite element simulations. Two cases are considered: (i) a material with E/s{sub y} = 24-similar to glass and (ii) a material with E/s{sub y} = 120-similar to metal films. In both cases, compressive residual stress shifts the simulated load-displacement response toward increasing hardness, irrespective of tip geometry. This shift is shown to be entirely due to pile up for the ''metal'' case, but primarily due to the direct influence of the residual stress for the ''glass'' case. Hardness changes and load-displacement curve shifts are explained by using the spherical cavity model. Supporting experimental results on stressed glasses are provided.
The ability to integrate metal and semiconductor micro-systems to perform highly complex functions, such as RF-MEMS, will depend on developing freestanding metal structures that offer improved conductivity, reflectivity, and mechanical properties. Three issues have prevented the proliferation of these systems: (1) warpage of active components due to through-thickness stress gradients, (2) limited component lifetimes due to fatigue, and (3) low yield strength. To address these issues, we focus on developing and implementing techniques to enable the direct study of the stress and microstructural evolution during electrodeposition and mechanical loading. The study of stress during electrodeposition of metal thin films is being accomplished by integrating a multi-beam optical stress sensor into an electrodeposition chamber. By coupling the in-situ stress information with ex-situ microstructural analysis, a scientific understanding of the sources of stress during electrodeposition will be obtained. These results are providing a foundation upon which to develop a stress-gradient-free thin film directly applicable to the production of freestanding metal structures. The issues of fatigue and yield strength are being addressed by developing novel surface micromachined tensile and bend testers, by interferometry, and by TEM analysis. The MEMS tensile tester has a ''Bosch'' etched hole to allow for direct viewing of the microstructure in a TEM before, during, and after loading. This approach allows for the quantitative measurements of stress-strain relations while imaging dislocation motion, and determination of fracture nucleation in samples with well-known fatigue/strain histories. This technique facilitates the determination of the limits for classical deformation mechanisms and helps to formulate a new understanding of the mechanical response as the grain sizes are refined to a nanometer scale. Together, these studies will result in a science-based infrastructure to enhance the production of integrated metal--semiconductor systems and will directly impact RF MEMS and LIGA technologies at Sandia.
Micromachines have the potential to significantly impact future weapon component designs as well as other defense, industrial, and consumer product applications. For both electroplated (LIGA) and surface micromachined (SMM) structural elements, the influence of processing on structure, and the resultant effects on material properties are not well understood. The behavior of dynamic interfaces in present as-fabricated microsystem materials is inadequate for most applications and the fundamental relationships between processing conditions and tribological behavior in these systems are not clearly defined. We intend to develop a basic understanding of deformation, fracture, and surface interactions responsible for friction and wear of microelectromechanical system (MEMS) materials. This will enable needed design flexibility for these devices, as well as strengthen our understanding of material behavior at the nanoscale. The goal of this project is to develop new capabilities for sub-microscale mechanical and tribological measurements, and to exercise these capabilities to investigate material behavior at this size scale.
The purpose of microstructural control is to optimize materials properties. To that end, they have developed sophisticated and successful computational models of both microstructural evolution and mechanical response. However, coupling these models to quantitatively predict the properties of a given microstructure poses a challenge. This problem arises because most continuum response models, such as finite element, finite volume, or material point methods, do not incorporate a real length scale. Thus, two self-similar polycrystals have identical mechanical properties regardless of grain size, in conflict with theory and observations. In this project, they took a tiered risk approach to incorporate microstructure and its resultant length scales in mechanical response simulations. Techniques considered include low-risk, low-benefit methods, as well as higher-payoff, higher-risk methods. Methods studied include a constitutive response model with a local length-scale parameter, a power-law hardening rate gradient near grain boundaries, a local Voce hardening law, and strain-gradient polycrystal plasticity. These techniques were validated on a variety of systems for which theoretical analyses and/or experimental data exist. The results may be used to generate improved constitutive models that explicitly depend upon microstructure and to provide insight into microstructural deformation and failure processes. Furthermore, because mechanical state drives microstructural evolution, a strain-enhanced grain growth model was coupled with the mechanical response simulations. The coupled model predicts both properties as a function of microstructure and microstructural development as a function of processing conditions.
This report summarizes materials issues associated with advanced micromachines development at Sandia. The intent of this report is to provide a perspective on the scope of the issues and suggest future technical directions, with a focus on computational materials science. Materials issues in surface micromachining (SMM), Lithographic-Galvanoformung-Abformung (LIGA: lithography, electrodeposition, and molding), and meso-machining technologies were identified. Each individual issue was assessed in four categories: degree of basic understanding; amount of existing experimental data capability of existing models; and, based on the perspective of component developers, the importance of the issue to be resolved. Three broad requirements for micromachines emerged from this process. They are: (1) tribological behavior, including stiction, friction, wear, and the use of surface treatments to control these, (2) mechanical behavior at microscale, including elasticity, plasticity, and the effect of microstructural features on mechanical strength, and (3) degradation of tribological and mechanical properties in normal (including aging), abnormal and hostile environments. Resolving all the identified critical issues requires a significant cooperative and complementary effort between computational and experimental programs. The breadth of this work is greater than any single program is likely to support. This report should serve as a guide to plan micromachines development at Sandia.
Computational materials simulations have traditionally focused on individual phenomena: grain growth, crack propagation, plastic flow, etc. However, real materials behavior results from a complex interplay between phenomena. In this project, the authors explored methods for coupling mesoscale simulations of microstructural evolution and micromechanical response. In one case, massively parallel (MP) simulations for grain evolution and microcracking in alumina stronglink materials were dynamically coupled. In the other, codes for domain coarsening and plastic deformation in CuSi braze alloys were iteratively linked. this program provided the first comparison of two promising ways to integrate mesoscale computer codes. Coupled microstructural/micromechanical codes were applied to experimentally observed microstructures for the first time. In addition to the coupled codes, this project developed a suite of new computational capabilities (PARGRAIN, GLAD, OOF, MPM, polycrystal plasticity, front tracking). The problem of plasticity length scale in continuum calculations was recognized and a solution strategy was developed. The simulations were experimentally validated on stockpile materials.
The behavior of MEMS devices is limited by the strength of critical features such as thin ligaments, oxide cuts joining layers, pin joints and hinges. Devices fabricated at Sandia's Microelectronic Development Laboratory have been successfully tested to investigate these features. A series of measurements were performed on samples with gage lengths of 15 to 1000 microns, using conventional and tungsten coated samples as well as samples that include the critical features of standard components in the test section. Specimens have a freely moving pin joint on one end that anchors the sample to the silicon die to allow rotation to reduce effects of bending. Each sample is loaded in uniaxial tension by pulling laterally with a flat tipped diamond in a computer-controlled Nanoindenter. Load is calculated by resolving the measured lateral and normal forces into the applied tensile force and frictional losses. The specimen cross section and gage length dimensions were verified by measuring against a standard in the SEM. Multiple tests can be programmed at one time and performed without operator assistance allowing the collection of significant populations of data.
Direct metal deposition technologies produce complex, near net shape components from Computer Aided Design (CAD) solid models. Most of these techniques fabricate a component by melting powder in a laser weld pool, rastering the weld bead to form a layer, and additively constructing subsequent layers. This report will describe anew direct metal deposition process, known as WireFeed, whereby a small diameter wire is used instead of powder as the feed material to fabricate components. Currently, parts are being fabricated from stainless steel alloys. Microscopy studies show the WireFeed parts to be filly dense with fine microstructural features. Mechanical tests show stainless steel parts to have high strength values with retained ductility. A model was developed to simulate the microstructural evolution and coarsening during the WireFeed process. Simulations demonstrate the importance of knowing the temperature distribution during fabrication of a WireFeed part. The temperature distribution influences microstructural evolution and, therefore, must be controlled to tailor the microstructure for optimal performance.
LIGA fabricated materials and components exhibit several processing issues affecting their metallurgical and mechanical properties, potentially limiting their usefulness for MEMS applications. For example, LIGA processing by metal electrodeposition is very sensitive to deposition conditions which causes significant processing lot variations of mechanical and metallurgical properties. Furthermore, the process produces a material with a highly textured lenticular rnicrostructural morphology suggesting an anisotropic material response. Understanding and controlling out-of-plane anisotropy is desirable for LIGA components designed for out-of-plane flexures. Previous work by the current authors focused on results from a miniature servo-hydraulic mechanical test frame constructed for characterizing LIGA materials. Those results demonstrated microstructural and mechanical properties dependencies with plating bath current density in LIGA fabricated nickel (LIGA Ni). This presentation builds on that work and fosters a methodology for controlling the properties of LIGA fabricated materials through processing. New results include measurement of mechanical properties of LIGA fabricated copper (LIGA Cu), out-of-plane and localized mechanical property measurements using compression testing and nanoindentation of LIGA Ni and LIGA Cu.