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At least 397 records · Page 22

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NASA NTRS2016

Exercise Effects on the Brain and Sensorimotor Function in Bed Rest

Long duration spaceflight microgravity results in cephalad fluid shifts and deficits in posture control and locomotion. Effects of microgravity on sensorimotor function have been investigated on Earth using head down tilt bed rest (HDBR). HDBR serves as a spaceflight analogue because it mimics microgravity in body unloading and bodily fluid shifts. Preliminary results from our prior 70 days HDBR studies showed that HDBR is associated with focal gray matter (GM) changes and gait and balance deficits, as well as changes in brain functional connectivity. In consideration of the health and performance of crewmembers we investigated whether exercise reduces the effects of HDBR on GM, functional connectivity, and motor performance. Numerous studies have shown beneficial effects of exercise on brain health. We therefore hypothesized that an exercise intervention during HDBR could potentially mitigate the effects of HDBR on the central nervous system. Eighteen subjects were assessed before (12 and 7 days), during (7, 30, and ~70 days) and after (8 and 12 days) 70 days of 6-degrees HDBR at the NASA HDBR facility in UTMB, Galveston, TX, US. Each subject was randomly assigned to a control group or one of two exercise groups. Exercise consisted of daily supine exercise which started 20 days before the start of HDBR. The exercise subjects participated either in regular aerobic and resistance exercise (e.g. squat, heel raise, leg press, cycling and treadmill running), or aerobic and resistance exercise using a flywheel apparatus (rowing). Aerobic and resistance exercise intensity in both groups was similar, which is why we collapsed the two exercise groups for the current experiment. During each time point T1-weighted MRI scans and resting state functional connectivity scans were obtained using a 3T Siemens scanner. Focal changes over time in GM density were assessed using voxel based morphometry (VBM8) under SPM. Changes in resting state functional connectivity was assessed using both a region of interest (ROI, or seed-to-voxel) approach as well as a whole brain intrinsic connectivity (i.e., voxel-to-voxel) analysis. For the ROI analysis we selected 11 ROIs of brain regions that are involved in sensorimotor function (i.e., L. Insular C., L. Putamen, R. Premotor C., L.+R. Primary Motor C., R. Vestibular C., L. Posterior Cingulate G., R. Cerebellum Lobule V + VIIIb + Crus I, and the R. Superior Parietal G.) and correlated their time course of brain activation during rest with all other voxels in the brain. The whole brain connectivity analysis tests changes in the strength of the global connectivity pattern between each voxel and the rest of the brain. Functional mobility was assessed using an obstacle course. Vestibular contribution to balance was measured using Neurocom Sensory Organization Test 5. Behavioral measures were assessed pre-HDBR, and 0, 8 and 12 days post-HDBR. Linear mixed models were used to test for effects of time, group, and group-by-time interactions. Family-wise error corrected VBM revealed significantly larger increases in GM volume in the right primary motor cortex in bed rest control subjects than in bed rest exercise subjects. No other significant group by time interactions in gray matter changes with bed rest were observed. Functional connectivity MRI revealed that the increase in connectivity during bed rest of the left putamen with the bilateral midsagittal precunes and the right cingulate gyrus was larger in bed rest control subjects than in bed rest exercise subjects. Furthermore, the increase in functional connectivity with bed rest of the right premotor cortex with the right inferior frontal gyrus and the right primary motor cortex with the bilateral premotor cortex was smaller in bed rest control subjects than in bed rest exercise subjects. Functional mobility performance was less affected by HDBR in exercise subjects than in control subjects and post HDBR exercise subjects recovered faster than control subjects. The group performance differences and GM changes were not related. Exercise in HDBR partially mitigates the adverse effect of HDBR on functional mobility, particularly during the post-bed rest recovery phase. In addition, exercise appears to result in differential brain structural and functional changes in motor regions such as the primary motor cortex, the premotor cortex and the putamen. Whether these central nervous system changes are related to motor behavioral changes including gait and balance warrants further research.

Koppelmans, V.↗

DOE OSTI2024

A new approach to the evaluation and solution of the relativistic kinetic dispersion relation and verification with continuum kinetic simulation

Here, the present work describes a new approach to evaluation and root finding for the kinetic dispersion relation of Langmuir waves, which is central to the analytical understanding of collisionless damping in plasmas. The plasma dispersion function is solved to machine precision using direct integration in the complex plane in combination with an analytic evaluation of the residue to account for the deformation along the Landau contour. To efficiently attain machine precision, the contour is displaced in the complex plane prior to integration, and numerical subtleties related to the placement of the contour are discussed. The approach is generic in that it applies to arbitrary distribution functions, with the present manuscript focused on relativistic cases. Detailed verification of results via direct kinetic simulation in a variety of configuration space dimensions is also presented. Finally, the technique is applied to the challenging case of highly relativistic (i.e. extremely hot) plasmas. Here we show both qualitative agreement with prior work, as well as the disappearance of the Landau root which would have significant implication for real-life observation or experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2003

CLARAty Functional-Layer Software

Functional-layer software for the Coupled Layer Architecture for Robotics Autonomy (CLARAty) is being developed. [CLARAty was described in Coupled-Layer Architecture for Advanced Software for Robots (NPO-21218), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48. To recapitulate: CLARAty was proposed to improve the modularity of robotic software while tightening the coupling between planning/execution and control subsystems. Whereas prior robotic software architectures have typically contained three levels, the CLARAty architecture contains two layers: a decision layer and a functional layer.] Just as an operating system provides abstraction from computational hardware, the CLARAty functional-layer software provides for abstraction for the different robotic systems. The functional-layer software establishes interrelated, object-oriented hierarchies that contain active and passive objects that represent the different levels of system abstrations and components. The functional-layer software is decomposed into a set of reusable core components and a set of extended components that adapt the reusable set to specific hardware implementations. The reusable components (a) provide behavior and interface definitions and implementations of basic functionality, (b) provide local executive capabilities, (c) manage local resources, and (d) support state and resource queries by the decision layer. Software for robotic systems can be built by use of these components.

Nesnas, Issa↗

NASA NTRS2008

The Radio Luminosity Function and Galaxy Evolution in the Coma Cluster

We investigate the radio luminosity function and radio source population for two fields within the Coma cluster of galaxies, with the fields centered on the cluster core and southwest infall region and each covering about half a square degree. Using VLA data with a typical rms sensitivity of 28 (mu)Jy per 4.4" beam, we identify 249 radio sources with optical counterparts brighter than r = 22 (equivalent to M(sub r) = -13 for cluster member galaxies). Comprehensive optical spectroscopy identifies 38 of these as members of the Coma cluster, evenly split between sources powered by an active nucleus and sources powered by active star formation. The radio-detected star-forming galaxies are restricted to radio luminosities between about 10(exp 21) and 10(exp 22) W/Hz, an interesting result given that star formation dominates field radio luminosity functions below about 10(exp 23) W/Hz. The majority of the radio-detected star-forming galaxies have characteristics of starbursts, including high specific star formation rates and optical spectra with strong emission lines. In conjunction with prior studies on post-starburst galaxies within the Coma cluster, this is consistent with a picture in which late-type galaxies entering Coma undergo a starburst prior to a rapid cessation of star formation. Optically bright elliptical galaxies (Mr less than or equals -20.5) make the largest contribution to the radio luminosity function at both the high (> approx. 3x10(exp 22) W/Hz) and low (< approx. 10(exp 21) W/Hz) ends. Through a stacking analysis of these optically-bright ellipticals we find that they continue to harbor radio sources down to luminosities as faint as 3x10(exp 19) W/Hz. However, contrary to published results for the Virgo cluster we find no evidence for the existence of a population of optically faint (M(sub r) approx. equals -14) dwarf ellipticals hosting strong radio AGN.

Miller, Neal A.↗

DOE OSTI2024

Spike-and-Slab Shrinkage Priors for Structurally Sparse Bayesian Neural Networks

Network complexity and computational efficiency have become increasingly significant aspects of deep learning. Sparse deep learning addresses these challenges by recovering a sparse representation of the underlying target function by reducing heavily overparameterized deep neural networks. Specifically, deep neural architectures compressed via structured sparsity (e.g., node sparsity) provide low-latency inference, higher data throughput, and reduced energy consumption. In this article, we explore two well-established shrinkage techniques, Lasso and Horseshoe, for model compression in Bayesian neural networks (BNNs). To this end, we propose structurally sparse BNNs, which systematically prune excessive nodes with the following: 1) spike-and-slab group Lasso (SS-GL) and 2) SS group Horseshoe (SS-GHS) priors, and develop computationally tractable variational inference, including continuous relaxation of Bernoulli variables. We establish the contraction rates of the variational posterior of our proposed models as a function of the network topology, layerwise node cardinalities, and bounds on the network weights. Furthermore, we empirically demonstrate the competitive performance of our models compared with the baseline models in prediction accuracy, model compression, and inference latency.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Validation of the Cossee–Arlman mechanism for propylene oligomerization on Ni/UiO-66

Steady state rate expressions can be derived to distinguish the Cossee–Arlman and metallacycle mechanisms postulated for propylene oligomerization on nickel-based catalysts based on product selectivities, where product selectivities for the former are a function of olefin pressure because sequential coordination and insertion steps lead to independent mechanistic pathways for different hexene isomers. In contrast, the metallacycle mechanism presents pressure-independent product selectivities due to successive coordination prior to the kinetically relevant steps in each mechanism. In this work, steady state propylene oligomerization rates and selectivities were measured in the absence of an activator on nickel functionalized UiO-66 metal organic framework (MOF), Ni/UiO-66, to validate the Cossee–Arlman mechanism for light olefin oligomerization. In situ NO titrations reveal that ~5% of nickel sites were active during the reaction, and thus, not all nickel sites are relevant for catalysis. Propylene dimerization was first order in propylene pressure from 5 to 500 kPa with an apparent activation energy of ~20 kJ mol -1 from 453 to 493 K. Calculated apparent activation energies with density functional theory (DFT) calculations on cluster models of Ni/UiO-66 are in agreement with experiment to corroborate the Cossee–Arlman mechanism. Selectivities of hexene products and the ratio of hexene product selectivities on Ni/UiO-66 are in accordance with selectivity expressions derived from the Cossee–Arlman mechanism. In conclusion, analysis of product selectivities can be used more extensively to demarcate the Cossee–Arlman and metallacycle mechanisms for olefin oligomerization on metal-based catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2000

Hardware Development Process for Human Research Facility Applications

The simple goal of the Human Research Facility (HRF) is to conduct human research experiments on the International Space Station (ISS) astronauts during long-duration missions. This is accomplished by providing integration and operation of the necessary hardware and software capabilities. A typical hardware development flow consists of five stages: functional inputs and requirements definition, market research, design life cycle through hardware delivery, crew training, and mission support. The purpose of this presentation is to guide the audience through the early hardware development process: requirement definition through selecting a development path. Specific HRF equipment is used to illustrate the hardware development paths. The source of hardware requirements is the science community and HRF program. The HRF Science Working Group, consisting of SCientists from various medical disciplines, defined a basic set of equipment with functional requirements. This established the performance requirements of the hardware. HRF program requirements focus on making the hardware safe and operational in a space environment. This includes structural, thermal, human factors, and material requirements. Science and HRF program requirements are defined in a hardware requirements document which includes verification methods. Once the hardware is fabricated, requirements are verified by inspection, test, analysis, or demonstration. All data is compiled and reviewed to certify the hardware for flight. Obviously, the basis for all hardware development activities is requirement definition. Full and complete requirement definition is ideal prior to initiating the hardware development. However, this is generally not the case, but the hardware team typically has functional inputs as a guide. The first step is for engineers to conduct market research based on the functional inputs provided by scientists. CommerCially available products are evaluated against the science requirements as well as modifications needed to meet program requirements. Options are consolidated and the hardware development team reaches a hardware development decision point. Within budget and schedule constraints, the team must decide whether or not to complete the hardware as an in-house, subcontract with vendor, or commercial-off-the-shelf (COTS) development. An in-house development indicates NASA personnel or a contractor builds the hardware at a NASA site. A subcontract development is completed off-site by a commercial company. A COTS item is a vendor product available by ordering a specific part number. The team evaluates the pros and cons of each development path. For example, in-bouse developments utilize existing corporate knowledge regarding bow to build equipment for use in space. However, technical expertise would be required to fully understand the medical equipment capabilities, such as for an ultrasound system. It may require additional time and funding to gain the expertise that commercially exists. The major benefit of subcontracting a hardware development is the product is delivered as an end-item and commercial expertise is utilized. On the other hand, NASA has limited control over schedule delays. The final option of COTS or modified COTS equipment is a compromise between in-house and subcontracts. A vendor product may exist that meets all functional requirements but req uires in-house modifications for successful operation in a space environment. The HRF utilizes equipment developed using all of the paths described: inhouse, subcontract, and modified COTS.

Bauer, Liz↗

DOE OSTI2021

\( \mathcal{N} \) = 4 supersymmetric Yang-Mills thermodynamics to order λ 2

We calculate the resummed perturbative free energy of \( \mathcal{N} \) = 4 supersymmetric Yang-Mills in four spacetime dimensions (SYM 4 , 4 ) through second order in the ’t Hooft coupling λ at finite temperature and zero chemical potential. Our final result is ultraviolet finite and all infrared divergences generated at three-loop level are canceled by summing over SYM 4 , 4 ring diagrams. Non-analytic terms at \( \mathcal{O} \) ( λ 3 / 2 ) and \( \mathcal{O} \) ( λ 2 log λ ) are generated by dressing the A 0 and scalar propagators. The gauge-field Debye mass m D and the scalar thermal mass M D are determined from their corresponding finite-temperature self-energies. Based on this, we obtain the three-loop thermodynamic functions of SYM 4 , 4 to \( \mathcal{O} \) ( λ 2 ). We compare our final result with prior results obtained in the weak- and strong-coupling limits and construct a generalized Padé approximant that interpolates between the weak-coupling result and the large- N c strong-coupling result. Our results suggest that the \( \mathcal{O} \) ( λ 2 ) weak-coupling result for the scaled entropy density is a quantitatively reliable approximation to the scaled entropy density for 0 ≤ λ ≲ 2.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Constraining Galaxy-Halo connection using machine learning

We investigate the potential of machine learning (ML) methods to model small-scale galaxy clustering for constraining Halo Occupation Distribution (HOD) parameters. Our analysis reveals that while many ML algorithms report good statistical fits, they often yield likelihood contours that are significantly biased in both mean values and variances relative to the true model parameters. This highlights the importance of careful data processing and algorithm selection in ML applications for galaxy clustering, as even seemingly robust methods can lead to biased results if not applied correctly. ML tools offer a promising approach to exploring the HOD parameter space with significantly reduced computational costs compared to traditional brute-force methods if their robustness is established. Using our ANN-based pipeline, we successfully recreate some standard results from recent literature. Properly restricting the HOD parameter space, transforming the training data, and carefully selecting ML algorithms are essential for achieving unbiased and robust predictions. Among the methods tested, artificial neural networks (ANNs) outperform random forests (RF) and ridge regression in predicting clustering statistics, when the HOD prior space is appropriately restricted. We demonstrate these findings using the projected two-point correlation function (w p (r p )), angular multipoles of the correlation function (ξ ℓ (r)), and the void probability function (VPF) of Luminous Red Galaxies from Dark Energy Spectroscopic Instrument mocks. Our results show that while combining w p (r p ) and VPF improves parameter constraints, adding the multipoles ξ 0 , ξ 2 , and ξ 4 to w p (r p ) does not significantly improve the constraints.

cosmology↗

DOE OSTI2024

Anisotropic physics-regularized interpretable machine learning of microstructure evolution

Anisotropic Physics-Regularized Interpretable Machine Learning Microstructure Evolution (APRIMME) is a general-purpose machine learning solution for grain growth simulations. In prior work, PRIMME employed a deep neural network to predict site-specific migration as a function of its neighboring sites to model normal, isotropic, grain growth behavior. This work aims to extend this method by incorporating grain boundary misorientation-based grain growth behavior. APRIMME is trained on anisotropic simulations created using the Monte Carlo-Potts (MCP) model. Furthermore, the results of this work are compared statistically using grain radius, number of sides per grain, mean neighborhood misorientations, and the standard deviation of triple junction dihedral angles, and are found to match in most cases. The exceptions are small and seem to be related to two causes: (1) the deterministic model of APRIMME is learning from the stochastic simulations of MCP, which seems to accentuate triple junction behaviors; and, (2) a bias against very small grains is made evident in a quicker decrease in grains than expected at the beginning of an APRIMME simulation. APRIMME is also evaluated for its general ability to capture anisotropic grain growth behavior by first investigating different test case initial conditions, including a circle grain, three grain, and hexagonal grain microstructures.

36 MATERIALS SCIENCE↗

DOE OSTI2024

In Situ Monitoring the Nucleation and Growth of Nanoscale CaCO 3 at the Oil–Water Interface

Interfaces can actively control the nucleation kinetics, orientations, and polymorphs of calcium carbonate (CaCO 3 ). Prior studies have revealed that CaCO 3 formation can be affected by the interplay between chemical functional moieties on solid–liquid or air–liquid interfaces as well as CaCO 3 ’s precursors and facets. Yet little is known about the roles of a liquid–liquid interface, specifically an oil–liquid interface, in directing CaCO 3 mineralization which are common in natural and engineered systems. Here, in this study, by using in situ X-ray scattering techniques to locate a meniscus formed between water and a representative oil, isooctane, we successfully monitored CaCO 3 formation at the pliable isooctane–water interface and systematically investigated the pivotal roles of the interface in the formation of CaCO 3 (i.e., particle size, its spatial distribution with respect to the interface, and its mineral phase). Different from bulk solution, ∼5 nm CaCO 3 nanoparticles form at the isooctane–water interface. They stably exist for a long time (36 h), which can result from interface-stabilized dehydrated prenucleation clusters of CaCO 3 . There is a clear tendency for enhanced amounts and faster crystallization of CaCO 3 at locations closer to isooctane, which is attributed to a higher pH and an easier dehydration environment created by the interface and oil. Our study provides insights into CaCO 3 nucleation at an oil–water interface, which can deepen our understanding of pliable interfaces interacting with CaCO 3 and benefit mineral scaling control during energy-related subsurface operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Shock-reshock of zirconium to explore the effect of microstructure on the alpha-omega phase transformation

Phase transformations play an important role in the mechanical behavior of materials subjected to extreme loading conditions. A series of shock-reshock experiments were fielded to determine whether the phase transitions in materials are significantly enhanced or inhibited by preexisting microstructural features. Polycrystalline zirconium samples were shock loaded using gas-gun plate impact and soft recovered to examine microstructure using electron backscatter diffraction (EBSD). Drive conditions were varied to study the (hcp) alpha to (hexagonal) omega solidsolid phase transformation. Recovered samples were then subjected to a second shock loading event to determine the change in material behavior as a function of pre-shock microstructure. Crystallography of phase fragments in the final microstructure showed that prior twinning (formed during the shock to a peak stress below the transition threshold) appeared to suppress omega formation/retention after reshock. Conversely, when a material was initially shocked into the omega phase field, retained-omega was not found to have a large impact on subsequent omega formation during reshock. This suggests that nucleation and growth of omega phase are important processes, and the relative activity of nucleation vs. growth processes is modified by a pre-existing substructure. Additionally, orientation relationships reveal a reverse transformation pathway (omega to alpha) dominates the final microstructure, suggesting significant grain growth in the omega phase field is possible even for dynamic timescales.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Information transfer as a framework for optimized phase imaging

In order to efficiently image a non-absorbing sample (a phase object), dedicated phase contrast optics are required. Typically, these optics are designed with the assumption that the sample is weakly scattering, implying a linear relation between a sample’s phase and its transmission function. In the strongly scattering, nonlinear case, the standard optics are ineffective, and the transfer functions used to characterize them are uninformative. We use the Fisher information (FI) to assess the efficiency of various phase imaging schemes and to calculate an information transfer function (ITF). We show that a generalized version of Zernike phase contrast is efficient given sufficient prior knowledge of the sample. We show that with no prior knowledge, a random sensing measurement yields a significant fraction of the available information. Finally, we introduce a generalized approach to common path interferometry that can be optimized to prioritize sensitivity to particular sample features. Each of these measurements can be performed using Fourier lenses and phase masks.

Koppell, Stewart↗

NASA NTRS1975

IUS/TUG orbital operations and mission support study. Volume 3: Space tug operations

A study was conducted to develop space tug operational concepts and baseline operations plan, and to provide cost estimates for space tug operations. Background data and study results are presented along with a transition phase analysis (the transition from interim upper state to tug operations). A summary is given of the tug operational and interface requirements with emphasis on the on-orbit checkout requirements, external interface operational requirements, safety requirements, and system operational interface requirements. Other topics discussed include reference missions baselined for the tug and details for the mission functional flows and timelines derived for the tug mission, tug subsystems, tug on-orbit operations prior to the tug first burn, spacecraft deployment and retrieval by the tug, operations centers, mission planning, potential problem areas, and cost data.

Source record↗

NASA NTRS1975

The Pioneer Projects - Economical exploration of the solar system

The interplanetary Pioneer missions are reviewed in terms of management implications and cost control. The responsibilities, organizational structure, and management practices of the Pioneer Projects are presented. The lines of authority and areas of responsibility of the principal organizational elements supporting the Pioneer missions are identified, and the methods employed for maintaining effective and timely interactions among these elements are indicated. The technical and administrative functions of various organizational elements of the project are described. The management and control of activities prior to and during the hardware procurement phase are described to indicate the basis for obtaining visibility of the technical progress, utilization of resources, and cost performance of the contractors and other institutions supporting the Pioneer projects.

Spahr, J. R.↗

NASA NTRS1977

Navigating the Viking landers

On July 20, 1976, Viking Lander 1 became the first unmanned spacecraft to land and operate successfully on the planet Mars. This was followed by a second successful landing on September 3, 1976. This paper gives a detailed description of the autonomous on-board navigation process to perform the guidance, control, and entry navigation functions. Also, the functions performed on the ground to generate and validate the guidance commands sent to the spacecraft prior to descent are described. In-flight measures of navigation system performance are compared against a-priori error estimates to show that the descents were completely nominal in all respects. The final landing errors were 25 km and 10 km for Missions 1 and 2, respectively.

Euler, E. A.↗

NASA NTRS2003

Reliability Sensitivity Analysis and Design Optimization of Composite Structures Based on Response Surface Methodology

This report discusses the development and application of two alternative strategies in the form of global and sequential local response surface (RS) techniques for the solution of reliability-based optimization (RBO) problems. The problem of a thin-walled composite circular cylinder under axial buckling instability is used as a demonstrative example. In this case, the global technique uses a single second-order RS model to estimate the axial buckling load over the entire feasible design space (FDS) whereas the local technique uses multiple first-order RS models with each applied to a small subregion of FDS. Alternative methods for the calculation of unknown coefficients in each RS model are explored prior to the solution of the optimization problem. The example RBO problem is formulated as a function of 23 uncorrelated random variables that include material properties, thickness and orientation angle of each ply, cylinder diameter and length, as well as the applied load. The mean values of the 8 ply thicknesses are treated as independent design variables. While the coefficients of variation of all random variables are held fixed, the standard deviations of ply thicknesses can vary during the optimization process as a result of changes in the design variables. The structural reliability analysis is based on the first-order reliability method with reliability index treated as the design constraint. In addition to the probabilistic sensitivity analysis of reliability index, the results of the RBO problem are presented for different combinations of cylinder length and diameter and laminate ply patterns. The two strategies are found to produce similar results in terms of accuracy with the sequential local RS technique having a considerably better computational efficiency.

Rais-Rohani, Masoud↗

NASA NTRS2006

Equipment for On-Wafer Testing From 220 to 325 GHz

A system of electronic instrumentation, constituting the equivalent of a two-port vector network analyzer, has been developed for use in on-wafer measurement of key electrical characteristics of semiconductor devices at frequencies from 220 to 325 GHz. A prior system designed according to similar principles was reported in Equipment for On-Wafer Testing at Frequencies Up to 220 GHz (NPO-20760), NASA Tech Briefs, Vol. 25, No. 11 (November 2001), page 42. As one would expect, a major source of difficulty in progressing to the present higher-frequency-range system was the need for greater mechanical precision as wavelengths shorten into the millimeter range, approaching the scale of mechanical tolerances of prior systems. The system (see figure) includes both commercial off-the-shelf and custom equipment. As in the system of the cited prior article, the equipment includes test sets that are extended versions of commercial network analyzers that function in a lower frequency range. The extension to the higher frequency range is accomplished by use of custom frequency-extension modules that contain frequency multipliers and harmonic mixers. On-wafer measurement is made possible by waveguide wafer probes that were custom designed and built for this wavelength range, plus an on-wafer calibration substrate designed for use with these probes. In this case, the calibration substrate was specially fabricated by laser milling. The system was used to make the first on-wafer measurements of a semiconductor device in the frequency range from 220 to 320 GHz. Some of the measurement results showed that the device had gain.

Samoska, Lorene↗