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NASA NTRS2012

Low-Cost, Rugged High-Vacuum System

A need exists for miniaturized, rugged, low-cost high-vacuum systems. Recent advances in sensor technology have led to the development of very small mass spectrometer detectors as well as other analytical instruments such as scanning electron microscopes. However, the vacuum systems to support these sensors remain large, heavy, and power-hungry. To meet this need, a miniaturized vacuum system was developed based on a very small, rugged, and inexpensive-to-manufacture molecular drag pump (MDP). The MDP is enabled by a miniature, very-high-speed (200,000 rpm), rugged, low-power, brushless DC motor optimized for wide temperature operation and long life. The key advantages of the pump are reduced cost and improved ruggedness compared to other mechanical hig-hvacuum pumps. The machining of the rotor and stators is very simple compared to that necessary to fabricate rotor and stator blades for other pump designs. Also, the symmetry of the rotor is such that dynamic balancing of the rotor will likely not be necessary. Finally, the number of parts in the unit is cut by nearly a factor of three over competing designs. The new pump forms the heart of a complete vacuum system optimized to support analytical instruments in terrestrial applications and on spacecraft and planetary landers. The MDP achieves high vacuum coupled to a ruggedized diaphragm rough pump. Instead of the relatively complicated rotor and stator blades used in turbomolecular pumps, the rotor in the MDP consists of a simple, smooth cylinder of aluminum. This will turn at approximately 200,000 rpm inside an outer stator housing. The pump stator comprises a cylindrical aluminum housing with one or more specially designed grooves that serve as flow channels. To minimize the length of the pump, the gas is forced down the flow channels of the outer stator to the base of the pump. The gas is then turned and pulled toward the top through a second set of channels cut into an inner stator housing that surrounds the motor. The compressed gas then flows down channels in the motor housing to the exhaust port of the pump. The exhaust port of the pump is connected to a commercially available diaphragm or scroll pump.

Sorensen, Paul↗

NASA NTRS1996

Parallel Simulation of Unsteady Turbulent Flames

Time-accurate simulation of turbulent flames in high Reynolds number flows is a challenging task since both fluid dynamics and combustion must be modeled accurately. To numerically simulate this phenomenon, very large computer resources (both time and memory) are required. Although current vector supercomputers are capable of providing adequate resources for simulations of this nature, the high cost and their limited availability, makes practical use of such machines less than satisfactory. At the same time, the explicit time integration algorithms used in unsteady flow simulations often possess a very high degree of parallelism, making them very amenable to efficient implementation on large-scale parallel computers. Under these circumstances, distributed memory parallel computers offer an excellent near-term solution for greatly increased computational speed and memory, at a cost that may render the unsteady simulations of the type discussed above more feasible and affordable.This paper discusses the study of unsteady turbulent flames using a simulation algorithm that is capable of retaining high parallel efficiency on distributed memory parallel architectures. Numerical studies are carried out using large-eddy simulation (LES). In LES, the scales larger than the grid are computed using a time- and space-accurate scheme, while the unresolved small scales are modeled using eddy viscosity based subgrid models. This is acceptable for the moment/energy closure since the small scales primarily provide a dissipative mechanism for the energy transferred from the large scales. However, for combustion to occur, the species must first undergo mixing at the small scales and then come into molecular contact. Therefore, global models cannot be used. Recently, a new model for turbulent combustion was developed, in which the combustion is modeled, within the subgrid (small-scales) using a methodology that simulates the mixing and the molecular transport and the chemical kinetics within each LES grid cell. Finite-rate kinetics can be included without any closure and this approach actually provides a means to predict the turbulent rates and the turbulent flame speed. The subgrid combustion model requires resolution of the local time scales associated with small-scale mixing, molecular diffusion and chemical kinetics and, therefore, within each grid cell, a significant amount of computations must be carried out before the large-scale (LES resolved) effects are incorporated. Therefore, this approach is uniquely suited for parallel processing and has been implemented on various systems such as: Intel Paragon, IBM SP-2, Cray T3D and SGI Power Challenge (PC) using the system independent Message Passing Interface (MPI) compiler. In this paper, timing data on these machines is reported along with some characteristic results.

Menon, Suresh↗

NASA NTRS2020

Disruptive Technologies and Their Putative Impacts Upon Society and Aerospace- Entering The Virtual Age

Developments in technology over the recent decades have been extraordinary. They include the IT, bio, nano, and now quantum and energetics technology arenas and their many combinatorial interactions and impacts. In the main, these are at the frontiers of the small and in a combinational, synergistic feeding frenzy with each other. They fall under the broad category of Disruptive Technologies and have greatly altered society. The outlook for the runout of these and other technology developments augers mid-term to later alterations in components of the human existence theorem, including the requirement to work for our living and our physiological makeup and longevity (Ref 1). The IT revolution began in the 1950s with the development of solid-state electronics. The biologics revolution began later in the 1960s and 1970s with DNA and genomics, and the nano revolution in the 1990s with self-forming nano systems and carbon nanotubes. Quantum technology is now developing rapidly, aided by enabling nano systems, and the energetics revolution is providing ever more efficient and less expensive renewable energy sources. The IT revolution has produced improvements of an astounding eleven orders of magnitude in computing speed since the late 1950s. As we shift from silicon to biological, optical, nano, molecular, and atomic computing, improvements of some 4 orders of magnitude are evidently possible from either optical or DNA computing [Refs 2and 3], then there are combinatorials. Then there is quantum computing, under development worldwide for an increasing number of applications and proffering phenomenal capabilities. The current fastest computers are considerably beyond human brain speed. Machine intelligence is developing well after decades of inadequate machine capability, now no longer the case, and a detour into expert systems. Researchers in machine intelligence are now pursuing deep learning approaches using neural nets, which are proving to be extremely useful. Some believe the frontier of potential human-level machine intelligence may be found in biomimetics and brain-emulation approaches. There is even a possibility of “emergence”—i.e., when the machine intelligence is complex enough that it “wakes up,” as when human intelligence emerged via evolution during the million-plus years of the hunter-gatherer epoch [ Ref 4]. In fact, some posit that human intelligence can be improved upon and is only a cul-de-sac of what is conceivable. The IT revolution has produced massive changes in human society and economics—from the Internet, enabling the rapid expansion of knowledgeability (and even what is knowable), to an increasingly pervasive trend of “tele-everything.” The extraordinary compilation, storage, and availability of truly massive amounts of information could, when combined with AI and under the mantra of “big data,” greatly improve many of our technical and commercial processes and their content including elucidating new heuristic governing laws.

Dennis M. Bushnell↗

NASA NTRSDate not supplied

Squeezing Every Last 'Bit' of Information from Enceladus Mass Spectrometry

Potential opportunities to return to Enceladus in Discovery and Flagship class missions inspire development of next-generation instruments and creative approaches to sample collection, sample analysis, and data analysis and transmission strategies. Mass spectrometers (MS) are ideally suited to future Enceladus missions due to their analytical power in identifying a range of molecular and ionic compositions – including complex organics – and potentially astrobiologically-important features such as isotope ratios, chirality, and enantiomeric excess. However, long communication delays from Enceladus and limited bandwidth limits the data transmission from these higher-data-volume instruments, likely delaying mission-related response to new data. We explore the utility of data science and machine learning (ML) on isotope ratio (IR)MS data collected from laboratory analogs of Enceladus to: 1) process data quickly for rapid ground-based analyses, 2) understand if compositional and biosignature information could be extracted from IRMS data, and 3) evaluate whether onboard ML techniques could improve sample analysis, cadence, and transmission prioritization. Laboratory analogs analyzed isotopes of volatile CO2 that interacted with seawaters of varying composition, and include both abiotic and biotic (microbially-influenced) experiments. Enceladus’s alkaline oceans promote speciation of carbon into multiple forms (e.g., H2CO3 / CO2, HCO3-, and CO32-), each of which could be isotopically fractionated by abiotic or biotic reactions. Large (>2‰) changes in carbon isotopes (δ13C) are observed from some biotic experiments inoculated with complex microbial ecosystems relative to the abiotic seawaters. ML training and classification suggests that microbial samples can be distinguished from abiotic samples, yet that a broad range of microbial experiments are necessary to train ML models to cover a range of complexities including disequilibria, and isotopic and compositional fractionation.

geochemistry↗

NASA NTRS1999

Protein machines and self assembly in muscle organization

The remarkable order of striated muscle is the result of a complex series of protein interactions at different levels of organization. Within muscle, the thick filament and its major protein myosin are classical examples of functioning protein machines. Our understanding of the structure and assembly of thick filaments and their organization into the regular arrays of the A-band has recently been enhanced by the application of biochemical, genetic, and structural approaches. Detailed studies of the thick filament backbone have shown that the myosins are organized into a tubular structure. Additional protein machines and specific myosin rod sequences have been identified that play significant roles in thick filament structure, assembly, and organization. These include intrinsic filament components, cross-linking molecules of the M-band and constituents of the membrane-cytoskeleton system. Muscle organization is directed by the multistep actions of protein machines that take advantage of well-established self-assembly relationships. Copyright 1999 John Wiley & Sons, Inc.

NASA Discipline Musculoskeletal↗

NASA NTRS1991

A parallel vectorized implementation of triple excitations in CCSD(T) - Application to the binding energies of the AlH3, AlH2F, AlHF2 and AlF3 dimers

An efficient method for various noniterative estimates of connected triple excitations in coupled-cluster theory is outlined and related to a similar expression occurring in Moller-Plesset perturbation theory. The method is highly vectorized and capable of utilizing multiple processors on a shared-memory machine, leading to computational rates in excess of one billion floating-point operations per second on four processors of a CRAY Y-MP. Using the new procedure, the binding energies of the D(2h) diborane-type dimers of AlH3, AlH2F, AlHF2, and AlF3 have been determined to be 32, 40, 20, and 47 kcal/mol, respectively. For Al2F6, the correlation procedure includes 232 molecular orbitals and over 1.5 x 10 to the 6th single and double coupled-cluster amplitudes, effectively accounting for over 2 x 10 to the 9th connected triple excitations.

Rendell, Alistair P.↗

NASA NTRSDate not supplied

Statistical Classification of Biosignature Information: Combining Elemental, Molecular, Reflectance, and Raman Data to Increase Life Detection Confidence

Planetary exploration missions seeking past or present signs of life carry not just a single instrument, but a suite. There is a need to study how these multiple data types can be combined to create “composite” biosignatures [1]. Algorithmic methods using existing data on living and non-living systems, though limited by the n = 1 of Earth, can nonetheless be informative. We assembled a database of 1277 measurements spanning 16 representative systems either indicative or non-indicative of life. Five classification (machine learning) methods were used on each individual data type, then on the entire set. This abstract summarizes the results; the data is described in more detail in [2], and methods in [3].

Biosignatures↗

NASA NTRS2003

Effect of Molding and Machining on Neoflon CTFE M400H Polychlorotrifluoroethylene Rod Stock and Valve Seat Properties

Since 1997 numerous fires have been reported to the Food and Drug Administration involving cylinder valves installed on medical use oxygen cylinders sold and operated within the United States. All of the cylinder valves in question had polychlorotrifluoroethylene (PCTFE) valve seats. Subsequent failure analysis showed that the main seat was the primary source of ignition. A review of the incidents involving cylinder valve fires indicated three possible ignition mechanisms: contaminant promotion, flow friction, and resonance. However, gas purity analysis showed that uncombusted, residual oxygen was within specification. Infrared and energy dispersive spectroscopy further showed that no contaminants or organic compounds were present in the remaining, uncombusted valve seat material or on seat plug surfaces. Therefore, contaminant-promoted ignition did not appear to be responsible for the failures. Observations of extruded material along the outer edge of the coined or loaded seat area produced by cylinder overuse or poppet overload led to concerns that accelerated gas flow across a deformed seat surface could generate enough localized heating to ignite the polymeric seat. Low molecular weight or highly amorphous quick-quenched PCTFE grades might be expected to be especially prone to this type of deformation. Such a failure mechanism has been described as flow friction; however, the corresponding mechanistic parameters are poorly understood. Subsequent revelation of low-temperature dimensional instability by thermomechanical analysis (TMA) in a variety of PCTFE sheet and rod stock samples led to new concerns that PCTFE valve seats could undergo excessive expansion or contraction during service. During expansion, additional extrusion and accompanying flow friction could occur. During contraction, a gap between the seal and adjacent metal surfaces could form. Gas flowing past the gap could, in turn, lead to resonance heating and subsequent ignition as described in ASTM Guide for Evaluation Nonmetallic Materials for Oxygen Service (G 63). Attempts to uncover the origins of the observed dimensional instability were hindered by uncertainties about resin grade, process history, and post-process heat history introduced by machining, annealing, and sample preparation. An approach was therefore taken to monitor property changes before and after processing and machining using a single, well-characterized lot of Neoflon CTFE.1 M400H resin. A task group consisting of the current PCTFE resin supplier, two molders, and four valve seat manufacturers was formed, and phased testing on raw resin, intermediate rod stock, and finished valve seats initiated. The effect of processing and machining on the properties of PCTFE rod stock and oxygen gas cylinder valve seats was then determined. Testing focused on two types of extruded rod stock and one type of compression-molded rod stock. To accommodate valve seat manufacturer preferences for certain rod stock diameters, two representative diameters were used (4.8 mm (0.1875 in.) and 19.1 mm (0.75 in.)). To encompass a variety of possible sealing configurations, seven different valve seat types with unique geometries or machining histories were tested. The properties investigated were dimensional stability as determined by TMA, specific gravity, differential scanning calorimetry (DSC), compressive strength, zero strength time, and intrinsic viscosity. Findings are discussed in the context of polymer structure-process-property relationships whenever possible.

Waller, Jess M.↗

NASA NTRSDate not supplied

Genomics Study of Effect of Redox-Active Metalloporphyrin on Murine Retina During Spaceflight

Astronauts returning from spaceflight have experienced eye problems, which may decrease retinal performance and lead to long-term effects on visual acuity. This study leverages the collected data from spaceflown murine retinas that were treated with redox-active metalloporphyrin (BuOE) to mitigate spaceflight-induced changes. 10-week-old adult C57BL/6 male mice (n=5 in each of BuOE treated and saline control groups) were flown on Space-X 24 to the ISS national lab, kept in low earth orbit for 35 days and returned to Earth alive. Our analysis of RNA-sequencing data generated from subsequent murine retina tissues uncovered genes, pathways, and epigenetic modifications consistent with therapeutic potential of BuOE. For spaceflown murine samples, the treatment group show differentially expressed genes relative to saline controls that reached significance (adjusted p-value < 0.05) and included genes Gpx3 and Crhbp, which are related to protection against cell oxidative damage and cellular response to organonitrogen compounds. Ranked fold-changes from the same contrast were used for gene set enrichment analysis, which showed biological processes reaching significance (adjusted p-value < 0.05) including glutathione metabolic processes and cellular response to xenobiotic stimulus. The findings from this investigation have the potential to provide valuable insights into the molecular mechanisms underlying conditions like spaceflight associated neuro-ocular syndrome and assess the effectiveness of BuOE as a countermeasure for astronauts experiencing neuro-ophthalmic abnormalities, which can lead to long-term effects on visual acuity.

Machine Learning↗

NASA NTRSDate not supplied

Genomics Study of Effect of Redox-Active Metalloporphyrin on Murine Retina During Spaceflight

Machine Learning↗

NASA NTRS1996

Computing Fluxes Of Molecules On And Near A Spacecraft

Molecular Flux (MOLFLUX) computer code is versatile program used to compute following conditions on and near spacecraft: fluxes of molecules to, and deposition of molecules on, surfaces; densities and column densities of molecules in surrounding space, and return fluxes of molecules to surfaces caused by both collisions of molecules with ambient atmosphere and by self-scattering. User has option to modify spacecraft configurations and sources of contamination and to choose which critical surfaces to examine. Written in FORTRAN and C language. Three machine versions available: VAX version (MSC-22260), HP version (MSC-22565), and Cray version (MSC-22566).

Ehlers, H. K.↗

NASA NTRS2019

TPSAS-NF1676L-32345-DND

Interest in the use of Raman spectrometers has seen an increase in the fields of geology and planetary sciences due to the non-destructive insight Raman spectra may provide into the molecular makeup of a given sample. Advancements in Raman spectrometer hardware have allowed for compact instruments to have deployment capabilities directly on interplanetary missions, flexible usage conditions requiring no sample collection/preparation, and no need for daylight radiation shielding. As the amount of science which can be collected from a Raman spectrometer in a given amount of time increases, a bottleneck will be created in data analysis which leaves a need for a faster method of spectral data classification. Recent studies have shown that machine learning models are able to solve this problem by achieving high-accuracy classification. Liu et al4 found the convolutional neural network (CNN) held the highest classification accuracy (96% top 5) for single sample Raman data.

A Atkinson↗

NASA NTRS2022

A Census of Young Stellar Objects in Two Line-of-Sight Star-Forming Regions Toward IRAS 22147+5948 in the Outer Galaxy

Context. Star formation in the outer Galaxy, namely, outside of the Solar circle, has not been extensively studied in part due to the low CO brightness of the molecular clouds linked with the negative metallicity gradient. Recent infrared surveys provide an overview of dust emission in large sections of the Galaxy, but they suffer from cloud confusion and poor spatial resolution at far-infrared wavelengths. Aims. We aim to develop a methodology to identify and classify young stellar objects (YSOs) in star-forming regions in the outer Galaxy and use it to resolve a long-standing disparity in terms of the distance and evolutionary status of IRAS 22147+5948. Methods. We used a support vector machine learning algorithm to complement standard color–color and color–magnitude diagrams in our search for YSOs in the IRAS 22147 region, based on publicly available data from the Spitzer Mapping of the Outer Galaxy survey. The agglomerative hierarchical clustering algorithm was used to identify clusters. Then the physical properties of individual YSOs were calculated. The distances were determined using CO 1–0 from the Five College Radio Astronomy Observatory survey. Results. We identified 13 Class I and 13 Class II YSO candidates using the color–color diagrams, along with an additional 2 and 21 sources, respectively, using the applied machine learning techniques. The spectral energy distributions of 23 sources were modeled with a star and a passive disk, corresponding to Class II objects. The models of three sources include envelopes that are typical for Class I objects. The objects were grouped into two clusters located at a distance of 2:2 kpc and 5 clusters at 5:6 kpc. The spatial extent of CO, radio continuum, and dust emission confirms the origin of YSOs in two distinct star-forming regions along a similar line of sight. Conclusions. The outer Galaxy may serve as a unique laboratory for exploring star formation across environments, on the condition that complementary methods and ancillary data are used to properly account for cloud confusion and distance uncertainties.

Agata Karska↗

NASA NTRS1998

A Very High Resolution Mid Infrared Spectrograph for SOFIA

The purpose of this project was to study the design of a high resolution mid-infrared spectrograph for the SOFIA airborne observatory. The primary motivation for the construction and use of such an instrument is the study of vibrational transitions of molecules in molecular clouds, circumstellar inflows and outflows, and planetary atmospheres, which are blocked from ground-based observations by absorption by the Earth's atmosphere. The instrument design studied is a cross-dispersed grating spectrograph with several modes of operation giving spectral resolving powers of approximately 4000, 20,000, and 100,000. In the two lower resolution modes a single grating is used in a long-slit spectrograph. At high resolution that grating serves as the cross-disperser for a 1-m long echelon, a very coarsely and steeply ruled grating, diamond-machined in aluminum. Several design study tasks were carried out: 1. An optical and mechanical design was developed. It differed from the preliminary design by using a reflecting focal reducer in the fore-optics and by rearranging the echelon and cross-dispersing chambers to improve the efficiency of the long-slit modes. 2. A finite-element analysis of the dewar and echelon support structures was done. It led us to change the echelon support to improve its rigidity. 3. Further information was obtained which convinced us that Hyperfine Inc. was capable of diamond-machining the echelon. 4. Several possible vendors of readout electronics and software were identified. It was decided that it is more cost-effective to purchase these items rather than developing them ourselves. 5. Observing and calibration procedures were studied. we did not identify significant changes needed from procedures used previously. 6. Possible expansions of instrument capabilities, including wavelength coverage, were studied. It appears unlikely that the echelon will perform well at wavelengths shortward of 5 microns, but the spectral coverage could be extended longward of 28 microns with the use of an Si:Sb detector. No patentable inventions were made during this study. Based on this design study, a proposal was submitted to construct the instrument. It was chosen as one of the first-light instruments for SOFIA.

Lacy, John H.↗

NASA NTRS1943

A Method for Removal of Bakelite-Impregnated Wire Strain Gages

An increasing interest is being shown in the use of wire-type strain gages to measure static and dynamic stresses in aircraft-engine parts. Bakelite cement has been found satisfactory as a bonding agent for attaching the strain gages to machine parts that must operate at elevated temperatures. On many occasions, it is desired to remove Bakelite-cemented gages from the test parts for the purpose of replacing faulty gages or of returning the parts to service after strain measurements have been completed. Removal of the gages by means of scraping without prior treatment is very unsatisfactory because it is tedious and almost invariably damages the finished surface. Various solvents have been tried, but all attempts in this direction have been unsuccessful inasmuch as Bakelite cement, when properly baked, forms a polymer of very high molecular weight that resists the action of solvents. This report presents a gas-flame method of removal that is rapid and does not inure the structural part.

Kemp, Richard H.↗

NASA NTRS1995

Fast Multipole Methods for Three-Dimensional N-body Problems

We are developing computational tools for the simulations of three-dimensional flows past bodies undergoing arbitrary motions. High resolution viscous vortex methods have been developed that allow for extended simulations of two-dimensional configurations such as vortex generators. Our objective is to extend this methodology to three dimensions and develop a robust computational scheme for the simulation of such flows. A fundamental issue in the use of vortex methods is the ability of employing efficiently large numbers of computational elements to resolve the large range of scales that exist in complex flows. The traditional cost of the method scales as Omicron (N(sup 2)) as the N computational elements/particles induce velocities at each other, making the method unacceptable for simulations involving more than a few tens of thousands of particles. In the last decade fast methods have been developed that have operation counts of Omicron (N log N) or Omicron (N) (referred to as BH and GR respectively) depending on the details of the algorithm. These methods are based on the observation that the effect of a cluster of particles at a certain distance may be approximated by a finite series expansion. In order to exploit this observation we need to decompose the element population spatially into clusters of particles and build a hierarchy of clusters (a tree data structure) - smaller neighboring clusters combine to form a cluster of the next size up in the hierarchy and so on. This hierarchy of clusters allows one to determine efficiently when the approximation is valid. This algorithm is an N-body solver that appears in many fields of engineering and science. Some examples of its diverse use are in astrophysics, molecular dynamics, micro-magnetics, boundary element simulations of electromagnetic problems, and computer animation. More recently these N-body solvers have been implemented and applied in simulations involving vortex methods. Koumoutsakos and Leonard (1995) implemented the GR scheme in two dimensions for vector computer architectures allowing for simulations of bluff body flows using millions of particles. Winckelmans presented three-dimensional, viscous simulations of interacting vortex rings, using vortons and an implementation of a BH scheme for parallel computer architectures. Bhatt presented a vortex filament method to perform inviscid vortex ring interactions, with an alternative implementation of a BH scheme for a Connection Machine parallel computer architecture.

Koumoutsakos, P.↗

NASA NTRS2021

Predicting the Functional State of Protein Kinases Using Interpretable Graph Neural Networks

Kinases are a family of proteins that function as molecular switches, regulating several essential cellular activities such as cell proliferation. Dysfunctional kinases are implicated in several types of cancers and hence they are actively pursued as drug targets. Given the vast number of complex kinase structures that are available in the protein data bank (PDB), there is a necessity to develop methodologies that can identify structurally important moieties of the kinases in an automated fashion, for such techniques can be instrumental in identifying novel drug targets. In this work, we develop a graph neural network (GNN) based deep learning framework for classifying the functionally active and inactive states of a large set of eukaryotic protein kinases, making use of their 3D structure from the PDB. We show that GNN based machine learning models can classify protein states with an accuracy greater than 97%. We further use the GNN models to automatically identify regions of the kinases that are important for its function. For this purpose, Gradient-weighted Class Activation Mapping (Grad-CAM) was implemented on the protein graphs. Remarkably, Grad-CAM consistently identifies the highly conserved DFG motif as the most important part of the protein across the entire kinome, without any prior input. Other regions of the hydrophobic core such as the HRD motif were also identified by the interpretable GNN framework, consistent with the literature. We discuss the significance of each of these regions in detail.

Ashwin Ravichandran↗

NASA NTRS1987

Effects of substrate misorientation and background impurities on electron transport in molecular-beam-epitaxial grown GaAs/AlGaAs modulation-doped quantum-well structures

The effects of substrate misorientation off the (001) plane and of background impurities on electron transport in MBE-grown GaAs/AlGaAs modulation-doped superlattice-buffered quantum-well structures were investigated. Low-field transport data were obtained on GaAs/AlGaAs structures grown on substrates oriented 0, 2, 4, and 6.5 deg off the (001) plane towards either (111)A or (111)B. It is shown that the low-field two-dimensional electron gas (2DEG) mobility is a function of the angle and direction of the substrate orientation, and that the 2DEG mobility is a function of the direction of the applied electric field in the GaAs quantum well. The anisotropy in the 2DEG mobility is also a function of the tilt angle and tilt azimuth direction of the substrate from the (001) plane. In addition, it is shown that the amount of interface scattering from the inverted interface is a sensitive function of the amount of background impurities in the MBE machine.

Radulescu, D. C.↗