Search NASA⌕ Search

SEARCH · Search NASA

Results for “highly selective”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Dopant Sensitive Electrolytic Etching of Germanium with High Selectivity

Abstract The enhanced charge carrier mobility and photon absorption compared to silicon make germanium attractive for next-generation photo diodes. However, the complex oxidation behavior of germanium challenges dopant-dependent selective etching that is desired for the fabrication of backside imaging architectures. This report demonstrates electrolytic wet etching of p-doped germanium which proceeds up to 17,500x faster than etching of intrinsic germanium. Homoepitaxially grown layers of germanium were electrolytically etched in potassium hydroxide over a range of biases. Intermittent acquisition of cyclic voltammetry spectra during etching has suppressed the formation of electric double layers, maintained appreciable etch rates, and allowed for in operando process control. The observed etch rates scaled with dopant concentration. An effective etch rate of germanium removal of 2.100±0.044 µm/min was accomplished for a boron dopant concentration of 6E18cm-3. For nominally intrinsic germanium, however, an effective etch rate of only 0.00012±0.00011 µm/min was observed. A series of systematic electrolytic etch experiments have revealed the transfer of 4 electrons per germanium atom removed.

Wood, Joseph G.↗
DOE OSTI2024

Nanoconfined Interfaces for Highly Selective Separation of Critical Rare Earth Elements

Industrial demand for rare earth elements (REEs) has surged over the past three decades due to their unique properties that support sustainable energy and new technologies. Separating individual REEs is challenging and hazardous, typically done through liquid-liquid extraction. There is an urgent need for environmentally friendly and efficient separation technologies for REEs. Porous materials offer promising advances for sustainable REE separation via ion-selective capture. We hypothesize that REE separation can be efficiently achieved in reactive nanopores, such as Zr(IV) and Cr(III) metal-organic frameworks (MOFs), through surface functionalization. By integrating material synthesis, interfacial chemistry experiments, theory, computation, and machine learning, we gained insights into the chemical factors controlling REE speciation and their competitive adsorption on MOFs. Our findings show that these materials’ selectivity can be tuned by surface functionalization. The machine learning component addressed ion-specific diffusion based on MOF topology and chemistry.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Analysis of signal to noise enhancement using a highly selective modulation tracking filter

Experiments are reported which utilize photodielectric effects in semiconductor loaded superconducting resonant circuits for suppressing noise in RF communication systems. The superconducting tunable cavity acts as a narrow band tracking filter for detecting conventional RF signals. Analytical techniques were developed which lead to prediction of signal-to-noise improvements. Progress is reported in optimization of the experimental variables. These include improved Q, new semiconductors, improved optics, and simplification of the electronics. Information bearing signals were passed through the system, and noise was introduced into the computer model.

Haden, C. R.↗
NASA NTRS1974

The resistance to embrittlement by a hydrogen environment of selected high strength iron-manganese base alloys

Fe-16Mn and Fe-25Mn base alloys, which had been cold worked to yield strength levels of 201 and 178 KSI, were resistant to degradation of mechanical properties in a one atmosphere hydrogen environment at ambient temperature under the loading conditions employed in this investigation. Transmission electron microscopy established that bands of epsilon phase martensite and fcc mechanical twins were formed throughout the fcc matrix when these alloys were cold worked. In the cold worked alloys a high density of crystal defects were observed associated with both types of strain induced structures, which should contribute significantly to the strengthening of these alloys. High strength iron base alloys can be produced which appear to have some resistance to degradation of mechanical properties in a hydrogen environment under certain conditions.

Benson, R. B., Jr.↗
NASA NTRS2004

A Survey of Large Molecules of Biological Interest toward Selected High Mass Star Forming Regions

We have surveyed three high mass Galactic star forming regions for interstellar methanol (CH3OH), formic acid (HCOOH), acetic acid (CH3COOH), methyl formate (HCOOCH3), methyl cyanide (CH3CN), and ethyl cyanide (CH3CH2CN) with the BIMA Array. From our observations, we have detected two new sources of interstellar HCOOH toward the hot core regions G19.61-0.23 and W75N. We have also made the first detections of CH3CH2CN and HCOOCH3 toward G19.61-0.23. The relative HCOOH/HCOOCH3 abundance ratio toward G19.61-0.23 is 0.18 which is comparable to the abundance ratios found by Liu and colleagues toward Sgr B2(N-LMH), Orion and W51(approximately 0.10). We have made the first detection of HCOOCH3 toward W75N. The relative HCOOH/HCOOCH3 abundance ratio toward W75N is 0.26 which is more than twice as large as the abundance ratios found by Liu and colleagues. Furthermore, the hot core regions around W75N show a chemical differentiation between the O and N cores similar to what is seen toward the Orion Hot Core and Compact Ridge and W3(OH) and W3(H2O). It is also apparent from our observations that the high mass star forming region G45.47+0.05 does not contain any compact hot molecular core and as a consequence its chemistry may be similar to cold dark clouds. Finally, the formation of CH3COOH appears to favor HMCs with well mixed N and O, despite the fact that CH3COOH does not contain a N atom. If proved to be true, this is an important constraint on CH3COOH formation and possibly other structurally similar biomolecules.

Remijan, A.↗
NASA NTRS2008

Thermal Expansion Studies of Selected High Temperature Thermoelectric Materials

Radioisotope thermoelectric generators (RTGs) generate electrical power by converting the heat released from the nuclear decay of radioactive isotopes (typically plutonium-238) into electricity using a thermoelectric converter. RTGs have been successfully used to power a number of space missions and have demonstrated their reliability over an extended period of time (tens of years) and are compact, rugged, radiation resistant, scalable, and produce no noise, vibration or torque during operation. System conversion efficiency for state-of-practice RTGs is about 6% and specific power less than or equal to 5.1 W/kg. Higher specific power would result in more on-board power for the same RTG mass, or less RTG mass for the same on-board power. The Jet Propulsion Laboratory has been leading, under the advanced thermoelectric converter (ATEC) project, the development of new high-temperature thermoelectric materials and components for integration into advanced, more efficient RTGs. Thermoelectric materials investigated to date include skutterudites, the Yb14MnSb11 compound, and SiGe alloys. The development of long-lived thermoelectric couples based on some of these materials has been initiated and is assisted by a thermo-mechanical stress analysis to ensure that all stresses under both fabrication and operation conditions will be within yield limits for those materials. Several physical parameters are needed as input to this analysis. Among those parameters, the coefficient of thermal expansion (CTE) is critically important. Thermal expansion coefficient measurements of several thermoelectric materials under consideration for ATEC are described in this paper. The stress response at the interfaces in material stacks subjected to changes in temperature is discussed, drawing on work from the literature and project-specific tools developed here. The degree of CTE mismatch and the associated effect on the formation of stress is highlighted.

silicon germanium↗
DOE OSTI2020

ScAIN etch mask for highly selective etching

A fabrication process employing the use of ScAlN as an etch mask is disclosed. The ScAlN etch mask is chemically nonvolatile in fluorine-based etch chemistries and has a low sputter yield, resulting in greater etch mask selectivity and reduced surface roughness for silicon and other semiconductor materials. The ScAlN etch mask has an etch mask selectivity of greater than 200,000:1 relative to silicon compared to an etch mask selectivity of less than 40,000:1 for a prior art AlN etch mask relative to silicon. Further, due to reduced sputtering of the ScAlN etch mask, and thus reduced micromasking, the ScAlN etch mask yielded a surface roughness of 0.6 μm compared to a surface roughness of 2.8 μm for an AlN etch mask.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unsupervised Clustering and Supervised Regression Learning to Select High Temperature Oxidation-Resistant Materials

High temperature oxidation and corrosion degradation mechanisms dictate the lifetime of materials critical to energy production. The combination of modeling and experimental approaches such as machine learning (ML) and data analytics, with sufficient experimental data, can accelerate the development of new materials while limiting its cost. In the present work, ML will be applied to two high temperature oxidation data libraries (Oak Ridge National Laboratory and National Air and Space Administration) that comprised of about 5000 mass change sample datasheets for a variety of materials and temperatures in dry air and air + 10 % H2O. A python code was developed to prepare the data for machine learning by collecting and formatting oxidation rate constants, alloy compositions and environment of exposure into a single data frame. Scikit-learn library and Statistics and Machine Learning Toolbox within MathWorks were then used to perform unsupervised clustering and supervised regression learning. The impact of dataset distribution on the performance of the developed ML models was evaluated. Potential strategies to improve the predictions and enhance extrapolative capability of the previously trained model were investigated.

Romedenne, Marie [ORNL] (ORCID:0000000317936561)↗
DOE OSTI2026

Highly Efficient Selection of High-redshift Emission-line Galaxies for Future DESI-like Surveys with Deep Multiband Imaging

Emission-line galaxies (ELGs) are an important tracer of baryon acoustic oscillations (BAOs) and large-scale structure at z > 1. In this work, we investigate the feasibility of using deep wide-area multiband imaging (e.g., from the Rubin Observatory) to efficiently select high-redshift ELGs. Using Hyper Suprime-Cam grizy photometry and COSMOS2020 many-band photometric redshifts, we design simple color cuts guided by a probabilistic random forest classifier to select galaxies at z = 1.1–1.6. We then empirically test and refine these color cuts using two samples of galaxies with deep spectroscopy and broad color coverage obtained with the Dark Energy Spectroscopic Instrument (DESI). Compared to DESI ELGs at z = 1.1–1.6, we achieve a higher redshift-measurement success rate (89% versus 69%), a much higher correct redshift-range success rate (84% versus 34%), and a far higher net surface density yield (1372 deg −2 versus 660 deg −2 ). Combining our sample with current DESI ELGs would increase the net ELG number density by a factor of ∼2.5, moving it out of the shot-noise limited regime and reducing the uncertainties on the BAO scale parameter at z = 1.1–1.6 by a factor of ∼2 at the highest redshifts. We also test selections using shallower photometry and obtain qualitatively similar results.

Salcedo Hernandez, Yoquelbin [University of Pittsb↗
DOE OSTI2020

Carbon supported single atom carbon dioxide reduction electro catalysts

Electrocatalysts composed of single atoms dispersed over porous carbon support were prepared by a lithium-melt method. The new catalysts demonstrated high selectivity, high Faradic efficiency and low overpotential toward to the electrocatalytic reduction of carbon dioxide to fuels.

Liu, Di-Jia↗