Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Control Samples”

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 811 records · Page 45

Method and apparatus for telemetry adaptive bandwidth compression

Methods and apparatus are provided for automatic and/or manual adaptive bandwidth compression of telemetry. An adaptive sampler samples a video signal from a scanning sensor and generates a sequence of sampled fields. Each field and range rate information from the sensor are hence sequentially transmitted to and stored in a multiple and adaptive field storage means. The field storage means then, in response to an automatic or manual control signal, transfers the stored sampled field signals to a video monitor in a form for sequential or simultaneous display of a desired number of stored signal fields. The sampling ratio of the adaptive sample, the relative proportion of available communication bandwidth allocated respectively to transmitted data and video information, and the number of fields simultaneously displayed are manually or automatically selectively adjustable in functional relationship to each other and detected range rate. In one embodiment, when relatively little or no scene motion is detected, the control signal maximizes sampling ratio and causes simultaneous display of all stored fields, thus maximizing resolution and bandwidth available for data transmission. When increased scene motion is detected, the control signal is adjusted accordingly to cause display of fewer fields. If greater resolution is desired, the control signal is adjusted to increase the sampling ratio.

Graham, Olin L.↗

Thermophysical Property Measurement and Materials Research in the NASA/MSFC Electrostatic Levitator

Containerless processing is an important tool for thermophysical property measurements and materials research. The freedom from a crucible allows processing of liquid materials in a metastable undercooled state, as well as allowing processing of high temperature and highly reactive melts. Electrostatic levitation (ESL) is a containerless method which provides a number of unique advantages, including the decoupling of positioning force from sample heating, the ability to operate in ultra-high vacuum or at moderate gas pressure (approximately 3 atm), and the ability to process non-conducting materials. ESL also has the potential to reduce internal flow velocities below those possible with electromagnetic, acoustic, or aero-acoustic techniques. The ESL facility at NASA's Marshall Space Flight Center (MSFC) is in use for thermophysical property measurements and materials research by a number of different internal and external investigators. The methods for obtaining access to the facility, as well as a summary of current capabilities and some future directions will be discussed. In electrostatic levitation, the acceleration of gravity (or residual acceleration in reduced gravity) is opposed by the action of an applied electric field on a charged sample. This positioning method is applicable to any material which can be electrically charged, whether solid or liquid, conducting, or insulating. Because the position of the sample is unstable, a 3-dimensional active control loop rapidly adjusts the applied field to maintain levitation and minimize motion of the sample. Heating lasers melt the sample, and may be adjusted to maintain specified thermal profiles. Microgravity allows electrostatic levitation to work even more effectively. With the need to cancel less than 1 milli-g, the applied field required is reduced from approximately 10 MV/m to approximately 10 kV/m. Alternatively, a microgravity ESL can position larger samples than is possible on the ground, or it can position samples which maintain their charge poorly. Microgravity also reduces the effects of buoyant convection and sedimentation. In the MSFC ESL, many different classes of experiments and measurements have been demonstrated in collaboration with many investigators. These capabilities include heat capacity measurement, phase diagram determination, and nucleation and growth experiments including nucleation rate, TTT curves, and phase selection. We have demonstrated the capability of triggering recalescence of an undercooled liquid sample without loss of levitation. Currently under development are techniques for measuring the surface tension, viscosity, and density of levitated samples, as well as other thermophysical properties. Expanded levitation capabilities including various gas environments for sample processing, sample rotation control and management of thermal gradients are under development for the MSFC ESL. Containerless processing allows research on materials which may not be processed any other way. Electrostatic levitation extends the range of containerless processing to include many materials and classes of materials which cannot be processed by conventional electromagnetic, acoustic, or aerodynamic levitation techniques.

Rogers, Jan↗

Controlling hydrocarbon transport and electron beam induced deposition on single layer graphene: Toward atomic scale synthesis in the scanning transmission electron microscope

Abstract Focused electron beam induced deposition (FEBID) is a direct write technique for depositing materials on a support substrate akin to 3D printing with an electron beam (e‐beam). Opportunities exist for merging this existing technique with aberration‐corrected scanning transmission electron microscopy to achieve molecular‐ or atomic‐level spatial precision. Several demonstrations have been performed using graphene as the support substrate. A common challenge that arises during this process is e‐beam‐induced hydrocarbon deposition, suggesting greater control over the sample environment is needed. Various strategies exist for cleaning graphene in situ. One of the most effective methods is to rapidly heat to high temperatures, for example, 600℃ or higher. While this can produce large areas of what appears to be atomically clean graphene, mobile hydrocarbons can still be present on the surfaces. Here, we show that these hydrocarbons are primarily limited to surface migration and demonstrate an effective method for interrupting the flow using e‐beam deposition to form corralled hydrocarbon regions. This strategy is effective for maintaining atomically clean graphene at high temperatures where hydrocarbon mobility can lead to substantial accumulation of unwanted e‐beam deposition.

36 MATERIALS SCIENCE↗

Multi-omics of NET formation and correlations with CNDP1, PSPB, and L-cystine levels in severe and mild COVID-19 infections

We report that we performed a multi-omics analysis of an immunologically naïve SARS-CoV-2 clinical cohort to characterize overall changes in plasma among control (uninfected), mild, and severe infections. A comparison of healthy controls and patient samples showed activation of neutrophil degranulation pathways. Consistent with this observation, we characterized neutrophil extracellular trap (NET) complexes that were partially initiated in a subset of the mild infections (showing partially formed NETs) and fully-formed NETs in a subset of severe infections (containing multiple NET proteins in individual patient samples). As a potential mechanism to suppress NET formation, multiple redox enzymes were elevated in the mild and severe population. Analysis of metabolites from the same cohort showed a 24 and 60-fold elevation in plasma L-cystine, the oxidized form of cysteine and substrate of the powerful antioxidant glutathione in mild and severe patients, respectively. Unique to patients with mild infections, the carnosine dipeptidase modifying enzyme (CNDP1) was up-regulated. The strong protein and metabolite oxidation signatures suggest multiple compensatory pathways working to suppress both free radical and NET formation in SARS-CoV-2 infections.

60 APPLIED LIFE SCIENCES↗

Impact of galactic cosmic ray simulation on nutritional content of foods

Foods packaged for future deep-space exploration missions may be prepositioned ahead of astronaut arrival, and will be exposed to galactic cosmic rays (GCRs) and solar radiation in deep space at higher levels and different spectrums than those found in low-Earth orbit (LEO). In this study, we have evaluated the impact of a GCR simulation (approximately 0.5 and 5 Gy doses) at the NASA Space Radiation Laboratory (NSRL) on two retort thermostabilized food products that are good sources of radiation labile nutrients (thiamin, vitamin E, or unsaturated fats). No trends or nutritional differences were found between the radiation-treated samples and the control immediately after treatment or one-year after treatment. Small changes in a few nutrients were measured following one-year of storage. Further studies are needed to confirm these results, as the foods in this study were heterogeneous, and this may have masked meaningful changes due to pouch-to-pouch variations.

59 BASIC BIOLOGICAL SCIENCES↗

Continual learning in the presence of repetition

Continual learning (CL) provides a framework for training models in ever-evolving environments. Although re-occurrence of previously seen objects or tasks is common in real-world problems, the concept of repetition in the data stream is not often considered in standard benchmarks for CL. Unlike with the rehearsal mechanism in buffer-based strategies, where sample repetition is controlled by the strategy, repetition in the data stream naturally stems from the environment. This report provides a summary of the CLVision challenge at CVPR 2023, which focused on the topic of repetition in class-incremental learning. The report initially outlines the challenge objective and then describes three solutions proposed by finalist teams that aim to effectively exploit the repetition in the stream to learn continually. The experimental results from the challenge highlight the effectiveness of ensemble-based solutions that employ multiple versions of similar modules, each trained on different but overlapping subsets of classes. This report underscores the transformative potential of taking a different perspective in CL by employing repetition in the data stream to foster innovative strategy design.

Class-incremental learning↗

Atom-by-Atom Direct Writing

Direct-write processes enable the alteration or deposition of materials in a continuous, directable, sequential fashion. Here, in this work, we demonstrate an electron beam direct-write process in an aberration-corrected scanning transmission electron microscope. This process has several fundamental differences from conventional electron-beam-induced deposition techniques, where the electron beam dissociates precursor gases into chemically reactive products that bond to a substrate. Here, we use elemental tin (Sn) as a precursor and employ a different mechanism to facilitate deposition. The atomic-sized electron beam is used to generate chemically reactive point defects at desired locations in a graphene substrate. Temperature control of the sample is used to enable the precursor atoms to migrate across the surface and bond to the defect sites, thereby enabling atom-by-atom direct writing.

36 MATERIALS SCIENCE↗

Mid-Infrared Photoluminescence from Tellurium Thin Films

Tellurium is an elemental semiconductor with a 0.34 eV optical band gap, showing promise for mid-infrared (MIR) optoelectronics including light-emitting diodes. However, quantitative measurement of the tellurium luminescence efficiency has not yet been investigated, and growing optically active films remain challenging. Here, we demonstrate the low-temperature growth of bright tellurium thin films by using physical vapor transport. The sample morphology is controlled by varying the growth temperature, yielding continuous thin films, microparticles, or nanowires. Additionally, we demonstrated patterned growth by using a seed layer for selective nucleation. Quantitative photoluminescence measurements at room temperature reveal an internal quantum yield of 2.0% at 0.34 eV for the as-grown tellurium films, comparable to the best-reported efficiencies of III-V and II-VI compound semiconductors with similar band gaps. Furthermore, we demonstrate band-gap tunability with Te-Se alloys, where up to 20% selenium incorporation gradually blue-shifts the band gap to 0.55 eV. The work demonstrates the potential use of tellurium for efficient MIR devices.

Wang, Shu↗

Characterization of Electronic Stress-Induced Changes in Multilayer MoS 2

Transition metal dichalcogenides like molybdenum disulfide (MoS 2 ) are compelling for next-generation electronic devices. In this work, we investigate the impact of electronic stress on MoS 2 to illustrate that observational and phenomenological information on multiple devices can be useful to describe changes in the device, and caution against the rationalization of paltry results as representative or correlative to device behavior. Here, we stress MoS 2 by applying a sustained 20 V DC bias to study the material’s response. Post-stress electronic characterization revealed nonuniform shifts in current–voltage (I–V) behavior alongside microscale changes. Complementary mechanical, spectroscopic, and scanning microwave impedance measurements showed that stress-induced features locally modulate stiffness, surface potential, Raman intensity, and charge carrier density. We correlated I–V behavior with morphological features (wrinkles, tears, folds, height) and device-level geometry (MoS 2 overlap with electrodes, channel area, contact length) on 50 test structures across five chips to move beyond anecdotal conclusions. We found no universal correlations before DC stress. However, device-level geometry was correlated with I–V behavior after DC stress, suggesting that electrode contacts play a more dominant role than morphology in determining performance. Delamination and thinning induced by DC stress led to localized reductions in charge carrier density within the affected regions. Further, delamination and thinning appear to map to I–V device performance in a few samples, but the correlation is lost when a larger sample size is considered. This suggests significant sample-to-sample variability in surface electronic states of the test structures. We also discuss how environmental factors introduced during fabrication may contribute to the observed heterogeneous device response. Progress will require high-resolution, multimodal analysis across many samples constructed under controlled, clean conditions. By building data sets that capture variability, we can better identify the true drivers of performance.

36 MATERIALS SCIENCE↗

Leveraging Multiple Raman Excitation Wavelength Systems for Process Monitoring of Nuclear Waste Streams

Processing nuclear waste from sites such as Hanford is a significant environmental cleanup need while being a significant logistical challenge. Integration of process monitoring tools, that can provide in situ and real-time feedback about the process, can significantly alleviate needs to collect grab samples for process control and product characterization. Raman spectroscopy paired with chemometric analysis is one process monitoring tool that can provide chemical composition information on a large number of chemical targets in nuclear waste streams. However, methods to improve limits of detection as well as drop uncertainty in quantification are needed. Optimizing instrument specifications can achieve this, here this is demonstrated by comparing limits of detection for key analytes when using Raman systems with 671 nm, 532 nm, and 405 nm excitation wavelengths. Generally, limits of detection decease (allowing the measurement of lower salt concentrations) with decreasing wavelength. Similarly, data collection times and averaging were optimized. Finally, multiple chemometric modeling approaches were leveraged, including multiblock methods that combined data from all three Raman systems to simultaneously quantify targets with improved sensitivity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Direct 2,3-Butanediol Conversion to Butene-Rich C 3+ Olefins over Copper-Modified 2D Pillared MFI: Consequence of Reduced Diffusion Length

2,3-Butanediol (2,3-BDO), a critical C 4 platform chemical derived from biomass, syngas, or CO 2 , can be converted to C 3+ olefins, serving as important renewable feedstocks for producing sustainable aviation fuels to decarbonize the hard-to-electrify air transportation sector. Herein, we report a bifunctional Cu-modified diffusion-free 2D pillared MFI catalyst (Cu/PMFI) which can selectively catalyze 2,3-BDO conversion to butene-rich C 3+ olefins (95% selectivity at 97% conversion, 523 K). 2,3-BDO conversion to butenes over Cu/PMFI primarily occurs via methyl ethyl ketone intermediate while 2-methyl propanal is also observed as another minor dehydration product that leads to butene formation. In comparison with a control mesoporous Cu/ZSM-5 sample prepared by the postsynthetic approach, Cu/PMFI shows favorable C 3+ olefin selectivity (95% over Cu/PMFI vs 80% over Cu/ZSM-5 at ~5.1 h TOS). The coke formation over Cu/PMFI is dramatically suppressed by >50% in contrast to Cu/ZSM-5 in 90 h 2,3-BDO conversion due to the reduced diffusion length. Cu/PMFI also favors butene formation and minimizes nonbutene C 3+ olefins by inhibiting the downstream oligomerization and cracking reactions. This study highlights the usefulness of the diffusion-free 2D PMFI materials in catalytic conversion of biomass-derived platform molecules and the significance of diffusion impact on catalyst coke formation and product distributions.

2,3-butanediol↗

Ultrafast lattice disordering can be accelerated by electronic collisional forces

In the prevalent picture of ultrafast structural phase transitions, the atomic motion occurs in a slowly varying potential energy surface determined adiabatically by the fast electrons. However, this ignores non-conservative forces caused by electron-lattice collisions, which can significantly influence atomic motion. Most ultrafast techniques only probe the average structure and are less sensitive to random displacements, and therefore do not detect the role played by non-conservative forces in phase transitions. Here we show that the lattice dynamics of the prototypical insulator-to-metal transition of VO 2 cannot be described by a potential energy alone. We use the sample temperature to control the preexisting lattice disorder before ultrafast photoexcitation across the phase transition and our ultrafast diffuse scattering experiments show that the fluctuations characteristic of the rutile metal develop equally fast (120 fs) at initial temperatures of 100 K and 300 K. This indicates that additional non-conservative forces are responsible for the increased lattice disorder. In conclusion, these results highlight the need for more sophisticated descriptions of ultrafast phenomena beyond the Born-Oppenheimer approximation as well as ultrafast probes of spatial fluctuations beyond the average unit cell measured by diffraction.

36 MATERIALS SCIENCE↗

Nodal superconductivity in miassite Rh 17 S 15

Solid state chemistry has produced a plethora of materials with properties not found in nature. For example, high-temperature superconductivity in cuprates is drastically different from the superconductivity of naturally occurring metals and alloys and is frequently referred to as unconventional. Unconventional superconductivity is also found in other synthetic compounds, such as iron-based and heavy-fermion superconductors. Here, we report compelling evidence of unconventional nodal superconductivity in synthetic samples of Rh 17 S 15 (T c = 5.4 K), which is also found in nature as the mineral miassite. We investigated the temperature-dependent variation of the London penetration depth Δλ(T) and the disorder evolution of the critical superconducting temperature T c and the upper critical field H c2 (T) in single crystalline Rh 17 S 15 . We found a T - linear temperature variation of Δλ(T) below 0.3T c , which is consistent with the presence of nodal lines in the superconducting gap of Rh 17 S 15 . The nodal character of the superconducting state is supported by the observed suppression of T c and H c2 (T) in samples with a controlled level of non-magnetic disorder introduced by 2.5 MeV electron irradiation. We propose a nodal sign-changing superconducting gap in the A 1g irreducible representation, which preserves the cubic symmetry of the crystal and is in excellent agreement with the derived superfluid density. To the best of our knowledge, this establishes miassite as the only mineral known so far that reveals unconventional superconductivity in its clean synthetic form, though it is unlikely that it is present in natural crystals because of unavoidable impurities that quickly destroy nodal superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots

Most problems within and beyond the scientific domain can be framed into one of the following three levels of complexity of function approximation. Type 1: Approximate an unknown function given input/output data. Type 2: Consider a collection of variables and functions, some of which are unknown, indexed by the nodes and hyperedges of a hypergraph (a generalized graph where edges can connect more than two vertices). Given partial observations of the variables of the hypergraph (satisfying the functional dependencies imposed by its structure), approximate all the unobserved variables and unknown functions. Type 3: Expanding on Type 2, if the hypergraph structure itself is unknown, use partial observations of the variables of the hypergraph to discover its structure and approximate its unknown functions. These hypergraphs offer a natural platform for organizing, communicating, and processing computational knowledge. While most scientific problems can be framed as the data-driven discovery of unknown functions in a computational hypergraph whose structure is known (Type 2), many require the data-driven discovery of the structure (connectivity) of the hypergraph itself (Type 3). We introduce an interpretable Gaussian Process (GP) framework for such (Type 3) problems that does not require randomization of the data, access to or control over its sampling, or sparsity of the unknown functions in a known or learned basis. Its polynomial complexity, which contrasts sharply with the super-exponential complexity of causal inference methods, is enabled by the nonlinear ANOVA capabilities of GPs used as a sensing mechanism.

Science & Technology - Other Topics↗

Micro on a macroscale: relating microbial-scale soil processes to global ecosystem function

ABSTRACT Soil microorganisms play a key role in driving major biogeochemical cycles and in global responses to climate change. However, understanding and predicting the behavior and function of these microorganisms remains a grand challenge for soil ecology due in part to the microscale complexity of soils. It is becoming increasingly clear that understanding the microbial perspective is vital to accurately predicting global processes. Here, we discuss the microbial perspective including the microbial habitat as it relates to measurement and modeling of ecosystem processes. We argue that clearly defining and quantifying the size, distribution and sphere of influence of microhabitats is crucial to managing microbial activity at the ecosystem scale. This can be achieved using controlled and hierarchical sampling designs. Model microbial systems can provide key data needed to integrate microhabitats into ecosystem models, while adapting soil sampling schemes and statistical methods can allow us to collect microbially-focused data. Quantifying soil processes, like biogeochemical cycles, from a microbial perspective will allow us to more accurately predict soil functions and address long-standing unknowns in soil ecology.

59 BASIC BIOLOGICAL SCIENCES↗

Galaxy morphologies revealed with Subaru HSC and super-resolution techniques. I. Major merger fractions of L UV ∼ 3–15 L*UV dropout galaxies at z ∼ 4–7

Abstract We perform a super-resolution analysis of the Subaru Hyper Suprime-Cam (HSC) images to estimate the major merger fractions of z ∼ 4–7 dropout galaxies at the bright end of galaxy UV luminosity functions (LFs). Our super-resolution technique improves the spatial resolution of the ground-based HSC images, from ∼1″ to $\lesssim \!\!{0{^{\prime \prime }_{.}}1}$, which is comparable to that of the Hubble Space Telescope, allowing us to identify z ∼ 4–7 bright major mergers at a high completeness value of $\gtrsim \!\!90\%$. We apply the super-resolution technique to 6412, 16, 94, and 13 very bright dropout galaxies at z ∼ 4, 5, 6, and 7, respectively, in a UV luminosity range of LUV ∼ 3–$15\, L_{\rm UV}^*$ corresponding to −24 ≲ MUV ≲ −22. The major merger fractions are estimated to be $f_{\rm merger}\sim 10\%$–$20\%$ at z ∼ 4 and $\sim 50\%$–$70\%$ at z ∼ 5–7, which shows no fmerger difference compared to those of a control faint galaxy sample. Based on the fmerger estimates, we verify contributions of source blending effects and major mergers to the bright-end of double power-law (DPL) shape of z ∼ 4–7 galaxy UV LFs. While these two effects partly explain the DPL shape at LUV ∼ 3–$10\, L_{\rm UV}^*$, the DPL shape cannot be explained at the very bright end of $L_{\rm UV}\gtrsim 10\, L_{\rm UV}^*$, even after the AGN contribution is subtracted. The results support scenarios in which other additional mechanisms such as insignificant mass quenching and low dust obscuration contribute to the DPL shape of galaxy UV LFs.

Shibuya, Takatoshi↗

Melting temperature measurement of refractory oxide ceramics as a function of oxygen fugacity using containerless methods

An aerodynamic conical nozzle levitator (CNL) has been used to measure the melting temperatures of refractory ceramics. The well-established method of cooling traces has been adapted to allow measurements for air-sensitive samples using a controlled atmosphere, where the oxygen partial pressure can be adjusted and monitored in real time. In this study, we explain the details of a system that we developed for use at the Spallation Neutron Source (Oak Ridge National Laboratory). Measurements of the melting behavior of (Fe,Cr,Al) 3 O 4 spinels were made between log (PO 2 (atm)) of -0.7 and -5. The melting temperature of hercynite is found to be oxygen potential dependent, ranging between 1692 and 1767°C at log (PO 2 ) values from -4.42 to -0.70.

36 MATERIALS SCIENCE↗

2022 American Conference on Neutron Scattering (ACNS 2022)

The 11th American Conference on Neutron Scattering (ACNS 2022) will be held on June 5-9, 2022, in Boulder, CO. The Conference will provide essential information on the breadth and depth of current neutron-related research worldwide. Hosted by the Neutron Scattering Society of America, this year’s Conference will feature a combination of invited and contributed talks, poster sessions, and tutorials. Topics of the conference are: Advances in Neutron Facilities, Instrumentation and Software: Developments in sources, instrumentation, sample environments and control software. Hard Condensed Matter: Magnetism, correlated metals, quantum/topological materials, superconductors, ferroelectrics, multiferroics, glasses, and disorder phenomena. Submissions outlining examples of neutron scattering in industrial and engineering applications involving hard condensed matter systems are also encouraged. Soft Matter: Neutron studies of soft materials and related fields including in situ and in operando studies. Polymers, surfactants, emulsions, gels, nanoparticles, colloidal suspensions and more. Submissions of computational studies or applications of machine learning beneficial to neutron scattering experiments, as well as examples of neutron scattering in industrial and engineering applications are strongly encouraged. Biology, Biophysics and Biotechnology: Neutron studies of biological and biologically relevant systems. Proteins, bio membranes, biological assemblies, natural materials, nucleic acids, drug-delivery platforms and biomedical systems. Submissions of computational studies or applications of machine learning beneficial to biological neutron scattering experiments, as well as examples of neutron scattering in applied research involving biological systems, are strongly encouraged. Materials Chemistry and Energy: Neutron-based studies of functional materials and materials for energy applications. Examples include porous materials such as metal organic frameworks (MOFs), zeolites; phosphors; novel pigments; electrolytes; catalysts; ionic conductors/cathode materials; photovoltaic materials (hybrid perovskites); thermoelectrics; magnetocalorics/electrocalorics. Structural Materials and Engineering: Neutron scattering studies of materials and engineering processes including structural materials, concrete and metals, as well as engineering processes including combustion, corrosion, additive manufacturing, and others. Neutron Physics: Fundamental physical studies of the neutron and related areas. Emerging Applications in Neutron Scattering: Machine Learning and Data Science: Advances in computing power have contributed to rapidly evolving machine learning and data science fields that can be leveraged to the benefit of the neutron scattering community. The purpose of this session is to highlight recent advances in machine learning and data science and to serve as the foundation of a parallel data and computation track highlighting computation advances and applications in neutron scattering throughout the conference.

36 MATERIALS SCIENCE↗