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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.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Field by field hybrid upwind splitting methods

A new and general approach to upwind splitting is presented. The design principle combines the robustness of flux vector splitting schemes in the capture of nonlinear waves and the accuracy of some flux difference splitting schemes in the resolution of linear waves. The new schemes are derived following a general hybridization technique performed directly at the basic level of the field by field decomposition involved in FDS methods. The scheme does not use a spatial switch to be tuned up according to the local smoothness of the approximate solution.

Coquel, Frederic↗
NASA NTRS1992

Experiments with recursive estimation in astronomical image processing

Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

Busko, I.↗
NASA NTRS2022

Simultaneous Retrieval of Selected Optical Water Quality Indicators From Landsat-8, Sentinel-2, and Sentinel-3

Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (a cdom (440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and a cdom (440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and a cdom (440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and a cdom (440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model.

Machine learning↗
DOE OSTI2022

Short-Range Order Tunes Optical Properties in Long-Range Disordered ZnSnN2-ZnO Alloy

Local site ordering offers a new paradigm for property control in functional materials. However, systems that exhibit a propensity for local order and global disorder are often challenging to characterize, and demonstrations of ordering-induced property tuning are few and far between. Here, we demonstrate that short-range ordering tunes the optical absorption edge in the long-range disordered alloy system (ZnSnN2)1-x(ZnO)2x at x = 0.25. We use combinatorial cosputtering to synthesize a set of thin-film samples spanning this alloy space. X-ray diffraction demonstrates lattice contraction as a function of alloy composition, confirming that a mixed-anion and -cation alloy has been synthesized. Using N and O K-edge X-ray absorption near-edge structure in conjunction with simulations of cation-disordered supercell structures, we find that samples exhibit octet-rule-breaking motifs around both anions. Upon annealing at an alloy composition of x = 0.25, X-ray absorption analysis suggests that local motif structure shifts toward octet-rule-conserving while long-range disorder is maintained. Spectroscopic ellipsometry reveals that local ordering increases the absorption edge energy at constant composition. Additionally, alloy-induced optical absorption edge tuning is demonstrated. This work paves the way toward property tuning with short-range ordering in (ZnSnN2)1-x(ZnO)2x and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nanoscale Probing of Electrical Memory Effects in van der Waals Layered PdSe 2

Tunable electronic materials that can be switched between different impedance states are fundamental to the hardware elements for neuromorphic computing architectures. This “brain-like” computing paradigm uses highly paralleled and colocated data processing, leading to greatly improved energy efficiency and performance compared to traditional architectures in which data have to be frequently transferred between processor and memory. In this work, we use scanning microwave impedance microscopy for nanoscale electrical and electronic characterization of two-dimensional layered semiconductor PdSe 2 to probe neuromorphic properties. The local resolution of tens of nanometers reveals significant differences in electronic behavior between and within PdSe 2 nanosheets (NSs). In particular, we detected both n-type and p-type behaviors, although previous reports only point to ambipolar n-type dominating characteristics. Nanoscale capacitance–voltage curves and subsequent calculation of characteristic maps revealed a hysteretic behavior originating from the creation and erasure of Se vacancies as well as the switching of defect charge states. In addition, stacks consisting of two NSs show enhanced resistive and capacitive switching, which is attributed to trapped charge carriers at the interfaces between the stacked NSs. Stacking n- and p-type NSs results in a combined behavior that allows one to tune electrical characteristics. In conclusion, as local inhomogeneities of electrical and electronic behavior can have a significant impact on the overall device performance, the demonstrated nanoscale characterization and analysis will be applicable to a wide range of semiconducting materials.

2D material↗
NASA NTRS2004

THIS: A Next Generation Tuneable Heterodyne Infrared Spectrometer for SOFIA

A new infrared heterodyne instrument has been developed which allows the use of both tuneable diode lasers (TDL) and quantum cascade lasers (QCL) as local oscillators (LO). The current frequency tuning range of our system extends from 900 to 1100/cm depending on the availability of lasers but is planned to be extended to 600/cm soon. The IF-bandwidth is 1.4 GHz using an acousto-optical spectrometer (AOS). The frequency resolution and stability of the system is approximately 10(exp 7). Currently, mercury-cadmium-telluride (MCT) detectors are used as mixers while new devices like quantum-well-infrared-photodetectors (QWIP) and hot-electron-bolometers (HEB) are investigated. The IF-bandwidth can be extended to about 3 GHz by using a new broadband acousto-optical spectrometer presently under development. The instrument is fully transportable and can be attached to any infrared or optical telescope. The semiconductor laser is stabilized to a Fabry-Perot ring-resonator, which is also used as an efficient diplexer to superimpose the local-oscillator and the signal radiation. As a first step measurements of trace gases in Earth's atmosphere and non-LTE emission from Venus' atmosphere were carried out as well as observations of molecular features in sunspots. Further astronomical observations from ground-based telescopes and the airborne observatory SOFIA are planned for the future. Of particular interest are molecules without a permanent dipole moment like H2, CH4, C2H2 etc.

Sonnabend, Guido↗
DOE OSTI2022

Resolving the Impact of Hydrogen Bonding on the Phylloquinone Cofactor through Two-Dimensional Infrared Spectroscopy

Phylloquinone (PhQ) is a molecule involved in photosynthetic electron transfer, where the local protein environment is known to tune the properties of PhQ through various noncovalent interactions. In this work, we determine how hydrogen bonding, one of these noncovalent interactions, alters the vibrational potential energy surface of PhQ. In addition, this work demonstrates how hydrogen bonding to PhQ manifests in ultrafast multidimensional vibrational spectra, which is an important step towards using ultrafast vibrational based spectroscopies to probe PhQ embedded in the binding pocket of photosynthetic reaction centers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Observation of Iso-Symmetric Structural and Lifshitz Transitions in Quasi-One-Dimensional CrNbSe 5

Chalcogenides-rich transition metal compounds host a rich landscape of emergent quantum phenomena that are intimately governed by their quasi-onedimensional chemical-bonding frameworks and their response to external perturbations such as pressure. Here, we report a pressure-induced iso-symmetric structural transition in the quasi-one-dimensional compound CrNbSe 5 , in which the electronic ground state is controlled not by symmetry breaking but by a continuous reorganization of local bonding interactions. Applied pressure reversibly tunes CrNbSe 5 between semiconducting and semimetallic states, enabling access to low- and high-carrier electronic regimes through direct modulation of metal−chalcogen bonding. High-pressure singlecrystal X-ray diffraction directly resolves the evolution of Cr−Se and Nb−Se bond distances, coordination polyhedra, and connectivity, revealing a fully reversible semimetal−semiconductor−semimetal transition driven by gradual yet cooperative bond rearrangements within a preserved crystallographic symmetry. In contrast to chemical substitution, which irreversibly alters composition and introduces disorder, pressure acts as a clean, continuous control parameter that reshapes the bonding landscape without disrupting structural symmetry. These results establish CrNbSe 5 as a model system for electronically driven phase switching via tunable chemical bonding, highlighting iso-symmetric bond reorganization as a powerful design principle for pressure-controlled electronic and spintronic functionalities.

Compression↗
DOE OSTI2026

Fabrication of Catalytic Distillation Membranes with Atomic Layer Deposition

The integration of catalysts onto the surface of membranes enables simultaneous physical separation and catalytic transformation of constituents in a feed stream, facilitating improved contaminant removal and fouling mitigation. Distillation membranes are a particularly attractive platform for catalytic membranes because they reject nonvolatile species and exhibit exceptional resistance to oxidative and radical-driven degradation. However, imparting catalytic functionality onto hydrophobic, porous distillation membranes has proven challenging since the membranes used are chemically inert and difficult to modify. Furthermore, catalysts on the membrane surface can decrease hydrophobicity and increase the membrane’s susceptibility to pore wetting and failure. In this work, we create a catalytic distillation membrane by coating a polytetrafluoroethylene membrane surface with titanium dioxide (TiO 2 ) via plasma-assisted atomic layer deposition (ALD). By precisely tuning the ALD parameters, we demonstrate localized growth of TiO 2 near (within approximately 1 μm) the surface of polytetrafluoroethylene membranes, forming a catalytically active interface while preserving the underlying hydrophobic pore structure. Localized growth of TiO 2 is confirmed by electron microscopy and spectroscopy techniques, and membranes coated with 500 cycles of ALD show pressure tolerance up to 12.8 bar and higher than 95% salt rejection in pressure-driven distillation. Photocatalytic activity is demonstrated via the degradation of methylene blue dye under UV irradiation, where increasing TiO2 loading leads to an enhancement in dye degradation. These results establish a general strategy for integrating catalytic functionality into chemically inert, hydrophobic membranes without compromising distillation performance, providing a pathway toward multifunctional membranes that couple advanced oxidation with membrane separation for water treatment.

atomic layer deposition↗
DOE OSTI2022

Orientation-controlled crystallization of γ-glycine films with enhanced piezoelectricity

Glycine, the simplest amino acid, is considered a promising functional biomaterial owing to its excellent biocompatibility and strong out-of-plane piezoelectricity. Practical applications require glycine films to be manufactured with their strong piezoelectric polar $\langle$001$\rangle$ direction aligned with the film thickness. Based on the recently-developed solidification approach of a polyvinyl alcohol (PVA) and glycine aqueous solution, in this work, we demonstrate that the crystal orientation of the as-synthesized film is determined by the orientation of glycine crystal nuclei. By controlling the local nucleation kinetics via surface curvature tuning, here we shifted the nucleation site from the edge to the middle of the liquid film, and thereby aligned the $\langle$001$\rangle$ direction vertically. As a result, the PVA–glycine–PVA sandwich film exhibits the highest average piezoelectric coefficient d 33 of 6.13 ± 1.13 pC N –1 . This work demonstrates a promising kinetic approach to achieve crystallization and property control in a scalable biocrystal manufacturing process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Neural architecture codesign for fast physics applications

We develop a pipeline to streamline neural architecture codesign for physics applications to reduce the need for ML expertise when designing models for novel tasks. Our method employs neural architecture search and network compression in a two-stage approach to discover hardware efficient models. This approach consists of a global search stage that explores a wide range of architectures while considering hardware constraints, followed by a local search stage that fine-tunes and compresses the most promising candidates. We exceed performance on various tasks and show further speedup through model compression techniques such as quantization-aware-training and neural network pruning. We synthesize the optimal models to high level synthesis code for FPGA deployment with the hls4ml library. Additionally, our hierarchical search space provides greater flexibility in optimization, which can easily extend to other tasks and domains. We demonstrate this with two case studies: Bragg peak finding in materials science and jet classification in high energy physics, achieving models with improved accuracy, smaller latencies, or reduced resource utilization relative to the baseline models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗
NASA NTRS2000

Coherent Doppler Laser Radar: Technology Development and Applications

NASA's Marshall Space Flight Center has been investigating, developing, and applying coherent Doppler laser radar technology for over 30 years. These efforts have included the first wind measurement in 1967, the first airborne flights in 1972, the first airborne wind field mapping in 1981, and the first measurement of hurricane eyewall winds in 1998. A parallel effort at MSFC since 1982 has been the study, modeling and technology development for a space-based global wind measurement system. These endeavors to date have resulted in compact, robust, eyesafe lidars at 2 micron wavelength based on solid-state laser technology; in a factor of 6 volume reduction in near diffraction limited, space-qualifiable telescopes; in sophisticated airborne scanners with full platform motion subtraction; in local oscillator lasers capable of rapid tuning of 25 GHz for removal of relative laser radar to target velocities over a 25 km/s range; in performance prediction theory and simulations that have been validated experimentally; and in extensive field campaign experience. We have also begun efforts to dramatically improve the fundamental photon efficiency of the laser radar, to demonstrate advanced lower mass laser radar telescopes and scanners; to develop laser and laser radar system alignment maintenance technologies; and to greatly improve the electrical efficiency, cooling technique, and robustness of the pulsed laser. This coherent Doppler laser radar technology is suitable for high resolution, high accuracy wind mapping; for aerosol and cloud measurement; for Differential Absorption Lidar (DIAL) measurements of atmospheric and trace gases; for hard target range and velocity measurement; and for hard target vibration spectra measurement. It is also suitable for a number of aircraft operations applications such as clear air turbulence (CAT) detection; dangerous wind shear (microburst) detection; airspeed, angle of attack, and sideslip measurement; and fuel savings through headwind minimization. In addition to the airborne and space platforms, a coherent Doppler laser radar system in an unmanned aerial vehicle (UAV) could provide battlefield weather and target identification.

Kavaya, Michael J.↗
DOE OSTI2026

Extremized nonlinear and linearized responses in soft metamaterials enabled by gradient-based design and grayscale digital light processing

In this study, we develop a gradient-based design approach that exploits grayscale digital light processing (DLP) 3D printing for extremizing the nonlinear and linearized response of soft metamaterials — materials that harness engineered geometric instabilities to undergo large and programmable changes in configuration. Grayscale DLP approaches modulate local mechanical properties at the pixel scale by tuning the light intensity within a single grayscale image, unlocking an exceptionally large design space. To effectively navigate this space, we develop smooth mappings between local light intensity values and global quantities of interest that characterize the behavior of soft metamaterials. Enabling these smooth mappings are robust and differentiable nonlinear finite element simulations powered by a trust region solver. A PDE-constrained optimization problem is then solved to invert these mappings and produce light intensity distributions that endow the printed part with varying stiffness and flexibility in distinctive regions. It is shown that optimizing the distribution of soft and stiff phases throughout a metamaterial structure results in markedly different buckling and self-contact configurations to drive extremized nonlinear compression and linearized vibration responses. Optimized light intensity distributions are translated to grayscale images and directly used to print soft metamaterial samples, showing remarkable agreement between the buckling and self-contact response in simulated and measured deformed configurations.

Additive manufacturing↗
DOE OSTI2024

Modifying the Reactivity of Single Pd Sites in a Trimetallic Sn‐Pd‐Ag Surface Alloy: Tuning CO Binding Strength

Abstract Improving control over active‐site reactivity is a grand challenge in catalysis. Single‐atom alloys (SAAs) consisting of a reactive component doped as single atoms into a more inert host metal feature localized and well‐defined active sites, but fine tuning their properties is challenging. Here, a framework is developed for tuning single‐atom site reactivity by alloying in an additional inert metal, which this work terms an alloy‐host SAA. Specifically, this work creates about 5% Pd single‐atom sites in a Pd 33 Ag 67 (111) single crystal surface, and then identifies Sn based on computational screening as a suitable third metal to introduce. Subsequent experimental studies show that introducing Sn indeed modifies the electronic structure and chemical reactivity (measured by CO desorption energies) of the Pd sites. The modifications to both the electronic structure and the CO adsorption energies are in close agreement with the calculations. These results indicate that the use of an alloy host environment to modify the reactivity of single‐atom sites can allow fine‐tuning of catalytic performance and boost resistance against strong‐binding adsorbates such as CO.

Mohrhusen, Lars↗
NASA NTRS1973

Automatic carrier acquisition system

An automatic carrier acquisition system for a phase locked loop (PLL) receiver is disclosed. It includes a local oscillator, which sweeps the receiver to tune across the carrier frequency uncertainty range until the carrier crosses the receiver IF reference. Such crossing is detected by an automatic acquisition detector. It receives the IF signal from the receiver as well as the IF reference. It includes a pair of multipliers which multiply the IF signal with the IF reference in phase and in quadrature. The outputs of the multipliers are filtered through bandpass filters and power detected. The output of the power detector has a signal dc component which is optimized with respect to the noise dc level by the selection of the time constants of the filters as a function of the sweep rate of the local oscillator.

Bunce, R. C.↗
DOE OSTI2022

Local Atomic Configuration Control of Superconductivity in the Undoped Pnictide Parent Compound BaFe 2 As 2

Emergent superconductivity is strongly correlated with the symmetry of local atomic configuration in the parent compounds of iron-based superconductors. While chemical doping or hydrostatic pressure can change the local geometry, conventional approaches do not provide a clear pathway in predictably tuning the detailed atomic arrangement due to the parent compound’s complicated structural deformation in the presence of the tetragonal-to-orthorhombic phase transition. Here, we demonstrate a systematic approach to manipulate local structural configurations in BaFe 2 As 2 epitaxial thin films by controlling two independent structural factors, orthorhombicity (in-plane anisotropy) and tetragonality (out-of-plane/in-plane balance), from lattice parameters. We tune superconductivity without doping utilizing both structural factors separately and controlling local tetrahedral coordination in the designed thin film heterostructures with substrate clamping and biaxial strain. We further show this allows quantitative control of the structural phase transition, the associated magnetism, and superconductivity in parent material BaFe 2 As 2 . Furthermore, this approach will advance the development of tunable thin film superconductors in a reduced dimension.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗