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At least 55 records · Page 3

Prediction of Drag Reduction in Supersonic and Hypersonic Flows with Counterflow Jets

Computational fluid dynamics solutions of the flowfield of a truncated cone-cylinder with and without counterflow jets have been obtained for the short penetration mode (SPM) and long penetration mode (LPM) of the freestream-counterflow jet interaction flowfield. For the case without the counterflow jet, the comparison of the normalized surface pressures showed very good agreement with experimental data. For the case with the SPM jet, the predicted surface pressures did not compare as well with the experimental data upstream of the expansion corner, while aft of the expansion corner, the comparison of the solution and the data is seen to give much better agreement. The difference in the prediction and the data could be due to the transient character of the jet penetration modes, possible effects of the plasma physics that are not accounted for here, or even the less likely effect of flow turbulence, etc. For the LPM jet computations, one-dimensional isentropic relations were used to derived the jet exit conditions in order to obtain the LPM solutions. The solution for the jet exit Mach number of 3 shows a jet penetration several times longer than that of the SPM, and therefore much weaker bow shock, with an attendant reduction in wave drag. The LPM jet is, in essence, seen to be a "pencil" of fluid, with much higher dynamic pressure, embedded in the oncoming supersonic or hypersonic freestream. The methodology for determining the conditions for the LPM jet could enable a practical approach for the design and application of counterflow LPM jets for the reduction of wave drag and heat flux, thus significantly enhancing the aerodynamic characteristics and aerothermal performance of supersonic and hypersonic vehicles. The solutions show that the qualitative flow structure is very well captured. The obtained results, therefore, suggest that counterflowing jets are viable candidate technology concepts that can be employed to give significant reductions in wave drag, heat flux, and other attendant aerodynamic benefits.

Daso, Endwell O.↗

Use of phosphoimidazolide-activated guanosine to investigate the nucleophilicity of spermine and spermidine

Guanosine 5'-phosphate 2-methylimidazolide (2-MeImpG), a labile phosphoimidazolide analog of guanosine triphosphate, was used to test the reactivity of the natural polyamines (PAs), spermine (spm) and spermidine (spd). The products are the guanosine 5'-phosphate-polyamine derivatives (PA-pG: spd-pG and spm-pG) which are quite stable in the range 4 < pH < 11. Our study is the first of which we are aware that reports on the nucleophilicity of these amines. The main findings are as follows. (i) HPLC analysis of the products indicates the formation of only two of the three possible spd products and only one of the two possible spm products. These results can be explained if only the primary amino groups of the two polyamines are reactive, while the secondary amino groups are rendered unreactive by a steric effect. The reactions of 2-MeImpG and other phosphoimidazolide derivatives of nucleosides (ImpNs) with primary and secondary monoamines support this interpretation (Kanavarioti et al. J. Org. Chem. 1995, 60, 632). (ii) The product ratio of the two spd-pG adducts derived from the primary amino groups varies between 2.40 and 0.71 in the range 6.1 < or equal to pH < or equal to 11.9. Such small variation in the product ratio can only be rationalized by the similar, but not identical, basicity of the two primary amino groups and provides strong support for a previously reported model for polyamine ionization (Onasch et. al. Biophys. Chem. 1984, 19, 245). (iii) On the basis of our kinetic determinations conditions at which the nucleophilicity of these amines is at a minimum and at which other interactions with ImpNs could be tested can be chosen.

NASA Discipline Exobiology↗

Monolithically Integrated, Mechanically Resilient Carbon-Based Probes for Scanning Probe Microscopy

Scanning probe microscopy (SPM) is an important tool for performing measurements at the nanoscale in imaging bacteria or proteins in biology, as well as in the electronics industry. An essential element of SPM is a sharp, stable tip that possesses a small radius of curvature to enhance spatial resolution. Existing techniques for forming such tips are not ideal. High-aspect-ratio, monolithically integrated, as-grown carbon nanofibers (CNFs) have been formed that show promise for SPM applications by overcoming the limitations present in wet chemical and separate substrate etching processes.

Kaul, Anupama B.↗

An Evaluation of a Passively Cooled Cylindrical Spectrometer Array in Lunar Orbit

This thesis will evaluate a passively cooled cylindrical spectrometer array in lunar orbit characterizing the thermal response in order to provide context for decision-making to scientists and engineers. To provide perspective on thermal issues and controls of space science instruments, a background search of historical lunar missions is provided. Next, a trial science mission is designed and analyzed which brings together the elements of the background search, lunar orbit environment and passive cooling. Finally, the trial science mission analysis results are provided along with the conclusions drawn. Scintillators are materials that when struck by particle radiation, absorb the particle energy which is then reemitted as light in or near the visible range. Nuclear astrophysics utilizes scintillating materials for observation of high-energy photons which are generated by sources such as solar flares, supernovae and neutron stars. SPMs are paired with inorganic scintillators to detect the light emitted which is converted into electronic signals. The signals are captured and analyzed in order to map the number and location of the high-energy sources. The SPM is utilized as it has single photon sensitivity, low voltage requirements and a fast response. SPMs are also compact, relatively inexpensive and allow the usage of lower-cost scintillating materials within the spectrometer. These characteristics permit large-area arrays while lowering cost and power requirements. The ability of a spectrometer to record and identify the interaction of high-energy photons for scientific return is not a trivial matter. Background noise is generated when particles that have not originated from the desired distant source impact the spectrometer. Additionally, thermally induced electrical signals are randomly generated within the SPM even in the absence of light which is referred to as dark current. Overcoming these obstacles requires greater light emittance and energy resolution with reduced dark current. Strong scintillation photon emittance ensures that low energy impacts will produce enough visible photons to be detected by the SPM. Higher energy resolution will ensure that single photon impacts can be distinguished from others of similar wavelength and energy; reduced dark current decreases the generation of random signals not associated with a photon impact. Increasing efficiency in each of these properties in a spectrometer comprised of inorganic scintillators and SPMs requires low temperatures. Low temperature maintenance in a lunar environment presents many unique challenges of its own. Even with the accumulated successes of past missions, the lunar environment remains a thermal challenge for engineers. The lunar orbit thermal environment is driven by radiation from three sources, direct solar radiation, reflected solar radiation from the lunar surface (albedo) and lunar radiation (Clawson 2002). Direct solar radiation values are consistent with those seen in Earth orbit (1325 W/m2) (Clawson 2002). The percentage of solar radiation reflected from the moon is consistently very low with the moon's dark regolith covered surface absorbing nearly 90% of the incident light (Clawson 2002). Yet, it is this absorption that gives the lunar orbit environment one of its most difficult thermal attributes as the absorbed solar radiation is released from the lunar surface as infrared radiation (IR). IR is of a wavelength that is readily absorbed by surfaces designed to function as radiation emitters. It is practical to therefore "choose radiator locations and spacecraft attitude to minimize radiator views to the lunar surface, when possible...pointing the radiator towards the sun to some extent, to minimize its view to the lunar surface, is frequently preferable. (Clawson 2002)" Additionally, the amount of direct solar radiation, lunar IR and albedo an orbiting satellite receives varies from one side of the moon to the other as the moon blocks the sun from view. This environment produces large temperature variations in a satellite's instrumentation, control electronics and propulsion systems which must be understood to characterize operating temperature envelopes.

Waggoner, Jason↗

Parameters Inference and Model Reduction for the Single-Particle Model of Li Ion Cells

The Single-Particle Model (SPM) of Li ion cell is a computationally efficient model for simulating Li ion cell for weak to moderate currents. The model depends n a number of parameters describing the geometry and material properties of a cell components. In order to apply the model to simulating a cell, the best-fit parametric values have to be inferred from a constant discharge data. We report our efforts to determine the best-fit set for 18650 LP batteries. We found that rather than being best-fit by a particular point in the parametric space the data is fit equally well by an ensemble of points clustering about an effective multidimensional manifold in the parametric space. This property of the SPM is known to be shared by a multitude of the so-called "sloppy models" of complex systems, characterized by a few stiff directions in the parametric space, in which the predicted behavior varies significantly, and a number of sloppy directions in which the behavior doesn't change appreciably. Only the stiff parameters combinations are identifiable. Geometrical features of the BFM give insights to possible reduction of the SPM to a model having fewer sloppy parameters. We have constructed a hierarchy of such models. The fully reduced model depends on only stiff effective parameters which are identifiable and can be used for characterization of the battery's state of health.

Khasin, Michael↗

Design of High Power Density 100 kW Surface Permanent Magnet Machine with No Heavy Rare Earth Material Using Current Source Inverter for Traction Application

Surface permanent magnet (SPM) machines are appealing candidates for traction applications because of high power density and high efficiency. Rare-earth magnets deliver high performance but raise concerns about material supply dependability, particularly if they use heavy rare-earth materials. This paper presents the design of a high-performance SPM machine without any heavy rare-earth material that is optimized specifically for a current-source inverter (CSI) traction drive. This machine is designed for a constant-power speed ratio (CPSR) of 3. A genetic algorithm has been performed to achieve a target of 50 kW/L active power density at speeds up to 20,000 rpm. Operation at a peak line-to-line voltage of 800 V can be achieved using 1200 V power devices with a safety margin. The predicted electromagnetic and rotor structural performance characteristics are presented using both analytical and finite element analysis (FEA) results.

(CPSR)↗

Exploring Physics of Ferroelectric Domain Walls in Real Time: Deep Learning Enabled Scanning Probe Microscopy

The functionality of ferroelastic domain walls in ferroelectric materials is explored in real-time via the in situ implementation of computer vision algorithms in scanning probe microscopy (SPM) experiment. The robust deep convolutional neural network (DCNN) is implemented based on a deep residual learning framework (Res) and holistically nested edge detection (Hed), and ensembled to minimize the out-of-distribution drift effects. The DCNN is implemented for real-time operations on SPM, converting the data stream into the semantically segmented image of domain walls and the corresponding uncertainty. Further the pre-defined experimental workflows perform piezoresponse spectroscopy measurement on thus discovered domain walls, and alternating high- and low-polarization dynamic (out-of-plane) ferroelastic domain walls in a PbTiO 3 (PTO) thin film and high polarization dynamic (out-of-plane) at short ferroelastic walls (compared with long ferroelastic walls) in a lead zirconate titanate (PZT) thin film is reported. This work establishes the framework for real-time DCNN analysis of data streams in scanning probe and other microscopies and highlights the role of out-of-distribution effects and strategies to ameliorate them in real time analytics.

36 MATERIALS SCIENCE↗

A Robust Neural Network for Extracting Dynamics from Electrostatic Force Microscopy Data

Advances in scanning probe microscopy (SPM) methods such as time-resolved electrostatic force microscopy (trEFM) now permit the mapping of fast local dynamic processes with high resolution in both space and time, but such methods can be time-consuming to analyze and calibrate. Here, we design and train a regression neural network (NN) that accelerates and simplifies the extraction of local dynamics from SPM data directly in a cantilever-independent manner, allowing the network to process data taken with different cantilevers. We validate the NN’s ability to recover local dynamics with a fidelity equal to or surpassing conventional, more time-consuming, calibrations using both simulated and real microscopy data. We apply this method to extract accurate photoinduced carrier dynamics on n = 1 butylammonium lead iodide, a halide perovskite semiconductor film that is of interest for applications in both solar photovoltaics and quantum light sources. Lastly, we use SHapley Additive exPlanations to evaluate the robustness of the trained model, confirm its cantilever-independence, and explore which parts of the trEFM signal are important to the network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autonomous Molecular Structure Imaging with High-Resolution Atomic Force Microscopy for Molecular Mixture Discovery

Due to its single-molecule sensitivity, high-resolution atomic force microscopy (HR-AFM) has proved to be a valuable and uniquely advantageous tool to study complex molecular mixtures, which hold promise for developing clean energy and achieving environmental sustainability. However, significant challenges remain to achieve the full potential of the sophisticated and time-consuming experiments. Automation combined with machine learning (ML) and artificial intelligence (AI) is key to overcoming these challenges. Here we present Auto-HR-AFM, an AI tool to automatically collect HR-AFM images of petroleum-based mixtures. In this study, we trained an instance segmentation model to teach Auto-HR-AFM how to recognize features in HR-AFM images. Auto-HR-AFM then uses that information to optimize the imaging by adjusting the probe-molecule distance for each molecule in the run. Auto-HR-AFM is the initial tool that will lead to fully automated scanning probe microscopy (SPM) experiments, from start to finish. This automation will allow SPM to become a mainstream characterization technique for complex mixtures, an otherwise unattainable target.

36 MATERIALS SCIENCE↗

Exploring the Relationship of Microstructure and Conductivity in Metal Halide Perovskites via Active Learning-Driven Automated Scanning Probe Microscopy

Electronic transport and hysteresis in metal halide perovskites (MHPs) are key to the applications in photovoltaics, light emitting devices, and light and chemical sensors. These phenomena are strongly affected by the materials microstructure including grain boundaries, ferroic domain walls, and secondary phase inclusions. Here, we demonstrate an active machine learning framework for “driving” an automated scanning probe microscope (SPM) to discover the microstructures responsible for specific aspects of transport behavior in MHPs. In our setup, the microscope can discover the microstructural elements that maximize the onset of conduction, hysteresis, or any other characteristic that can be derived from a set of current–voltage spectra. Furthermore, this approach opens new opportunities for exploring the origins of materials functionality in complex materials by SPM and can be integrated with other characterization techniques either before (prior knowledge) or after (identification of locations of interest for detail studies) functional probing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autonomous Experiments in Scanning Probe Microscopy and Spectroscopy: Choosing Where to Explore Polarization Dynamics in Ferroelectrics

Polarization dynamics in ferroelectric materials are explored via automated experiment in piezoresponse force microscopy/spectroscopy (PFM/S). A Bayesian optimization (BO) framework for imaging is developed, and its performance for a variety of acquisition and pathfinding functions is explored using previously acquired data. The optimized algorithm is then deployed on an operational scanning probe microscope (SPM) for finding areas of large electromechanical response in a thin film of PbTiO 3 , with results showing that, with just 20% of the area sampled, most high-response clusters were captured. Furthermore, this approach can allow performing more complex spectroscopies in SPM that were previously not possible due to time constraints and sample stability. Improvements to the framework to enable the incorporation of more prior information and improve efficiency further are modeled and discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-resolved broadband impulsive stimulated Brillouin scattering in single crystal hematite

Impulsive stimulated Brillouin scattering (ISBS) has emerged as a noninvasive means to determine the elastic properties of transparent materials. Here, we report on time-resolved broadband ISBS reflectivity measurements in single crystal hematite, α-Fe 2 O 3 . We found that the observed transient reflectivity changes are best described by the known strain propagation model (SPM) and introduced a simple derivation of the ISBS-SPM formula based on ray tracing, which accounts for the presence of the interface. Additionally, measurements at different incident probe beam angles illustrate a plausible approach toward determining the speed of sound in transparent media without any prior knowledge of their dielectric properties and vice versa.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fabrication of pristine 2D heterostructures for scanning probe microscopy

Material-by-design has been a long-standing aspiration that has recently become a reality. Such designer materials have been repeatedly demonstrated using the top-down approach of mechanical exfoliation and stacking, leading to a variety of artificial 2D heterostructures with new properties that are otherwise unattainable. Consequently, tremendous research frontiers in physics, chemistry, engineering, and life science have been created. While thousands of layered crystals exist in nature, only a few dozen of them with manageable chemical-stability have been made into heterostructures using this method. Moreover, experimental investigations of materials that have received limited exploration in the 2D realm, such as cuprates, halides, and perovskites, along with their heterostructures, have been fundamentally hindered by their rapid chemical degradation. Another critical challenge imposed by exfoliating and stacking 2D layers in ambient environment is the absorption of itinerant gas molecules that further contaminate sensitive 2D interfaces in the heterostructures. Such contamination and compromised material properties significantly hinder surface-sensitive local probes—scanning probe microscopy (SPM)—that often require nanometer to atomic scale surface cleanliness. In this article, we aim to provide a technical review of recent development toward 2D materials and heterostructure fabrication in more controlled environments that are suitable for SPM characterizations. These include the development of more efficient mechanical exfoliation and dry-transfer techniques, as well as the incorporation of 2D material exfoliation and transfer in inert gas, low vacuum, and, eventually, ultra-high vacuum environments. Finally, we provide an outlook on the remaining challenges and opportunities in ultra-clean 2D material fabrication techniques.

Materials Science↗

Reward based optimization of resonance-enhanced piezoresponse spectroscopy

Dynamic spectroscopies in scanning probe microscopy (SPM) are critical for probing material properties, such as force interactions, mechanical properties, polarization switching, electrochemical reactions, and ionic dynamics. However, the practical implementation of these measurements is constrained by the need to balance imaging time and data quality. Signal to noise requirements favor long acquisition times and high frequencies to improve signal fidelity. However, these are limited on the low end by contact resonant frequency and photodiode sensitivity and on the high end by the time needed to acquire high-resolution spectra or the propensity for sample degradation under high field excitation over long times. The interdependence of key parameters such as instrument settings, acquisition times, and sampling rates makes manual tuning labor-intensive and highly dependent on user expertise, often yielding operator-dependent results. These limitations are prominent in techniques like dual amplitude resonance tracking in piezoresponse force microscopy that utilize multiple concurrent feedback loops for topography and resonance frequency tracking. Here, a reward-driven workflow is proposed that automates the tuning process, adapting experimental conditions in real time to optimize data quality. Furthermore, this approach significantly reduces the complexity and time required for manual adjustments and can be extended to other SPM spectroscopic methods, enhancing overall efficiency and reproducibility.

47 OTHER INSTRUMENTATION↗

Effect of focused nanosecond laser pulse irradiation on microtribological properties of diamond-like films

We have examined the effect of focused nanosecond laser pulses on the formation and tribological properties of microstructures in the form of a matrix of craters produced in a – C : H : Si : O diamond-like films (DLFs), both undoped and doped with tungsten. The studies are performed by scanning probe microscopy (SPM) using SPM probes of standard design with a tip and probes without a tip (tipless-type probes). A special procedure is developed for assessing the wettability (contact angle) of individual sections of the laser-induced microstructure by the local adhesion force. According to estimates, the material inside the crater becomes softer and more hydrophobic as a result of laser irradiation. This is manifested to the greatest extent in tungsten-doped DLFs, where the crater walls are arranged like terraces formed by ‘nanoflakes’, i.e. grains of the substance. Scanning of microstructures with a tipless probe in the regime of lateral force microscopy demonstrates a decrease in friction in the crater area. (interaction of laser radiation with matter. laser plasma)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Design and Comparison of Surface Inset Permanent Magnet Machine and Surface Permanent Magnet Machine without Heavy Rare Earth Magnets for Traction Applications

This paper presents two machine designs: a surface inset permanent magnet (SIPM) machine and a surface permanent magnet (SPM) machine, both without heavy rare-earth magnets, that achieve 50 kW/L active power density and a constant-power speed ratio of 3 for EV traction applications. Compared to surface PM machines, SIPM machines do not require a special containment sleeve to hold the magnets in place at high speeds, provided that the rotor laminations are carefully designed together with the magnet mounting configuration to ensure the rotor’s structural integrity. Comparisons between the SPM and SIPM machines sharing the same stator, same current level, and same power speed envelope are presented. Both deliver very similar performance characteristics, but the SIPM machine’s simpler magnet containment configuration may give it an advantage in terms of reduced material and manufacturing costs.

42 ENGINEERING↗

Advancing Reel-to-Reel Inspection Techniques for Long HTS Conductors: Comparison and Innovations

The continuous advancement of high-temperature superconductor (HTS) technologies has greatly accelerated the development and deployment of HTS applications. Among the critical tools supporting these advancements are reel-to-reel (R2R) critical current (I c ) measurement techniques, which are extensively used by both manufacturers and end users to characterize long-length REBCO conductors. These techniques play a vital role in quality assurance and quality control (QA/QC), ensuring the reliability and performance of HTS conductors and applications throughout the production cycle. We have developed a range of in-house devices for R2R measurements at the University of Houston and Princeton Plasma Physics Laboratory. These include one-dimensional (1D) scan using a magnetic circuit (MC) and two-dimensional (2D) magnetic field mapping systems based on scanning probe array microscope (SPAM) or scanning probe microscopy (SPM). Each technique offers distinct advantages: the MC system provides ultra-fast scanning speeds, ideal for rapid inspection in large-scale industrial production; the high-resolution SPM delivers detailed insights for conductor research and development; and the SPAM, with its simpler mechanical setup, can be upgraded for higher field and lower temperature conditions with a balanced 2D resolution. Here we compared the magnetization and detection capabilities of these techniques through experiments on rare-earth barium copper oxide (REBCO) coated conductor samples, with data analysis supported by numerical simulations. Based on our comprehensive comparative studies, we propose enhancements for each measurement system and provide guidelines for selecting the optimal technique combinations to meet specific application requirements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗