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Time-reversed Young’s experiment: Deterministic, diffractionless second-order interference effect
The classic Young’s double-slit experiment exhibits first-order interference, producing alternating bright and dark fringes shaped by the diffraction effect of the slits. In contrast, here we demonstrate that its time-reversed configuration generates an ideal, deterministic second-order ‘ghost’ interference pattern free from diffraction and first-order effects with the use of only a position-fixed detector. The pattern’s size is governed by the dimensions of the ‘effectively extended light source’ formed by point emitter(s). Beyond highlighting the nonreciprocal physics between the two configurations, this system unlocks a range of novel phenomena inaccessible in traditional double-slit experiments. These include fully programmable, digitized interference fringe formations and the ability to align the pattern plane with the source plane on the same side of the setup. Remarkably, our proposed experiment achieves these outcomes without relying on nonclassical correlations or quantum entanglement. Here, by restoring time-reversal symmetry and eliminating diffraction, our theoretical analysis reveals that this approach offers exciting potential for advancing optical imaging and sensing technologies with improved transverse and longitudinal phase-shift sensitivity and resolution limit beyond current limitations.
Wind turbine blade material in the United States: Quantities, costs, and end-of-life options
Wind energy has experienced enormous growth in the past few decades; as a result, there are thousands of wind turbines around the world that will reach the end of their design lifetimes in the coming years. Much of the material in those turbines can be recycled using conventional processes, but the composite material that is the main component of the blades is more challenging to recycle. In the United States, turbine blades may be disposed of in landfills, adding a new solid waste stream to the material already being landfilled. This paper presents a spatially resolved estimate of the mass and volume of wind turbine blade waste in each state by 2050 and compares these amounts to estimates of the remaining landfill capacity by state. In this work, we estimate costs for each stage of the disposal process to indicate cost levels for alternatives. Assuming a 20-year turbine lifetime, the cumulative blade waste in 2050 is approximately 2.2 million tons. This value represents approximately 1% of remaining landfill capacity by volume, or 0.2% by mass. We also find that the current cost of disposing of blades in large segments or through grinding is relatively low in comparison to the overall life-cycle cost of energy. Based on these findings, landfill space constraints and disposal costs appear unlikely to motivate a change in waste handling strategies under current policy conditions. Instead, more profound shifts in recycling technologies, blade materials, or policy may be needed to move towards a circular economy for wind turbine blades.
Dynamic Tuning of a Thin Film Electrocatalyst by Tensile Strain
We report the ability to tune the catalytic activities for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) by applying mechanical stress on a highly n-type doped rutile TiO 2 films. We demonstrate through operando electrochemical experiments that the low HER activity of TiO 2 can reversibly approach those of the state-of-the-art non-precious metal catalysts when the TiO2 is under tensile strain. At 3% tensile strain, the HER overpotential required to generate a current density of 1 mA/cm 2 shifts anodically by 260 mV to give an onset potential of 125 mV, representing a drastic reduction in the kinetic overpotential. A similar albeit smaller cathodic shift in the OER overpotential is observed when tensile strain is applied to TiO 2 . Results suggest that significant improvements in HER and OER activities with tensile strain are due to an increase in concentration of surface active sites and a decrease in kinetic and thermodynamics barriers along the reaction pathway(s). Our results highlight that strain applied to TiO 2 by precisely controlled and incrementally increasing (i.e. dynamic ) tensile stress is an effective tool for dynamically tuning the electrocatalytic properties of HER and OER electrocatalysts relative to their activities under static conditions.
Modeling of frequency-sweeping Alfvén modes in the TJ-II stellarator
Alfvénic activity has been observed in the TJ-II stellarator which resembles the frequency sweeping demonstrated by Alfvén cascade modes in tokamaks. A numerical validation study was conducted using a reduced magnetohydrodynamic (MHD) model to show that such modes could only have been observed in discharges where the rotational transform profile was non-monotonic. During experiments, coil current was varied which resulted in shifting of the minimum value of the rotational transform profile. To mimic this effect, we study the Alfvénic activity predicted by the reduced MHD model for a set of input rotational transform profiles with varying minima. A mode is found whose toroidal and poloidal mode numbers match those predicted in experiments which sweeps downward/upward in frequency as the minimum value of the rotational transform profile is increased/decreased. The results serve as a demonstration of the validity and utility of MHD spectroscopy.
Casimir interactions between two parallel graphene sheets carrying steady-state drift currents
Here, we investigate the fluctuation-induced Casimir interactions between two parallel graphene sheets carrying steady-state drift currents. The graphene properties are modeled based on the shifted Fermi disk model to capture the nonequilibrium optical response of the system. We find that the drift current introduces a repulsive correction to the perpendicular to the layers Casimir interaction, thereby reducing the overall attractive force. Although the correction is repulsive, it does not overcome the underlying attraction between the layers. It also generates a lateral force that opposes the carrier flow direction. Both contributions are studied in terms of distance and drift velocity functionalities showing pathways for Casimir force control.
Dissimilar responses of fungal and bacterial communities to soil transplantation simulating abrupt climate changes
Both fungi and bacteria play necessary roles in regulating soil carbon cycling. To implement future carbon stability, it is imperative to understand their responses to environmental changes, which is subject to large uncertainty. As current global warming is causing range shifts toward higher latitudes, we conducted three reciprocal soil transplantation experiments over large transects in 2005 to simulate abrupt climate changes. Six years after soil transplantation, fungal biomass of transplanted soils showed a general pattern of changes from donor sites to destination, which were more obvious in bare fallow soils than in maize cropped soils. Strikingly, fungal community compositions were clustered by sites, demonstrating that fungi of transplanted soils acclimatized to the destination environment. Several fungal taxa displayed sharp changes in relative abundance, including Podospora, Chaetomium, Mortierella and Phialemonium. In contrast, bacterial communities remained largely unchanged. Consistent with the important role of fungi in affecting soil carbon cycling, 8.1%-10.0% of fungal genes encoding carbon-decomposing enzymes were significantly (p < 0.01) increased as compared with those from bacteria (5.7%-8.4%). To explain these observations, we found that fungal occupancy across samples was mainly determined by annual average air temperature and rainfall, whereas bacterial occupancy was more closely related to soil conditions, which remained stable 6 years after soil transplantation. Together, these results demonstrate dissimilar response patterns and resource partitioning between fungi and bacteria, which may have considerable consequences for ecosystem-scale carbon cycling.
Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete
Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.
An evaluation of noise and its effects on shuttle crewmembers during STS-50/USML-1
High noise levels can lead to physiological, psychological, and performance effects in man, ranging from irritability, annoyance, and sleep interference to interference with verbal communication and fatigue, and to temporary or permanent threshold shift at more extreme levels. The current study evaluated the acoustic environment of the STS50/USML-1 mission. The major objectives were to gain subjective assessments of the STS-50 noise levels, document impacts of noise upon crewmember performance, collect inflight sound level measurements, compare noise levels across missions, evaluate the current Shuttle acoustic criterion, and to make recommendations regarding noise specifications for SSF and other long-duration manned space missions. Sound measurements indicated that background noise levels were 60, 64, and 61 A-weighted decibels, respectively, on the Orbiter middeck, flight deck, and Space lab. All levels were rated acceptable, with the Spacelab environment rated the most favorably. Sleep stations afforded attenuation from airborne noise sources, although all crewmembers reported being awakened by crew activity on the middeck. Models of distance for acceptable speech communications were generated, identifying situations of compromised verbal communications to be avoided.
Fault Tolerant Characteristics of Artificial Neural Network Electronic Hardware
The fault tolerant characteristics of analog-VLSI artificial neural network (with 32 neurons and 532 synapses) chips are studied by exposing them to high energy electrons, high energy protons, and gamma ionizing radiations under biased and unbiased conditions. The biased chips became nonfunctional after receiving a cumulative dose of less than 20 krads, while the unbiased chips only started to show degradation with a cumulative dose of over 100 krads. As the total radiation dose increased, all the components demonstrated graceful degradation. The analog sigmoidal function of the neuron became steeper (increase in gain), current leakage from the synapses progressively shifted the sigmoidal curve, and the digital memory of the synapses and the memory addressing circuits began to gradually fail. From these radiation experiments, we can learn how to modify certain designs of the neural network electronic hardware without using radiation-hardening techniques to increase its reliability and fault tolerance.
Human Research Program Human Health Countermeasures Element Cardiovascular Risks Standing Review Panel (SRP)
The Cardiovascular Risk Standing Review Panel (SRP) evaluated several cardiovascular risks associated with space flight along with the ongoing and emerging plans to study these issues and potentially propose and/or develop countermeasures. The areas of focus included: 1) The risk of cardiac rhythm problems during prolonged space flight, and 2) Issues related to the risk of orthostatic intolerance during re-exposure to gravity. An emerging area of concern is radiation associated vascular injury. The risk of cardiac rhythm disturbances has emerged based on case reports only. No systematic study of this risk has been published. However, concerns about this risk are heightened by the age range of astronauts, the structural changes in the heart that occur during space flight, and the potential shifts in fluids and electrolytes. The current plan is to use prolonged Holter monitor EKG records made as part of the "Integrated Cardiovascular SMO" in space to determine more about the frequency and magnitude of this problem and to link this data to complementary data from the nutrition group on electrolytes. The SRP was supportive of this approach. The SRP also felt that any data related to cardiovascular risk in space should be better coordinated with the medical screening data that all astronauts undergo at regular intervals. Additionally, while there are potential privacy issues related to this suggestion, many of the current barriers to better coordination of experimental and clinical data appear to reflect longstanding cultural traditions at NASA that need rethinking. The risk of orthostatic intolerance during re-exposure to gravity was seen by the SRP as an area supported by a wealth of published physiological evidence. The SRP also felt that moving forward with the planned approach to countermeasures was reasonable and that extensive additional hypothesis testing on the physiology of orthostatic intolerance was not needed at this time. There was support for developing ground based models of limited (e.g. 1/6 th) G environments on Earth that generated a number of ideas for consideration by NASA investigators.
Using Lag Compensator in Orbit Feedback
Growing demand on the beam orbit stability requires higher loop gain inside the operational bandwidth. However, increasing the gain leads to the increase of the unity gain frequency and problems with systems stability due to the additional phase shifts caused by the trims (power supplies, eddy currents in vacuum chambers, etc.) and filtering of beam position data. Conventionally employed systems have 20 dB/decade slope near the unity gain providing 90 degrees phase shift which is sufficient for stability. Increase of the slope to 40 dB/decade by adding additional pole into the signal chain increases the phase shift to 180 degrees and makes system unstable. Utilizing one or more lag compensators allows to increase the gain while keeping phase margin acceptable. The paper provides more details on the proposed solution as well as simulations of how the transients will be modified.
Total-Ionizing-Dose Effects and Low-Frequency Noise in 16-nm InGaAs FinFETs With HfO 2 /Al 2 O 3 Dielectrics
Here, total-ionizing-dose mechanisms are investigated in 16-nm InGaAs FinFETs with an HfO 2 /Al 2 O 3 gate-stack. Transistors are irradiated up to 500 krad(SiO 2 ) and annealed at high temperatures. Irradiated devices show negative threshold-voltage V th shifts, subthreshold stretch-out, and leakage current increases. These result from positive charge trapping in the gate oxide and shallow trench insulators, and increases in the interface and border-trap charge densities. Low-frequency noise measurements at different temperatures indicate a significant increase of noise magnitude in irradiated devices at an activation energy of ~0.4 eV. Density functional theory (DFT) calculations strongly suggest that transistor V th shifts are due primarily to hole trapping at oxygen vacancies in HfO 2 , and the increased noise is due primarily to O vacancies in Al 2 O 3 . Additional contributions to the noise from defects in the GaAs buffer layer are also likely, primarily at low temperatures.
Field-aligned currents associated with substorms in the vicinity of synchronous orbit. I - The July 5, 1979, substorm observed by SCATHA, GOES 3, and GOES 2
Magnetic field topology and field-aligned current signatures in the vicinity of synchronous orbit are examined for a substorm on July 5, 1979. Changes from taillike to dipolar field geometry propagate earthward near the midnight meridian during the substorm. The major field-aligned currents producing a negative D perturbation at and around synchronous orbit are downward currents flowing into the auroral ionosphere on L shells greater than the synchronous spacecraft L shell. Although these currents are located initially on higher L shells, they shift toward the lower L shells as the change from taillike to dipolar fields propagates earthward. There may exist upward field-aligned currents located on smaller L shells in the limited longitudinal region near the meridian where mid-latitude D perturbations change their sign.
Expansion-based passive ranging
A new technique of passive ranging which is based on utilizing the image-plane expansion experienced by every object as its distance from the sensor decreases is described. This technique belongs in the feature/object-based family. The motion and shape of a small window, assumed to be fully contained inside the boundaries of some object, is approximated by an affine transformation. The parameters of the transformation matrix are derived by initially comparing successive images, and progressively increasing the image time separation so as to achieve much larger triangulation baseline than currently possible. Depth is directly derived from the expansion part of the transformation. To a first approximation, image-plane expansion is independent of image-plane location with respect to the focus of expansion (FOE) and of platform maneuvers. Thus, an expansion-based method has the potential of providing a reliable range in the difficult image area around the FOE. In areas far from the FOE the shift parameters of the affine transformation can provide more accurate depth information than the expansion alone, and can thus be used similarly to the way they were used in conjunction with the Inertial Navigation Unit (INU) and Kalman filtering. However, the performance of a shift-based algorithm, when the shifts are derived from the affine transformation, would be much improved compared to current algorithms because the shifts - as well as the other parameters - can be obtained between widely separated images. Thus, the main advantage of this new approach is that, allowing the tracked window to expand and rotate, in addition to moving laterally, enables one to correlate images over a very long time span which, in turn, translates into a large spatial baseline - resulting in a proportionately higher depth accuracy.
Expansion-based passive ranging
This paper describes a new technique of passive ranging which is based on utilizing the image-plane expansion experienced by every object as its distance from the sensor decreases. This technique belongs in the feature/object-based family. The motion and shape of a small window, assumed to be fully contained inside the boundaries of some object, is approximated by an affine transformation. The parameters of the transformation matrix are derived by initially comparing successive images, and progressively increasing the image time separation so as to achieve much larger triangulation baseline than currently possible. Depth is directly derived from the expansion part of the transformation. To a first approximation, image-plane expansion is independent of image-plane location with respect to the focus of expansion (FOE) and of platform maneuvers. Thus, an expansion-based method has the potential of providing a reliable range in the difficult image area around the FOE. In areas far from the FOE the shift parameters of the affine transformation can provide more accurate depth information than the expansion alone, and can thus be used similarly to the way they have been used in conjunction with the Inertial Navigation Unit (INU) and Kalman filtering. However, the performance of a shift-based algorithm, when the shifts are derived from the affine transformation, would be much improved compared to current algorithms because the shifts--as well as the other parameters--can be obtained between widely separated images. Thus, the main advantage of this new approach is that, allowing the tracked window to expand and rotate, in addition to moving laterally, enables one to correlate images over a very long time span which, in turn, translates into a large spatial baseline resulting in a proportionately higher depth accuracy.
The Large-Scale Current System During Auroral Substorms
We present an empirical model of the equivalent current system in the ionosphere during the peak of a classical bulge-type auroral sub storm. This model is derived from measurements made by ~110 ground magnetometer stations during 116 substorms. The data are temporally and spatially organized using global auroral images obtained by the Polar Visible Imaging System Earth Camera. The empirical equivalent current system displays three key features: a poleward shift of the westward electrojet connecting the postmidnight and premidnight components; a polar cap swirl; and significantly different magnitudes of the postmidnight and premidnight westward electrojets. This leads us to propose a two-wedge current system linking the ionosphere to the magnetosphere. The bulge current wedge is located in the premidnight region just equatorward of the open-closed field line boundary while another three-dimensional current system is located in the postmidnight region well within the auroral oval. We use Biot and Savart calculations and Tsyganenko mapping and show that this new model is a likely solution for the large-scale current system.