Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “memory effects”

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 1,621 records · Page 90

Thickness independent reduced forming voltage in oxygen engineered HfO{sub 2} based resistive switching memories

The conducting filament forming voltage of stoichiometric hafnium oxide based resistive switching layers increases linearly with layer thickness. Using strongly reduced oxygen deficient hafnium oxide thin films grown on polycrystalline TiN/Si(001) substrates, the thickness dependence of the forming voltage is strongly suppressed. Instead, an almost constant forming voltage of about 3 V is observed up to 200 nm layer thickness. This effect suggests that filament formation and switching occurs for all samples in an oxidized HfO{sub 2} surface layer of a few nanometer thickness while the highly oxygen deficient thin film itself merely serves as a oxygen vacancy reservoir.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Complexity reduction effects on transient, atomic plasmas

Plasma simulations involving collisional-radiative processes present many computational challenges because of the wide range in scales spanned by the governing set of plasma physics equations. These numerical challenges are primarily caused by limitations in resources such as memory and computational time. Collisional-radiative models deliver a part of the challenge because of the large number of levels and transitions that are associated with atomic plasmas. Multiple complexity reduction techniques have been introduced in the past to overcome this obstacle, including the quasi-steady-state solution, uniform grouping, and the recently-devised Boltzmann grouping. These reduction schemes were tested against full numerical simulations of a simplified, time-dependent argon model, with and without an external Planckian radiation field. Lastly, results will show the advantages and disadvantages of using complexity reduction techniques when employed in various plasma regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Caloric effects in ferroic materials

The fundamentals and applications of ferroic materials$-$ferromagnetic, ferroelectric, and ferroelastic$-$are common subjects discussed in just about every graduate course related to functional materials. Looking beyond today’s traditional uses, such as in permanent magnets, capacitors, and shape-memory alloys, there are worthwhile and interesting questions common to the caloric properties of these ferroic materials. Can ferroic materials be used in a cooling cycle? Why are these materials susceptible to external fields? Which combination of properties is required to make some of them suitable for efficient cooling and heat pumping? We address these questions in this introduction to ferroic cooling, which comprises magnetocaloric, electrocaloric, elastocaloric and barocaloric approaches and combinations thereof (i.e., multicalorics). These are addressed in greater detail in the articles in this issue.

36 MATERIALS SCIENCE↗

Current-driven domain wall motion enhanced by the microwave field

The magnetic domain wall (DW) motion driven by a spin-polarized current opens a new concept for memory and logic devices. However, the critical current density required to overcome the intrinsic and/or extrinsic pinning of DW remains too large for practical applications. Here, we show, by using micromagnetic simulations and analytical approaches, that the application of a microwave field offers an effective solution to this problem. When a transverse microwave field is applied, the adiabatic spin-transfer torque (STT) alone can sustain a steady-state DW motion without the sign of Walker breakdown, meaning that the intrinsic pinning disappears. The extrinsic pinning can also be effectively reduced. Moreover, the DW velocity is increased greatly for the microwave-assisted DW motion. This provides a new way to manipulate the DW motion at low current densities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Estimation of the time for steam generator trip due to cyber intrusions

The time required to trip a pressurized water reactor (PWR) by inserting malicious signals into its steam generator (SG) control system has been studied using the Generic PWR (GPWR) Simulator. A semi-analytical model is developed to approximately reproduce the simulator response and understand the dynamics of the control unit. A series of two proportional-integral controllers determines control action according to preset constants, the readings from the feedwater level sensor, and those from feedwater and steam flowrate transmitters. It is observed that the most important factor that determines whether a trip will occur is how much additional water is added to or withheld from the SG over time compared to normal operating conditions. In order to determine the effects of control action on the SG, changes in mass inventory are considered. This approach models the SG water level as a function of mass inventory and has a backward temporal memory. A Python interface is developed for the GPWR framework to automatically simulate different spoofing scenarios and post-process the related data. We observe that the trip times predominantly depend on flow mismatch and/or level errors. Controller parameters, including the integral time and gain constants, either speed up or slow down the rate of progression to a trip setpoint but do not cause a trip by themselves. The reactor can trip on a high-level signal when the reading crosses above 78%, increased from its reference level of 57%, or a low-level reading when it is below 25%. The present results show roughly how long the operators would have to respond to an attack, given a specific set of spoofing signals within the issue space analyzed. Furthermore, we have generated a simple surface by fitting a combination of exponential functions to the data obtained from the GPWR Simulator. In general, trips on a low level have been observed to occur faster than those on a high level.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A mouse model of pre-pregnancy maternal obesity combined with offspring exposure to a high-fat diet resulted in cognitive impairment in male offspring

Cognitive impairment is a brain dysfunction characterized by neuropsychological deficits in attention, working memory, and executive function. Maternal obesity and consumption of a high-fat diet (HFD) in the offspring has been suggested to have detrimental consequences for offspring cognitive function through its effect on the hippocampus and prefrontal cortex. Therefore, our study aimed to investigate the effects of maternal obesity and offspring HFD exposure on the brain metabolome of the offspring.

60 APPLIED LIFE SCIENCES↗

Cations Control Lipid Bilayer Memcapacitance Associated with Long-Term Potentiation

Phospholipid bilayers can be described as capacitors whose capacitance per unit area (specific capacitance, C m ) is determined by their thickness and dielectric constant–independent of applied voltage. It is also widely assumed that the C m of membranes can be treated as a “biological constant”. Recently, using droplet interface bilayers (DIBs), it was shown that zwitterionic phosphatidylcholine (PC) lipid bilayers can act as voltage-dependent, nonlinear memory capacitors, or memcapacitors. When exposed to an electrical “training” stimulation protocol, capacitive energy storage in lipid membranes was enhanced in the form of long-term potentiation (LTP), which enables biological learning and long-term memory. LTP was the result of membrane restructuring and the progressive asymmetric distribution of ions across the lipid bilayer during training, which is analogous, for example, to exponential capacitive energy harvesting from self-powered nanogenerators. Here, we describe how LTP could be produced from a membrane that is continuously pumped into a nonequilibrium steady state, altering its dielectric properties. During this time, the membrane undergoes static and dynamic changes that are fed back to the system’s potential energy, ultimately resulting in a membrane whose modified molecular structure supports long-term memory storage and LTP. Here, we also show that LTP is very sensitive to different salts (KCl, NaCl, LiCl, and TmCl 3 ), with LiCl and TmCl 3 having the most profound effect in depressing LTP, relative to KCl. This effect is related to how the different cations interact with the bilayer zwitterionic PC lipid headgroups primarily through electric-field-induced changes to the statistically averaged orientations of water dipoles at the bilayer headgroup interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reversible Methanolation of Metal Halide Perovskites

The low formation energies inherent in metal halide perovskites enable the structure to be easily broken and remade with little energy input. In this work, we leverage low formation energy to demonstrate 0D/3D structural transformations induced by reversible intercalation of methanol to yield dramatic control of visible light absorption. We identify a methanolated structure that features sheets of 0D isolated [PbI6]4- octahedra separated by MAI and methanol. Methanol and water reversibly displace each other in the 0D complex by controlling the chemical potential of the system via Le Chatelier's principle. The weaker H-bonding of methanol compared to water effectively reduces the complex dissociation temperature from 70 to 50 degrees C, rendering the methanol complex more desirable for an array of next-generation applications spanning low-power-consumption memory to switchable photovoltaics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Diffusion‐Based Uncertainty Quantification Method to Advance E3SM Land Model Calibration

Abstract Calibrating land surface models and accurately quantifying their uncertainty are crucial for improving the reliability of simulations of complex environmental processes. This, in turn, advances our predictive understanding of ecosystems and supports climate‐resilient decision‐making. Traditional calibration methods, however, face challenges of high computational costs and difficulties in accurately quantifying parameter uncertainties. To address these issues, we develop a diffusion‐based uncertainty quantification (DBUQ) method. Unlike conventional generative diffusion methods, which are computationally expensive and memory‐intensive, DBUQ innovates by formulating a parameterized generative model and approximates this model through supervised learning, which enables quick generation of parameter posterior samples to quantify its uncertainty. DBUQ is effective, efficient, and general‐purpose, making it suitable for site‐specific ecosystem model calibration and broadly applicable for parameter uncertainty quantification across various earth system models. In this study, we applied DBUQ to calibrate the Energy Exascale Earth System Model land model at the Missouri Ozark AmeriFlux forest site. Results indicated that DBUQ produced accurate parameter posterior distributions similar to those from Markov Chain Monte Carlo sampling but with 30 times less computing time. This significant improvement in efficiency suggests that DBUQ can enable rapid, site‐level model calibration at a global scale, enhancing our predictive understanding of climate impacts on terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗

The Influence of Land‐Surface Conditions on the 2020–2021 Western US Drought

Abstract In summer 2021, 90% of the western United States (WUS) experienced drought, with over half of the region facing extreme or exceptional conditions, leading to water scarcity, crop loss, ecological degradation, and significant socio‐economic consequences. Beyond the established influence of oceanic forcing and internal atmospheric variability, this study highlights the importance of land‐surface conditions in the development of the 2020–2021 WUS drought, using observational data analysis and novel numerical simulations. Our results demonstrate that the soil moisture state preceding a meteorological drought, due to its intrinsic memory, is a critical factor in the development of soil droughts. Specifically, wet soil conditions can delay the transition from meteorological to soil droughts by several months or even nullify the effects of La Niña‐driven meteorological droughts, while drier conditions can exacerbate these impacts, leading to more severe soil droughts. For the same reason, soil droughts can persist well beyond the end of meteorological droughts. Our numerical experiments suggest a relatively weak soil moisture‐precipitation coupling during this drought period, corroborating the primary contributions of the ocean and atmosphere to this meteorological drought. Additionally, drought‐induced vegetation losses can mitigate soil droughts by reducing evapotranspiration and slowing the depletion of soil moisture. This study highlights the importance of soil moisture and vegetation conditions in seasonal‐to‐interannual drought predictions. Findings from this study have implications for regions like the WUS, which are experiencing anthropogenically‐driven soil aridification and vegetation greening, suggesting that future soil droughts in these areas may develop more rapidly, become more severe, and persist longer.

Jiang, Yelin [Lamont‐Doherty Earth Observatory Col↗

Nonvolatile data storage using mechanical force-induced polarization switching in ferroelectric polymer

Ferroelectric polymers offer the promise of low-cost and flexible electronic products. They are attractive for information storage due to their spontaneous polarization which is usually switched by electric field. Here, we demonstrate that electrical signals can be readily written on ultra-thin ferroelectric polymer films by strain gradient-induced polarization switching (flexoelectric effect). A force with magnitude as small as 64nN is enough to induce highly localized (40 nm feature size) change in the polarization states. The methodology is capable of realizing nonvolatile memory devices with miniaturized cell size and storage density of tens to hundreds Gbit per square inch.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Man-rated flight software for the F-8 DFBW program

The design, implementation, and verification of the flight control software used in the F-8 DFBW program are discussed. Since the DFBW utilizes an Apollo computer and hardware, the procedures, controls, and basic management techniques employed are based on those developed for the Apollo software system. Program assembly control, simulator configuration control, erasable-memory load generation, change procedures and anomaly reporting are discussed. The primary verification tools are described, as well as the program test plans and their implementation on the various simulators. Failure effects analysis and the creation of special failure generating software for testing purposes are described.

Bairnsfather, R. R.↗

Principles for problem aggregation and assignment in medium scale multiprocessors

One of the most important issues in parallel processing is the mapping of workload to processors. This paper considers a large class of problems having a high degree of potential fine grained parallelism, and execution requirements that are either not predictable, or are too costly to predict. The main issues in mapping such a problem onto medium scale multiprocessors are those of aggregation and assignment. We study a method of parameterized aggregation that makes few assumptions about the workload. The mapping of aggregate units of work onto processors is uniform, and exploits locality of workload intensity to balance the unknown workload. In general, a finer aggregate granularity leads to a better balance at the price of increased communication/synchronization costs; the aggregation parameters can be adjusted to find a reasonable granularity. The effectiveness of this scheme is demonstrated on three model problems: an adaptive one-dimensional fluid dynamics problem with message passing, a sparse triangular linear system solver on both a shared memory and a message-passing machine, and a two-dimensional time-driven battlefield simulation employing message passing. Using the model problems, the tradeoffs are studied between balanced workload and the communication/synchronization costs. Finally, an analytical model is used to explain why the method balances workload and minimizes the variance in system behavior.

Nicol, David M.↗

Optically intraconnected computer employing dynamically reconfigurable holographic optical element

An optically intraconnected computer and a reconfigurable holographic optical element employed therein. The basic computer comprises a memory for holding a sequence of instructions to be executed; logic for accessing the instructions in sequence; logic for determining for each the instruction the function to be performed and the effective address thereof; a plurality of individual elements on a common support substrate optimized to perform certain logical sequences employed in executing the instructions; and, element selection logic connected to the logic determining the function to be performed for each the instruction for determining the class of each function and for causing the instruction to be executed by those the elements which perform those associated the logical sequences affecting the instruction execution in an optimum manner. In the optically intraconnected version, the element selection logic is adapted for transmitting and switching signals to the elements optically.

Bergman, Larry A.↗

NavP: Structured and Multithreaded Distributed Parallel Programming

We present Navigational Programming (NavP) -- a distributed parallel programming methodology based on the principles of migrating computations and multithreading. The four major steps of NavP are: (1) Distribute the data using the data communication pattern in a given algorithm; (2) Insert navigational commands for the computation to migrate and follow large-sized distributed data; (3) Cut the sequential migrating thread and construct a mobile pipeline; and (4) Loop back for refinement. NavP is significantly different from the current prevailing Message Passing (MP) approach. The advantages of NavP include: (1) NavP is structured distributed programming and it does not change the code structure of an original algorithm. This is in sharp contrast to MP as MP implementations in general do not resemble the original sequential code; (2) NavP implementations are always competitive with the best MPI implementations in terms of performance. Approaches such as DSM or HPF have failed to deliver satisfying performance as of today in contrast, even if they are relatively easy to use compared to MP; (3) NavP provides incremental parallelization, which is beyond the reach of MP; and (4) NavP is a unifying approach that allows us to exploit both fine- (multithreading on shared memory) and coarse- (pipelined tasks on distributed memory) grained parallelism. This is in contrast to the currently popular hybrid use of MP+OpenMP, which is known to be complex to use. We present experimental results that demonstrate the effectiveness of NavP.

navigational programming (NavP)↗

RACER: Effective Race Detection Using AspectJ

The limits of coding with joint constraints on detected and undetected error rates Programming errors occur frequently in large software systems, and even more so if these systems are concurrent. In the past, researchers have developed specialized programs to aid programmers detecting concurrent programming errors such as deadlocks, livelocks, starvation and data races. In this work we propose a language extension to the aspect-oriented programming language AspectJ, in the form of three new built-in pointcuts, lock(), unlock() and may be Shared(), which allow programmers to monitor program events where locks are granted or handed back, and where values are accessed that may be shared amongst multiple Java threads. We decide thread-locality using a static thread-local objects analysis developed by others. Using the three new primitive pointcuts, researchers can directly implement efficient monitoring algorithms to detect concurrent programming errors online. As an example, we expose a new algorithm which we call RACER, an adoption of the well-known ERASER algorithm to the memory model of Java. We implemented the new pointcuts as an extension to the Aspect Bench Compiler, implemented the RACER algorithm using this language extension and then applied the algorithm to the NASA K9 Rover Executive. Our experiments proved our implementation very effective. In the Rover Executive RACER finds 70 data races. Only one of these races was previously known.We further applied the algorithm to two other multi-threaded programs written by Computer Science researchers, in which we found races as well.

data analysis↗

Resistive memory for radiation resistant non-volatile memory (NSTRF Final Report)

As space programs increase in number and scope, there is an increasing need for radiation-hardened electronic devices and circuits. In particular, missions to high-radiation environments, such as Europa, would greatly benefit from improved radiation hardness in electronic devices. In pursuit of this goal, resistive memory (RRAM) devices were fabricated at SUNY Polytechnic Institute and evaluated for radiation hardness. Our objectives were to produce RRAM devices resistant to high levels of radiation damage and to demonstrate that these devices would improve mission lifetime in high-radiation environments. Furthermore, the underlying mechanisms of radiation were investigated to provide recommendations for radiation-hardening RRAM devices, which could be applied to any candidate RRAM devices being considered for space applications. Devices were fabricated using several fabrication approaches, including patterning by shadow mask, photolithography-based etching, and photolithography-based liftoff. In each of these cases, total ionizing dose (TID) effects and displacement damage dose (DDD) effects were measured. TID effects from exposure to a 60Co gamma source were not observed to cause changes in device resistance or switching parameters in any experiments, with each device tested to at least 20 Mrad(Si). DDD was measured as radiation-generated oxygen vacancies per cm 3 since oxygen vacancies are generally considered to be the active species involved in switching these devices. The lowest DDD level that caused a device to change resistance state was 10 21 vacancies per cm 3 , and most devices failed at 1022 vacancies per cm 3 . This is an extremely high DDD level, even for RRAM devices, which have been reported to fail in the range of 10 17 -10 20 vacancies per cm 3 . For comparison, an example flash memory device failed at 10 15 vacancies per cm 3 . Vendor-fabricated devices with a similar composition to our own were also tested against TID and DDD. The vendor-fabricated devices did not exhibit changes due to TID, up to the tested level of 30 Mrad(Si). Meanwhile, vendor devices exhibited resistance state changes at 10 21 vacancies per cm 3 , similar to our own devices. These results indicate that Ta0x-based RRAM devices may be particularly resilient to both TID and DDD effects. The very high tolerance to radiation effects is most likely due to the high intrinsic concentration of oxygen vacancies within our devices. Based on X-ray photoelectron spectroscopy (XPS) measurements, there are approximately 10 22 oxygen vacancies per cm 3 in our devices as deposited. Most devices failed when the radiation-induced vacancies reached this level, indicating suggesting that a high intrinsic vacancy concentration protects against lower levels of displacement damage. High vacancy concentration likely also protects against TID by facilitating leakage of trapped charge out of the oxide. The use of a thin switching oxide (25 nm Ta0 x , for our devices) is also expected to improve radiation hardness, as there is less room for charge trapping. Therefore, those wishing to produce very radiation-tolerant RRAM devices can probably achieve this by using a thin oxide that contains a high intrinsic concentration of oxygen vacancies. Our devices appear to be very tolerant of radiation effects, and would greatly increase the expected lifetime of a mission to Europa or another high-radiation target compared to flash memory devices. The similar radiation performance of vendor-fabricated devices is promising for adoption of RRAM devices as radiation-hardened memory devices for use in space. With continued commercial development of these devices, RRAM devices are strong candidates for next-generation memories that are inherently rad-hard.

36 MATERIALS SCIENCE↗

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗