Search NASA⌕ Search

SEARCH · Search NASA

Results for “Reversible computation”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reverse Osmosis Simulation Data

This dataset consists of computational fluid dynamics (CFD) output for various spacer configurations in a feed-water channel in reverse osmosis (RO) applications. Feed-water channels transport brine solution to the RO membrane surfaces. The spacers embedded in the channels help improve membrane performance by disrupting the concentration boundary layer growth on membrane surfaces. Refer to the "Related Work" resource below for more details. This dataset considers a feed-water channel of length 150mm. The inlet brine velocity and concentration are fixed at 0.1m/s and 100kg/m3 respectively. The diameter of the cylindrical spacers is fixed as 0.3mm and six varying inter-spacer distances of 0.75mm, 1mm, 1.5mm, 2mm, 2.5mm, and 3mm are simulated. The dataset comprising the steady, spatial fields of solute concentration, velocity, and density near each spacer is placed in the folder corresponding to the spacer configuration considered. We run two sets of CFD simulations and include the outputs from both sets for each configuration: (1) with a coarser mesh, producing low-resolution (LR) data of spatial resolution 20x20, and (2) with a finer mesh, producing high-resolution (HR) data of spatial resolution 100x100. These data points can be treated as images with the quantities of interest as their channels and can be used to train machine learning models to learn a mapping from the LR images as inputs to the HR images as outputs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Cost-optimal selection of pH control for mineral scaling prevention in high recovery reverse osmosis desalination

Conference proceedings for Foundations of Computer Aided Process Design (FOCAPD) 2024 that details a cost optimization model for pH control to prevent mineral scaling in high recovery reverse osmosis. This work applies a framework for incorporating detailed water chemistry predictions such as precipitation, pH change, and mineral scaling tendencies with process-scale optimization. It demonstrates that the acid choice for pH control can have a significant impact on pretreatment costs.

Amusat, Oluwamayowa↗
DOE OSTI2024

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation

Here, we present a supervised learning framework of training generative models for density estimation. Generative models, including generative adversarial networks (GANs), normalizing flows, and variational auto-encoders (VAEs), are usually considered as unsupervised learning models, because labeled data are usually unavailable for training. Despite the success of the generative models, there are several issues with the unsupervised training, e.g., requirement of reversible architectures, vanishing gradients, and training instability. To enable supervised learning in generative models, we utilize the score-based diffusion model to generate labeled data. Unlike existing diffusion models that train neural networks to learn the score function, we develop a training-free score estimation method. This approach uses mini-batch-based Monte Carlo estimators to directly approximate the score function at any spatial-temporal location in solving an ordinary differential equation (ODE), corresponding to the reverse-time stochastic differential equation (SDE). This approach can offer both high accuracy and substantial time savings in neural network training. Once the labeled data are generated, we can train a simple, fully connected neural network to learn the generative model in the supervised manner. Compared with existing normalizing flow models, our method does not require the use of reversible neural networks and avoids the computation of the Jacobian matrix. Compared with existing diffusion models, our method does not need to solve the reverse-time SDE to generate new samples. As a result, the sampling efficiency is significantly improved. We demonstrate the performance of our method by applying it to a set of 2D datasets as well as real data from the University of California Irvine (UCI) repository.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Environmental Mercury Chemistry – In Silico

Mercury (Hg) is a global environmental contaminant. Major anthropogenic sources of Hg emission include gold mining and the burning of fossil fuels. Once deposited in aquatic environments, Hg can undergo redox reactions, form complexes with ligands, and adsorb onto particles. It can also be methylated by microorganisms. Mercury, especially its methylated form methylmercury, can be taken up by organisms, where it bioaccumulates and biomagnifies in the food chain, leading to detrimental effects on ecosystem and human health. In support of the recently enforced Minamata Convention on Mercury, a legally binding international convention aimed at reducing the anthropogenic emission of—and human exposure to—Hg, its global biogeochemical cycle must be understood. Thus, a detailed understanding of the molecular-level interactions of Hg is crucial.The ongoing rapid development of hardware and methods has brought computational chemistry to a point that it can usefully inform environmental science. This is particularly true for Hg, which is difficult to handle experimentally due to its ultratrace concentrations in the environment and its toxicity. The current account provides a synopsis of the application of computational chemistry to filling several major knowledge gaps in environmental Hg chemistry that have not been adequately addressed experimentally.Environmental Hg chemistry requires defining the factors that determine the relative affinities of different ligands for Hg species, as they are critical for understanding its speciation, transformation and bioaccumulation in the environment. Formation constants and the nature of bonding have been determined computationally for environmentally relevant Hg(II) complexes such as chlorides, hydroxides, sulfides and selenides, in various physical phases. Quantum chemistry has been used to determine the driving forces behind the speciation of Hg with hydrochalcogenide and halide ligands. Of particular importance is the detailed characterization of solvation effects. Indeed, the aqueous phase reverses trends in affinities found computationally in the gas phase. Computation has also been used to investigate complexes of methylmercury with (seleno)amino acids, providing a molecular-level understanding of the toxicological antagonism between Hg and selenium (Se). Furthermore, evidence is emerging that ice surfaces play an important role in Hg transport and transformation in polar and alpine regions. Therefore, the diffusion of Hg and its ions through an idealized ice surface has been characterized.Microorganisms are major players in environmental mercury cycling. Some methylate inorganic Hg species, whereas others demethylate methylmercury. Quantum chemistry has been used to investigate catalytic mechanisms of enzymatic Hg methylation and demethylation. The complex interplay between the myriad chemical reactions and transport properties both in and outside microbial cells determines net biogeochemical cycling. In conclusion, prospects for scaling up molecular work to obtain a mechanistic understanding of Hg cycling with comprehensive multiscale biogeochemical modeling are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Information criteria for quantifying loss of reversibility in parallelized KMC

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot be computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Electric‐Field‐Driven Reversal of Ferromagnetism in (110)‐Oriented, Single Phase, Multiferroic Co‐Substituted BiFeO 3 Thin Films

Abstract While multiferroic materials are attractive systems for the promise of ultra‐low‐power‐consumption computational technologies, electric‐field‐induced magnetization reversal is a key challenge for realizing devices at scale. Though significant research efforts have been working toward the realization of a material which couples ferroelectricity and ferromagnetism, there are few, even composite, systems which are practical for device scale applications at room temperature. Co‐substituted multiferroic BiFe 0.9 Co 0.1 O 3 is a promising candidate system, due to coupled ferroelectricity and weak ferromagnetism at room temperature. Here, it is theoretically indicated that the ferroic orders in this material are statically coupled, where an in‐plane 109° ferroelectric switching event can result in the reversal of this out‐of‐plane component of magnetization, and the electric field‐induced magnetization reversal is experimentally observed. Such an in‐plane poling configuration is particularly desirable for device applications.

Chemistry↗
DOE OSTI2025

Metastable‐State Photoacids with Fast Reverse Reactions

Metastable-state photoacid (mPAH) has become a common tool for controlling and driving chemical processes with light. mPAHs with fast reverse reactions are desirable for precise temporal control or generating quick pulses of proton concentration. Here, in this work, different approaches towards fast reversing mPAHs are studied. Experimental and computational results showed that stabilizing the charge–transfer intermediate is an effective way to increase the rate. A novel mPAH with a reverse reaction ≈500 times faster than the most used mPAH in methanol is developed. Another water-soluble mPAH showed a reverse reaction with a rate constant of 7.8 s −1 , which is the fastest ever reported. The half-life of the acidic state is calculated to be 89 ms, which allowed to demonstrate sub-second switching using this mPAH.

Abbood, Rana [Florida Institute of Technology, Mel↗
DOE OSTI2020

Time-reversal of an unknown quantum state

For decades, researchers have sought to understand how the irreversibility of the surrounding world emerges from the seemingly time-symmetric, fundamental laws of physics. Quantum mechanics conjectured a clue that final irreversibility is set by the measurement procedure and that the time-reversal requires complex conjugation of the wave function, which is overly complex to spontaneously appear in nature. Building on this Landau-Wigner conjecture, it became possible to demonstrate that time-reversal is exponentially improbable in a virgin nature and to design an algorithm artificially reversing a time arrow for a given quantum state on the IBM quantum computer. However, the implemented arrow-of-time reversal embraced only the known states initially disentangled from the thermodynamic reservoir. Here we develop a procedure for reversing the temporal evolution of an arbitrary unknown quantum state. This opens the route for general universal algorithms sending temporal evolution of an arbitrary system backward in time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities

Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. Further, in this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Adsorption Study of Al 3+ , Cr 3+ , and Mn 2+ onto Quartz and Corundum using Flow Microcalorimetry, Quartz Crystal Microbalance, and Density Functional Theory

The adsorption of aqueous ions onto natural mineral surfaces controls numerous mineral–water interactions and is governed by, among other numerous factors, ion dehydration and hydrolysis. This work explored the extent to which dehydration and hydrolysis affect the adsorption of three metal cations, Al 3+ , Cr 3+ , and Mn 2+ , onto quartz (SiO2) and corundum (Al 2 O 3 ) surfaces at pH 3.8 through the integration of flow microcalorimetry (FMC), quartz crystal microbalance with dissipation (QCM-D) measurements and density functional theory (DFT) calculations. At pH 3.8, negligible amounts of Mn 2+ and Al 3+ are hydrolyzed, while 78% of Cr 3+ exist in hydrolyzed species. QCM-D and FMC measurements showed that Al 3+ and Cr 3+ adsorb to both surfaces, while Mn 2+ adsorbed only to Al 2 O 3 . DFT bond energy calculations confirmed the favorable bonding between the mineral surfaces and Al 3+ and Cr 3+ , and that Mn 2+ adsorption onto SiO 2 was unfavorable. Furthermore, FMC showed that on both surfaces, the adsorption of Al 3+ was endothermic and reversible, while that of Cr 3+ was exothermic and partially irreversible. Through the integration of experimental and computational methods, this work suggested that the reversible adsorption of unhydrolyzed cations (Mn 2+ and Al 3+ ) occurred through weak electrostatic interactions. The large energy cost required to dehydrate unhydrolyzed cations resulted in an endothermic adsorption process. Meanwhile, hydrolyzed Cr 3+ species can adsorb on quartz and corundum through covalent-bond formation, and thus, their adsorption was partially irreversible. Furthermore, the hydrolysis of Cr 3+ lowered the dehydration energy during adsorption, resulting in an exothermic adsorption. By using bond energies as a guide to indicate the possibility of thermodynamically favored adsorption, there was a strong agreement between the DFT and experimental techniques. The findings presented here contribute to understanding and predicting various mineral–water interfacial processes in the natural environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Iridium Complexes with Proton-Responsive Azole-Type Ligands as Effective Catalysts for CO 2 Hydrogenation

Pentamethylcyclopentadienyl iridium (Cp*Ir) complexes with bidentate ligands consisting of a pyridine ring and an electron-rich diazole ring were prepared. Their catalytic activity towards CO 2 hydrogenation in 2.0 M KHCO 3 aqueous solutions (pH 8.5) at 50 °C, under 1.0 MPa CO 2 /H 2 (1:1) have been reported as an alternative to photo- and electrochemical CO 2 reduction. Bidentate ligands incorporating an electron-rich diazole ring improved the catalytic performance of the Ir complexes compared to the bipyridine ligand. Complexes 2, 4 and 6, possessing both a hydroxy group and an uncoordinated NH group, which are proton-responsive and capable of generating pendent-bases in basic media, recorded high initial TOF values of 1300 h -1 , 1550 h -1 and 2000 h -1 , respectively. Here, spectroscopic and computational investigations revealed that the reversible deprotonation changes the electronic properties of the complexes and causes interactions between pendent base and substrate and/or solvent water molecules, resulting in the high catalytic performance in basic media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Systematic Screening of COVID-19 Disease Based on Chest CT and RT-PCR for Cancer Patients Undergoing Radiation Therapy in a Coronavirus French Hotspot

Patients with cancer are presumed to be more vulnerable to COVID-19. We evaluated a screening strategy combining chest computed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) for patients treated with radiation therapy at our cancer center located in a COVID-19 French hotspot during the first wave of the pandemic.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

De novo designed ice-binding proteins from twist-constrained helices

Attaining molecular-level control over solidification processes is a crucial aspect of materials science. To control ice formation, organisms have evolved bewildering arrays of ice-binding proteins (IBPs), but these have poorly understood structure–activity relationships. We propose that reverse engineering using de novo computational protein design can shed light on structure–activity relationships of IBPs. We hypothesized that the model alpha-helical winter flounder antifreeze protein uses an unusual undertwisting of its alpha-helix to align its putative ice-binding threonine residues in exactly the same direction. We test this hypothesis by designing a series of straight three-helix bundles with an ice-binding helix projecting threonines and two supporting helices constraining the twist of the ice-binding helix. Our findings show that ice-recrystallization inhibition by the designed proteins increases with the degree of designed undertwisting, thus validating our hypothesis, and opening up avenues for the computational design of IBPs.

Science & Technology - Other Topics↗
DOE OSTI2015

On the Green's function of the partially diffusion-controlled reversible ABCD reaction for radiation chemistry codes

Several computer codes simulating chemical reactions in particles systems are based on the Green's functions of the diffusion equation (GFDE). Indeed, many types of chemical systems have been simulated using the exact GFDE, which has also become the gold standard for validating other theoretical models. In this work, a simulation algorithm is presented to sample the interparticle distance for partially diffusion-controlled reversible ABCD reaction. This algorithm is considered exact for 2-particles systems, is faster than conventional look-up tables and uses only a few kilobytes of memory. The simulation results obtained with this method are compared with those obtained with the independent reaction times (IRT) method. This work is part of our effort in developing models to understand the role of chemical reactions in the radiation effects on cells and tissues and may eventually be included in event-based models of space radiation risks. However, as many reactions are of this type in biological systems, this algorithm might play a pivotal role in future simulation programs not only in radiation chemistry, but also in the simulation of biochemical networks in time and space as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Study of the development of relativistic plasma bunches in a long mirror trap by optical and X-ray imaging and numerical simulations

The work presents experimental results demonstrating the feasibility of autoresonance acceleration of electrons in a long mirror trap with a reverse magnetic field. It is shown that gyromagnetic autoresonance results in the formation of a plasma bunch with average electron energy of several hundred keV, which is confined for a long time in the trap. The results of computer simulations of the regime of reverse gyromagnetic autoresonance agree well with the experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Bubble chambers for experiments in nuclear astrophysics

A bubble chamber has been developed to be used as an active target system for low energy nuclear astrophysics experiments. Adopting ideas from dark matter detection with superheated liquids, a detector system compatible with gamma-ray beams has been developed. This detector alleviates some of the limitations encountered in standard measurements of the minute cross sections of interest to stellar environments. While the astrophysically relevant nuclear reaction processes at hydrostatic burning temperatures are dominated by radiative captures, in this experimental scheme we measure the time reversed processes. Such photodisintegrations allow us to compute the radiative capture cross sections when transitions to excited states of the reaction products are negligible. Due to the transformation of phase space, the photodisintegration cross-sections are up to two orders of magnitude higher. The main advantage of the new target-detector system is a density several orders of magnitude higher than conventional gas targets. Also, the detector is virtually insensitive to the gamma-ray beam itself, thus allowing us to detect only the products of the nuclear reaction of interest. The development and the operation as well as the advantages and disadvantages of the bubble chamber are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Using Modeling and Simulation to Complement Testing for Increased Understanding of Weapon Subassembly Response.

As part of Sandia’s nuclear deterrence mission, the B61-12 Life Extension Program (LEP) aims to modernize the aging weapon system. Modernization requires requalification and Sandia is using high performance computing to perform advanced computational simulations to better understand, evaluate, and verify weapon system performance in conjunction with limited physical testing. The Nose Bomb Subassembly (NBSA) of the B61-12 is responsible for producing a fuzing signal upon ground impact. The fuzing signal is dependent upon electromechanical impact sensors producing valid electrical fuzing signals at impact. Computer generated models were used to assess the timing between the impact sensor’s response to the deceleration of impact and damage to major components and system subassemblies. The modeling and simulation team worked alongside the physical test team to design a large-scale reverse ballistic test to not only assess system performance, but to also validate their computational models. The reverse ballistic test conducted at Sandia’s sled test facility sent a rocket sled with a representative target into a stationary B61-12 (NBSA) to characterize the nose crush and functional response of NBSA components. Data obtained from data recorders and high-speed photometrics were integrated with previously generated computer models in order to refine and validate the model’s ability to reliably simulate real-world effects. Large-scale tests are impractical to conduct for every single impact scenario. By creating reliable computer models, we can perform simulations that identify trends and produce estimates of outcomes over the entire range of required impact conditions. Sandia’s HPCs enable geometric resolution that was unachievable before, allowing for more fidelity and detail, and creating simulations that can provide insight to support evaluation of requirements and performance margins. As computing resources continue to improve, researchers at Sandia are hoping to improve these simulations so they provide increasingly credible analysis of the system response and performance over the full range of conditions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗