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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Identification of shared viral sequences in peat moss metagenomes reveals elements of a possible Sphagnum core virome

Viruses are an understudied component of plant microbiomes. Identifying viruses that are shared between individual plants, or members of the “core virome”, could reveal stable viral populations with the potential to modulate the composition and function of the microbiome. Here, we examined the virome associated with Sphagnum mosses, a keystone species that has direct influence over the fate of peatland carbon stores. We analyzed bulk metagenomes and metatranscriptomes generated from Sphagnum field samples collected over a ten-month period to identify virus-like sequences shared among plants. Individual Sphagnum samples harbored distinct DNA and RNA viromes where only a small percentage (< 1%) of the total number of identified viral contigs were shared among all samples. Based on taxonomic classification, the shared viral contigs represent bacterial viruses, or phage (Caudoviricetes), as well as viruses of eukaryotes, namely nucleocytoplasmic large DNA viruses (Nucleocytoviricota) and RNA viruses (Riboviria). We linked the shared phage-like contigs to viral regions within sequenced genomes of bacterial taxa that are members of the Sphagnum core microbiome, suggesting that these contigs represent temperate phage or degraded prophage. The putative nucleocytoplasmic large DNA viruses and RNA viruses were phylogenetically diverse and showed sequence similarity to viruses associated with a broad range of hosts and environmental sources. The identification of shared viral contigs suggested that, despite the compositional heterogeneity between samples, Sphagnum mosses may harbor a core virome. Future work validating the presence of the core virome is warranted as it may aid in understanding how persistent viruses impact microbiome ecology and symbiont evolution within this climatically relevant keystone species.

Metagenomics↗
NASA NTRS2004

Experimental Test-Bed for Intelligent Passive Array Research

This document describes the test-bed designed for the investigation of passive direction finding, recognition, and classification of speech and sound sources using sensor arrays. The test-bed forms the experimental basis of the Intelligent Small-Scale Spatial Direction Finder (ISS-SDF) project, aimed at furthering digital signal processing and intelligent sensor capabilities of sensor array technology in applications such as rocket engine diagnostics, sensor health prognostics, and structural anomaly detection. This form of intelligent sensor technology has potential for significant impact on NASA exploration, earth science and propulsion test capabilities. The test-bed consists of microphone arrays, power and signal distribution modules, web-based data acquisition, wireless Ethernet, modeling, simulation and visualization software tools. The Acoustic Sensor Array Modeler I (ASAM I) is used for studying steering capabilities of acoustic arrays and testing DSP techniques. Spatial sound distribution visualization is modeled using the Acoustic Sphere Analysis and Visualization (ASAV-I) tool.

Solano, Wanda M.↗
NASA NTRS1993

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Jaggi, S.↗
DOE OSTI2013

Soar adaptive optics observations of the globular cluster NGC 6496

We present high-quality BVRI photometric data in the field of globular cluster NGC 6496 obtained with the SOAR Telescope Adaptive Module (SAM). Our observations were collected as part of the ongoing SAM commissioning. The distance modulus and cluster color excess as found from the red clump are (m – M) {sub V} = 15.71 ± 0.02 mag and E(V – I) = 0.28 ± 0.02 mag. An age of 10.5 ± 0.5 Gyr is determined from the difference in magnitude between the red clump and the subgiant branch. These parameters are in excellent agreement with the values derived from isochrone fitting. From the color-magnitude diagram we find a metallicity of [Fe/H] = –0.65 dex and hence support a disk classification for NGC 6496. The complete BVRI data set for NGC 6469 is made available in the electronic edition of the Journal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Chemical reaction enhanced graph learning for molecule representation

Abstract Motivation Molecular representation learning (MRL) models molecules with low-dimensional vectors to support biological and chemical applications. Current methods primarily rely on intrinsic molecular information to learn molecular representations, but they often overlook effectively integrating domain knowledge into MRL. Results In this article, we develop a reaction-enhanced graph learning (RXGL) framework for MRL, utilizing chemical reactions as domain knowledge. RXGL introduces dual graph learning modules to model molecule representation. One module employs graph convolutions on molecular graphs to capture molecule structures. The other module constructs a reaction-aware graph from chemical reactions and designs a novel graph attention network on this graph to integrate reaction-level relations into molecular modeling. To refine molecule representations, we design a reaction-based relation learning task, which considers the relations between the reactant and product sides in reactions. In addition, we introduce a cross-view contrastive task to strengthen the cooperative associations between molecular and reaction-aware graph learning. Experiment results show that our RXGL achieves strong performance in various downstream tasks, including product prediction, reaction classification, and molecular property prediction. Availability and implementation The code is publicly available at https://github.com/coder-ACAC/RLM.

Biochemistry & Molecular Biology↗
DOE OSTI2025

United States multi-sector land use and land cover base maps to support human and Earth system models

Abstract Earth System Models (ESMs) require current and future projections of land use and landcover change (LULC) to simulate land-atmospheric interactions and global biogeochemical cycles. Among the most utilized land systems in ESMs are the Community Land Model (CLM) and the Land-Use Harmonization 2 (LUH2) products. Regional studies also use these products by extending coarse projections to finer resolutions via downscaling or by using multisector dynamic (MSD) models. One such MSD model is the Global Change Analysis Model (GCAM), which has its own independent land module, but often relies on CLM or LUH2 as spatial inputs for its base years. However, this requires harmonization of thematically incongruent land systems at multiple spatial resolutions, leading to uncertainty and error propagation. To resolve these issues, we develop a thematically consistent LULC system for the conterminous United States adaptable to multiple MSD frameworks to support research at a regional level. Using empirically derived spatial products, we developed a series of base maps for multiple contemporary years of observation at a 30-m resolution that support flexibility and interchangeability amongst LUH2, CLM, and GCAM classification systems.

Oliver, Jay↗
NASA NTRS1980

Optical identification of 4U1907 + 09 using the HEAO-1 scanning modulation collimator position

The paper reports an optical identification of 4U1907 + 09 with a m(v) = 16.4 stellar object in the location determined by the scanning modulation collimator experiment on the first High Energy Astronomy Observatory (HEAO-1). The identification is based on the presence of very strong and broad H-alpha emission. The optical data constrain the distance to be 2-13 kpc, and this gives a range of uncertainty to the typical 2-10 keV luminosity of (1 x 10 to the 35th to 3 x 10 to the 36th) erg/s. The X-ray spectrum and variability is reported, and consideration is given to the hypothesis that the object is an OB supergiant, although its faintness in the blue makes precise spectral classification impossible. It is suggested that this system is an example of a luminous, massive primary emitting a stellar wind which is accreted on the compact object.

Schwartz, D. A.↗
NASA NTRS1991

Three Hierarchies in Skeletal Muscle Fibre Classification Allotype, Isotype and Phenotype

Immunocytochemical analyses using specific anti-myosin antibodies of mammalian muscle fibers during regeneration, development, and after denervation have revealed two distinct myogenic components determining fiber phenotype. The jaw-closing muscles of the cat contain superfast fibers which express a unique myosin not found in limb muscles. When superfast muscle is transplanted into a limb muscle bed, regenerating myotubes synthesize superfast myosin independent of innervation. Reinnervation by the nerve to a fast muscle leads to the expression of superfast and not fast myosin, while reinnervation by the nerve to a slow muscle leads to the expression of a slow myosin. When limb muscle is transplanted into the jaw muscle bed, only limb myosins are synthesized. Thus jaw and limb muscles belong to distinct allotypes, each with a unique range of phenotype options, the expressions of which may be modulated by the nerve. Primary and secondary myotubes in developing jaw and limb muscles are observed to belong to different categories characterized by different patterns of myosin gene expression. By taking into consideration the pattern of myosins synthesized and the changes in fiber size after denervation, 3 types of primary (fast, slow, and intermediate) fibers can be distinguished in rat fast limb muscles. All primaries synthesize slow myosin soon after their formation, but this is withdrawn in fast and intermediate primaries at different times. After neonatal denervation, slow and intermediate primaries express slow primaries hypertrophy with other fibers atrophy. In the mature rat, the number of slow fibers in the EDL is less than the number of slow primaries. Upon denervation, hypertrophic slow fibers matching the number and topographic distribution of slow primaries appear, suggesting that a subpopulation of the slow primaries acquire the fast phenotype during adult life, but reveal their original identity as slow primaries in response to denervation by hypertrophying and synthesizing slow myosin. It is proposed that within each muscle allotype, the various isotypes of primary and secondary fibers are myogenically determined, and are derived from different lineage of myoblasts.

Hoh, Joseph F. Y.↗
DOE OSTI2015

Technical Note: MRI only prostate radiotherapy planning using the statistical decomposition algorithm

Purpose: In order to enable a magnetic resonance imaging (MRI) only workflow in radiotherapy treatment planning, methods are required for generating Hounsfield unit (HU) maps (i.e., synthetic computed tomography, sCT) for dose calculations, directly from MRI. The Statistical Decomposition Algorithm (SDA) is a method for automatically generating sCT images from a single MR image volume, based on automatic tissue classification in combination with a model trained using a multimodal template material. This study compares dose calculations between sCT generated by the SDA and conventional CT in the male pelvic region. Methods: The study comprised ten prostate cancer patients, for whom a 3D T2 weighted MRI and a conventional planning CT were acquired. For each patient, sCT images were generated from the acquired MRI using the SDA. In order to decouple the effect of variations in patient geometry between imaging modalities from the effect of uncertainties in the SDA, the conventional CT was nonrigidly registered to the MRI to assure that their geometries were well aligned. For each patient, a volumetric modulated arc therapy plan was created for the registered CT (rCT) and recalculated for both the sCT and the conventional CT. The results were evaluated using several methods, including mean average error (MAE), a set of dose-volume histogram parameters, and a restrictive gamma criterion (2% local dose/1 mm). Results: The MAE within the body contour was 36.5 ± 4.1 (1 s.d.) HU between sCT and rCT. Average mean absorbed dose difference to target was 0.0% ± 0.2% (1 s.d.) between sCT and rCT, whereas it was −0.3% ± 0.3% (1 s.d.) between CT and rCT. The average gamma pass rate was 99.9% for sCT vs rCT, whereas it was 90.3% for CT vs rCT. Conclusions: The SDA enables a highly accurate MRI only workflow in prostate radiotherapy planning. The dosimetric uncertainties originating from the SDA appear negligible and are notably lower than the uncertainties introduced by variations in patient geometry between imaging sessions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Data and scripts associated with a manuscript on a meta-analysis synthesizing stream biogeochemical response to wildfires across space and time (v2)

This data package is associated with the publication “Catchment characteristics modulate the influence of wildfires on nitrate and dissolved organic carbon in lotic systems across space and time: A meta-analysis” submitted to Global Biogeochemical Cycles (Cavaiani et al. 2025). This study uses meta-analytical techniques to evaluate the effect of wildfire on in-stream responses in burned and unburned watersheds. The study aims to provide additional insight into the range of responses and net influences that wildfires have on hydro-biogeochemistry across broad spatial scales, burn extents, and the persistence of water-quality change. This study compiles data and metadata from 18 total publications that includes 1) surface water geochemistry data (dissolved organic carbon; nitrate), 2) climate classifications, 3) year of the wildfire, 4) the time lag between when the fire occurred and when the sampling occurred, and 5) study design of the publication. In total, this meta-analysis draws data that spans 8 climate guilds, 3 biomes, 62 watersheds, and 20 unique wildfires. See Sites_meta_data.csv for citations of the papers used in this meta-analysis. All R scripts and the associated data can also be found on GitHub at This data package was originally published in March 2024. It was updated in April 2025 (v2; new and modified files). See the change history section in the readme for more details. This data package contains five primary folders that include the following: (1) inputs; (2) output for analysis; (3) initial plots; (4) R scripts; and (5) GIS data. The data package also contains a data dictionary (dd) that provides column header definitions and a file-level metadata (flmd) file that describes every file. The “inputs” folder contains a list of all publications identified during the formal web search and an indication of whether each publication was included in the final analysis. Additionally, it includes site-level metadata, catchment characteristics, and GIS data for all publications included in the final analysis. The “Output_for_analysis” folder contains all data frames and figures generated from each R script used for additional data analysis. The “initial_plots” folder includes all exploratory figures that will be included in a supplemental and figures that will be submitted with the manuscript for publication. The “R_scripts” folder contains the scripts that perform all the data manipulations, statistical analyses, and plots. The “gis_data” folder includes shape files for each fire included in this meta-analysis. This data package contains the following file types: csv, pdf, jpeg, cpg, dbf, prj, shp, shp.ea.iso.xml, shp.iso.xml, shx.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Unrolled Video Super-Resolution Network with Autoregressive Prior for the Case of Known Motion

Real-time detection and classification of distant objects is necessary for many national security applications. However, when objects are far from the sensor, they occupy only a small number of pixels in the captured video, limiting the amount of visual detail available for recognition. State-of-the-art classification methods typically rely on high-resolution (HR) video streams to capture characteristic object features, but obtaining such detail is challenging for distant objects that occupy only a few pixels. This motivates the development of video super-resolution (VSR) methods that enhance object classification by recovering fine details from low-pixel representations. Current VSR methods rely either on model-based optimization, which is interpretable but computationally expensive, or on learning-based approaches, which are efficient and high-performing but often lack flexibility and interpretability. In this report, we propose an end-to-end trainable unrolled VSR network, UVSRNet, which super-resolves each frame in a video by exploiting sub-pixel motion between neighboring low-resolution (LR) frames as well as incorporating high-frequency detail from previously super-resolved frames. In particular, by unrolling a plug-and-play (PnP) half-quadratic splitting (HQS) algorithm, we leverage a model-based data-fitting module alongside a learning-based autoregressive prior module. This combination yields a method that maintains the flexibility and interpretability of model-based methods while achieving the performance advantages of learning-based methods.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2014

Structures of the NLRP14 pyrin domain reveal a conformational switch mechanism regulating its molecular interactions

Pyrin domains (PYDs) recruit downstream effector molecules in NLR signalling. A specific charge-relay system suggests a the formation of a signalling complex involving a PYD dimer. The cytosolic tripartite NLR receptors serve as important signalling platforms in innate immunity. While the C-terminal domains act as sensor and activation modules, the N-terminal death-like domain, e.g. the CARD or pyrin domain, is thought to recruit downstream effector molecules by homotypic interactions. Such homotypic complexes have been determined for all members of the death-domain superfamily except for pyrin domains. Here, crystal structures of human NLRP14 pyrin-domain variants are reported. The wild-type protein as well as the clinical D86V mutant reveal an unexpected rearrangement of the C-terminal helix α6, resulting in an extended α5/6 stem-helix. This reordering mediates a novel symmetric pyrin-domain dimerization mode. The conformational switching is controlled by a charge-relay system with a drastic impact on protein stability. How the identified charge relay allows classification of NLRP receptors with respect to distinct recruitment mechanisms is discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Using individual patient anatomy to predict protocol compliance for prostate intensity-modulated radiotherapy

If a prostate intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT) plan has protocol violations, it is often a challenge knowing whether this is due to unfavorable anatomy or suboptimal planning. This study aimed to create a model to predict protocol violations based on patient anatomical variables and their potential relationship to target and organ at risk (OAR) end points in the setting of definitive, dose-escalated IMRT/VMAT prostate planning. Radiotherapy plans from 200 consecutive patients treated with definitive radiation for prostate cancer using IMRT or VMAT were analyzed. The first 100 patient plans (hypothesis-generating cohort) were examined to identify anatomical variables that predict for dosimetric outcome, in particular OAR end points. Variables that scored significance were further assessed for their ability to predict protocol violations using a Classification and Regression Tree (CART) analysis. These results were then validated in a second group of 100 patients (validation cohort). In the initial analysis of the hypothesis-generating cohort, percentage of rectum overlap in the planning target volume (PTV) (%OR) and percentage of bladder overlap in the PTV (%OB) were highlighted as significant predictors of rectal and bladder dosimetry. Lymph node treatment was also significant for bladder outcomes. For the validation cohort, CART analysis showed that %OR of < 6%, 6% to 9% and > 9% predicted a 13%, 63%, and 100% rate of rectal protocol violations respectively. For the bladder, %OB of < 9% vs > 9% is associated with 13% vs 88% rate of bladder constraint violations when lymph nodes were not treated. If nodal irradiation was delivered, plans with a %OB of < 9% had a 59% risk of violations. Percentage of rectum and bladder within the PTV can be used to identify individual plan potential to achieve dose-volume histogram (DVH) constraints. A model based on these factors could be used to reduce planning time, improve work flow, and strengthen plan quality and consistency.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2018

A NICER Look at the Aql X-1 Hard State

We report on a spectral-timing analysis of the neutron star low-mass X-ray binary(LMXB)AqlX-1 with the Neutron Star Interior Composition Explorer (NICER) on the International Space Station (ISS). AqlX-1 wasobserved with NICER during a dim outburst in 2017 July, collecting approximately 50 ks of good exposure. The spectral and timing properties of the source correspond to that of a (hard) extreme island state in the atoll classification. We find that the fractional amplitude of the low-frequency (<0.3Hz) band-limited noise shows adramatic turnover as a function of energy: it peaks at 0.5keV with nearly 25% rms, drops to 12% rms at 2keV,and rises to 15% rms at 10keV. Through the analysis of covariance spectra, we demonstrate that band-limited noise exists in both the soft thermal emission and the power-law emission. Additionally, we measure hard timelags, indicating the thermal emission at 0.5keV leads the power-law emission at 10 keV on a timescale of 100ms at 0.3Hz to10ms at 3Hz. Our results demonstrate that the thermal emission in the hard state is intrinsically variable, and is driving the modulation of the higher energy power-law. Interpreting the thermal spectrum as disk emission, we find that our results are consistent with the disk propagation model proposed for accretion onto black holes.

Bult, Peter↗
DOE OSTI2021

Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases

Family 7 glycoside hydrolases (GH7) are among the principal enzymes for cellulose degradation in nature and industrially. These important enzymes are often bimodular, including a catalytic domain and carbohydrate binding module (CBM) attached via a flexible linker, and exhibit an active site that binds cello-oligomers of up to ten glucosyl moieties. GH7 cellulases consist of two major subtypes: cellobiohydrolases (CBH) and endoglucanases (EG). Despite the critical importance of GH7 enzymes, there remain gaps in our understanding of how GH7 sequence and structure relate to function. Here, we employed machine learning to gain data-driven insights into relationships between sequence, structure, and function across the GH7 family. Machine-learning models, trained only on the number of residues in the active-site loops as features, were able discriminate GH7 CBHs and EGs with up to 99% accuracy, demonstrating that the lengths of loops A4, B2, B3, and B4 strongly correlate with functional subtype across the GH7 family. Classification rules were derived such that specific residues at 42 different sequence positions each predicted the functional subtype with accuracies surpassing 87%. A random forest model trained on residues at 19 positions in the catalytic domain predicted the presence of a CBM with 89.5% accuracy. Our ML results recapitulate, as top-performing features, a substantial number of the sequence positions determined by previous experimental studies to play vital roles in GH7 activity. We surmise that the yet-to-be-explored sequence positions among the top-performing features also contribute to GH7 functional variation and may be exploited to understand and manipulate function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

New identifications of bright X-ray sources with the HEAO-1 Scanning Modulation Collimator

Based on data obtained with the HEAO-1 Scanning Modulation Collimator (MC) experiment, candidate Be star systems and BL Lac objects are reported. Identification of the V = 6.6 star HD91188 as a Be star is confirmed, and X-ray luminosities ranging from 9 x 10 to the 32nd to 1.4 x 10 to the 34th ergs/s are derived. A B2 spectral type with a reddening E(B - V) = 0.42 is deduced for a V = 9.87 star which appears in an MC location diamond for the source 1H0550 + 286. A V = 16.5 ultraviolet excess object in the location 2A1058 - 226 = 3A1057 - 224 = 4U1057 - 21 = H1100 - 230 gave a 20 cm flux of 83 mJy, and a V = 16.2 ultraviolet excess object at 3A1422 + 425 = 1H143 + 423 was found to have a 20 cm flux of 33 mJy, suggesting their classification as BL Lac objects.

Schwartz, D. A.↗
DOE OSTI2014

TU-F-12A-03: Using 18F-FDG-PET-CT and Deformable Registration During Head-And-Neck Cancer (HNC) Intensity Modulated Radiotherapy (IMRT) to Predict Treatment Response

Purpose: To evaluate the effect of deformable vs. rigid registration of pre-treatment 18F-FDG-PET-CT to intra-treatment 18F-FDG-PET-CT on different standardized uptake value (SUV) parameters and investigate which parameters correlate best with post-treatment response in patients undergoing IMRT for HNC. Methods: Pre-treatment and intra-treatment PET-CT (after 20Gy) scans were acquired, in addition to a 12 week post-treatment PET-CT to assess treatment response. Primary and lymph node gross tumor volumes (GTV-PRI and GTV-LN) were contoured on the pre-treatment CT. These contours were then mapped to intra-treatment PET images via rigid and deformable registration. Absolute changes from pre- to intra-treatment scans for rigid and deformable registration were extracted for the following parameters: SUV-MAX, SUV-MEAN, SUV-20%, SUV-40%, and SUV-60% (SUV-X% is the minimum SUV to the highest-intensity X% volume). Results: Thirty-eight patients were evaluated, with 27 available for classification as complete or incomplete response (CR/ICR). The pre-treatment average tumor volumes for the patients were 24.05cm{sup 3} for GTV-PRI and 23.4cm{sup 3} for GTV-LN. For GTV-PRI, there was no statistically significant difference between rigid vs. deformable registration across all ΔSUV parameters. For GTV-LN contours, all parameters were significantly different except for ΔSUV-MAX. For deformably-registered GTV-PRI, changes in the following metrics were significantly different for CR vs. ICR: SUV-MEAN(p=0.003), SUV-20%(p=0.02), SUV-40%(p=0.02), and SUV-60%(p=0.008). The following cutoff values separated CR from ICR with high sensitivity and specificity: ΔSUV-MEAN=1.49, ΔSUV-20%=2.39, ΔSUV-40%=1.80 and ΔSUV-60%=1.31. Corresponding areas under the Receiver Operating Characteristics curve were 0.90, 0.81, 0.81, and 0.85, respectively. Conclusion: Rigidly and deformably registered contours yielded statistically similar SUV parameters for GTV-PRI, but not GTV-LN. This implies that neither registration should be solely relied upon for nodal GTVs. Of the four SUV parameters found to be predictive of CR vs. ICR, SUV-MEAN was the strongest. Preliminary results show promise for using intra-treatment 18F-FDG-PET-CT with deformable registration to predict treatment response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Maximizing dynamic range and performance of anatase TiO 2 ECRAM through structure and programming

Here, in this study, we investigate the structure-dependent modulation characteristics of all-solid-state three-terminal electrochemical random-access memory (ECRAM) based on an anatase Li x TiO 2 channel. By directly comparing “asymmetric” and “symmetric” ECRAM device architectures, we reveal significant insight into the impact of a non-zero gate-drain open-circuit voltage and its influence on voltage vs. current-controlled gating. We also explore the impact of potentiation/depression write parameters on the symmetry, linearity, and dynamic range of the device response. Together, initial results from optimizing structure and programming approaches yielded unprecedented G max /G min ratios of >1,000 for ECRAM and hundreds of tunable memory states with excellent linearity and symmetry. Simulations based on these ECRAM devices further illustrate the promise of this analog memory technology, achieving near 2% classification error in the MNIST digit recognition benchmark for a range of training parameters compared to a theoretical best of 1.66% and outperforming other device models extracted from the literature.

AIHWKit↗