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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The use of analgesics for intentional self-poisoning: Trends in U.S. poison center data

In the U.S., intentional self-poisonings with analgesics that are available without a prescription increased from 2000 to 2018. Given concerns regarding mental health outcomes during the COVID-19 pandemic, we examined and compared trends in pediatric and adult intentional self-poisoning with acetaminophen, aspirin, ibuprofen, and naproxen from 2016 to 2021 using the National Poison Data System (NPDS) to see if these trends have continued. We extracted annual case counts of all suspected suicide attempts from intentional poisoning, and of suspected suicide attempts resulting in major effects or death, from the NPDS for non-prescription single ingredient adult formulation acetaminophen, non-prescription single ingredient adult formulation aspirin, single ingredient formulation ibuprofen, and single ingredient formulation naproxen. We enumerated the cases by year, age, and gender. Most cases of intentional self-poisoning within the review period involved acetaminophen and ibuprofen and the 13–19-year-olds constituted the highest proportion of intentional self-poisoning cases across age groups for all four analgesics. Cases involving females predominated cases involving males by 3:1 or greater. Here, the 13–19-year-old age group also represented the largest proportion of cases that resulted in major clinical effects or deaths. An increasing trend in suicide poisoning cases with acetaminophen and ibuprofen was observed in the 6-19-years age group and this trend appeared to exacerbate from 2020 to 2021 corresponding with the start of the COVID-19 pandemic period.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Quasiparticle Poisoning of Superconducting Qubits from Resonant Absorption of Pair-Breaking Photons

The ideal superconductor provides a pristine environment for the delicate states of a quantum computer: because there is an energy gap to excitations, there are no spurious modes with which the qubits can interact, causing irreversible decay of the quantum state. As a practical matter, however, there exists a high density of excitations out of the superconducting ground state even at ultralow temperature; these are known as quasiparticles. Observed quasiparticle densities are of order 1 μ m - 3 , tens of orders of magnitude greater than the equilibrium density expected from theory. Nonequilibrium quasiparticles extract energy from the qubit mode and can induce dephasing. Here we show that a dominant mechanism for quasiparticle poisoning is direct absorption of high-energy photons at the qubit junction. We use a Josephson junction-based photon source to controllably dose qubit circuits with millimeter-wave radiation, and we use an interferometric quantum gate sequence to reconstruct the charge parity of the qubit. We find that the structure of the qubit itself acts as a resonant antenna for millimeter-wave radiation, providing an efficient path for photons to generate quasiparticles. A deep understanding of this physics will pave the way to realization of next-generation superconducting qubits that are robust against quasiparticle poisoning.

Liu, Chuan-Hong↗
DOE OSTI2024

A Compound Data Poisoning Technique with Significant Adversarial Effects on Transformer-based Sentiment Classification Tasks

Transformer-based models have demonstrated much success in various natural language processing tasks. However, they are often vulnerable to adversarial attacks, such as data poisoning, which can intentionally fool the model into generating incorrect results. In this article, we present a novel, compound variant of a data poisoning attack on a transformer-based model that maximizes the poisoning effect while minimizing the scope of poisoning. Here we do so by combining the established data poisoning technique (label flipping) with a novel adversarial artifact selection and insertion technique aimed at minimizing detectability and the scope of the poisoning footprint. We find that by using a combination of these two techniques, we achieve a state-of-the-art attack success rate of approximately 90% while poisoning only 0.5% of the original training set, thus minimizing the scope and detectability of the poisoning action. These findings have the potential to advance the development of better data poisoning detection methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Electrochemical cleaning: An in-Situ method to reverse chromium poisoning in solid oxide fuel cell cathodes

Chromium poisoning is one of the primary factors that affect solid oxide fuel cell (SOFC) durability. In this study, an electrochemical cleaning method has been employed to reverse the effects of chromium poisoning. Two cells were fabricated and poisoned under identical conditions by operating them at 800°C in the presence of a Cr source. Both poisoned cells exhibited a significant reduction in maximum power density and an increase in polarization resistance. One of the poisoned cells, designated as the baseline cell, was cooled to room temperature after poisoning. Microstructural observation of the baseline cell showed significant contamination of the cathode active layer by chromium oxide and (Cr,Mn) spinel deposits. The other poisoned cell was electrochemically cleaned for two hours under a mild electrolytic condition. As a result of the electrochemical cleaning process, the chromium oxide deposits were substantially removed leading to a significant reduction of Cr concentration in the cathode, especially at the cathode/electrolyte interface. Furthermore, a substantial fraction of the cell performance loss was also reversed. To the best of our knowledge, this is a first demonstration of reversing the effects of chromium poisoning using a rapid in-situ process.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers

Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning attacks manipulate training data to induce unreliability of an ML model, whereas backdoor data poisoning attacks maintain system performance unless the MLmodel is presented with an input containing an embedded“trigger” that provides a predetermined response advantageous to the adversary. Our work builds upon prior back-door data-poisoning research for ML image classifiers and systematically assesses different experimental conditions including types of trigger patterns, persistence of trigger patterns during retraining, poisoning strategies, architectures (ResNet-50, NasNet, NasNet-Mobile), datasets (Flowers, CIFAR-10), and potential defensive regularization techniques (Contrastive Loss, Logit Squeezing, Manifold Mixup,Soft-Nearest-Neighbors Loss). Experiments yield four key findings. First, the success rate of backdoor poisoning at-tacks varies widely, depending on several factors, including model architecture, trigger pattern and regularization technique. Second, we find that poisoned models are hard to detect through performance inspection alone. Third, regularization typically reduces backdoor success rate, although it can have no effect or even slightly increase it, depending on the form of regularization. Finally, backdoors inserted through data poisoning can be rendered ineffective after just a few epochs of additional training on a small set of clean data without affecting the model’s performance.

Truong, Loc T.↗
DOE OSTI2025

Model Residuals as Shields: A Two-Level Formulation to Defend Smart Grids From Poisoning Attacks

The advancement of smart grids presents both vast opportunities and heightened cybersecurity risks. Data-driven defense mechanisms, though designed as a shield against these threats, can fall prey to poisoning attacks. We delve into regression settings, underscoring the imperative to fortify defenses against a spectrum of poison ratios, notably those above 0.5—an issue scarcely addressed in prior studies. Recognizing the susceptibilities of smart grids and their manipulable sensors, we exploit the very intent of poisoning attacks, compromising model accuracy, as our defense mechanism. Our proposed two-level optimization framework discerns between poisoned and authentic data based on model residuals, outperforming or matching existing methods in 72% to 77% of precision and 75% to 80% of recalls across various poisoning attacks, poison ratios, and datasets. Once the authentic data are identified, the trained model is adaptable for a variety of applications. Comprehensive evaluations on different smart grid datasets, pitted against myriad poisoning schemes, validate our methodology’s edge over existing methods. Here, we also shed light on the implications of model misspecification originating from temporal auto-correlation, a common feature in Internet of Things and smart grid data.

Adversarial machine learning (ML)↗
DOE OSTI2024

Ultra-stable and poison tolerant oxygen evolution activity enabled by surface In 2 O 3- x (OH) y of Co 3 In 2 S 2 large single crystals

Water is an earth-abundant source for clean hydrogen production via electrochemical water electrolysis (WE). However, the surface poisoning that occurs in aqueous electrolytes drastically deactivates the electrocatalytic performance of electrodes. Here, in this study, we report electrochemically formed In 2 O 3-x (OH) y on the surface of a large (1–1.5 mm long, 0.5–0.6 mm wide and 0.3–0.5 mm thick) single crystal of Weyl semimetal Co 3 In 2 S 2 (Co 3 In 2 S 2 /In 2 O 3-x (OH) y ) as an ultra-stable and poison tolerant electrode for the oxygen evolution reaction (OER) in 1 M KOH, addressing a bottleneck in WE. The OER activity of the powder form of Co 3 In 2 S 2 is limited by its aerophilic nature. Remarkably, the single-crystal electrodes maintained their high activity for a continuous operational period of 5 h in 1 M KOH electrolyte with/without 10 mM strong surface-poisoning ligands i.e., potassium cyanide, bipyridine, and ethylenediaminetetraacetate disodium salt. The electrodes exhibited stable OER activity for 1000 h at 100 mA cm -2 (1.73 V vs. RHE). The temperature-dependent OER polarization curves (10–70 °C) unambiguously revealed surface poisoning through the suppression of precatalytic Co-redox peaks on the bipyridine poisoned electrode, which led to the stabilization of surface Co-sites. The X-ray photoelectron spectroscopy analyses of pristine, poisoned and post-electrocatalytic single-crystal Co 3 In 2 S 2 electrodes revealed the existence of an In 2 O 3-x (OH) y surface phase, which could be the potential heterostructure for the origin of ultra-stable and poison tolerant OER activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Combined Cr and S poisoning behaviors of La 1-x Sr x MnO 3±δ and La 1-x Sr x Co 1-y FeyO 3-δ cathodes in solid oxide fuel cells

Although the individual effects of airborne Cr and S contaminants on SOFC cathode performance degradation have been extensively studied, the combined effects of Cr and S contaminants remain largely unexplored. Under the real SOFC operating condition where the Cr and S species coexist, their effects may compete, affecting the poisoning behavior. Here, our investigation reveals that the combined Cr and S poisoning behavior of LSCF remains different from those of individual Cr and S poisonings, while the combined poisoning mechanism of LSM is equivalent to the sum of those of individual Cr and S effects. For LSCF electrode, gaseous Cr species are deposited mainly at the LSCF/GDC interface by electrochemical reduction, rather than forming SrCrO 4 on LSCF surfaces (as in the case of Cr-only poisoning), indicating no reaction between Cr vapors and SrO on the LSCF surface. Thermodynamic analysis demonstrates that the SrO on LSCF surface absorbs SO 2 (g) and thereby loses the Cr-gettering effect, allowing Cr vapors to flow through LSCF and to reach the LSCF/GDC interface where the Cr deposition occurs. Unlike LSCF, LSM electrode shows cumulative effects of Cr and S, as Cr accumulation occurs at the triple-phase boundary and S absorption takes place at localized Sr-rich regions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Transient pattern formation in an active matter contact poisoning model

Abstract One of the most notable features in repulsive particle based active matter systems is motility-induced-phase separation (MIPS) where a dense, often crystalline phase and low density fluid coexist. Most active matter studies involve time-dependent activity; however, there are many active systems where individual particles transition from living or moving to dead or nonmotile due to lack of fuel, infection, or poisoning. Here we consider an active matter particle system at densities where MIPS does not occur. When we add a small number of infected particles that can poison other particles, rendering them nonmotile, we find a rich variety of time dependent pattern formation, including MIPS, a wetting phase, and a fragmented state formed when mobile particles plow through a nonmotile packing. We map the patterns as a function of time scaled by epidemic duration, and show that the pattern formation is robust for a wide range of poisoning rates and activity levels. We also show that pattern formation does not occur in a random death model, but requires the promotion of nucleation by contact poisoning. Our results should be relevant to biological and active matter systems where there is some form of poisoning, death, or transition to nonmotility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Sulfur Poisoning and Performance Recovery of SOFC Air Electrodes

The sulfur poisoning and performance recovery of the state-of-the-art SOFC cathodes (La 0 . 80 Sr 0 . 20 ) 0 . 95 MnO 3 ± δ (LSM) and (La 0 . 60 Sr 0 . 40 ) 0 . 95 Co 0 . 20 Fe 0 . 80 O 3 – δ (LSCF), have been studied. Electrochemical impedance spectroscopy measurements of LSCF|GDC and LSM|YSZ half-cells are carried out in alternating atmospheres of air and SO 2 –air at 700°C for hundreds of hours. In the presence of SO 2 , the electrochemical performance of both the cells decays with ohmic and non-ohmic losses, owing to the absorption and chemical interaction of SO 2 with the electrodes. In LSCF, the SrO segregated on the surface tends to absorb and react with SO 2 , forming SrSO 4 followed by the exsolution of Co-Fe. As for LSM, SO 2 is absorbed onto the Sr-rich areas of LSM, including the active reaction sites near the TPBs, leading to Sr exsolution and SrSO 4 formation, leaving a Sr-deficient LSM. During the subsequent exposure to air, the performance of the sulfur-contaminated LSM is almost restored. The LSM particles, exposed to alternating atmospheres of air and SO 2 -air during the electrochemical tests, show a relatively clean surface with sparsely distributed SrSO 4 particles, indicating a high stability against sulfur poisoning. It is suggested that the loosely adsorbed SO 2 at the TPBs is readily swept away by the SO 2 -free air flow, recovering its ORR activity, whereas the Sr-deficient LSM due to Sr-exsolution stays modified, contributing to the incomplete performance restoration. Unlike the case of LSM, the performance of the sulfur-poisoned LSCF partially recovers during the subsequent exposure to air. Correspondingly, the LSCF particles have a modified morphology covered with numerous nanoparticles, mostly SrSO 4 , showing the irreversible aspect of the sulfur poisoning. The morphology modification is not concentrated near the electrode/electrolyte interface but over the entire cathode, indicating that the degree of recovery from sulfur poisoning is closely related to the presence of SrO and chemical activity of Sr in the electrodes at the solid-gas interface. These results also show the potential application of LSM for a sulfur sensor available in high-temperature harsh conditions.

25 ENERGY STORAGE↗
DOE OSTI2019

Alkali-metal poisoning effect of total CO and propane oxidation over Co 3 O 4 nanocatalysts

Cobalt oxide (Co 3 O 4 ), a low-cost transitional metal oxide, has been widely studied for catalytic total oxidation of CO and hydrocarbons. However, much less attention has been paid to the poisoning effect due to alkali metals in such oxidation catalysts despite the ease of access to such poisons in both mobile and stationary combustion sources. Here, the alkali metals such as Na, K and Li were readily deposited onto a Co 3 O 4 catalyst to study their poisoning effect on CO and propane oxidation. 1% doping onto Co 3 O 4 was found to increase the light-off temperature by 50 ºC in CO oxidation and over 160 ºC in propane oxidation. It is also noted that alkali metals exhibited a 'locking-effect' on oxygen of Co 3 O 4 , leading to poor oxygen mobility of alkali metal doped catalysts. Lastly, during the reaction, alkali metals can significantly promote the adsorption of CO 2 to form robust surface carbonate species even at high temperature, another reason for the poisoning effect of alkali metals on Co 3 O 4 nanocatalysts for catalytic oxidation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Modernizing the active neutron collar poison rod correction using simulations to enhance PWR fresh fuel verification

The declared inventory of 235 U in fresh, low enriched uranium, nuclear fuel assemblies is routinely verified by nuclear safeguards inspectorates using the UNCL (Uranium Neutron Collar – Light Water Reactor Fuel) nondestructive assay instrument. The trend in modern fuels is towards higher initial enrichment, which in turn requires a larger number of burnable poison pins with higher Gadolinia concentration to hold down the initial reactivity. UNCL assay error for modern fuel assemblies typically exceeds 10%. The traditional algorithm used to correct the response for burnable poison content needs revision to achieve accuracy comparable to the $\sigma_\text{R}$ of 4.5% expected for poison-free assemblies. Here we review the problem and use a large set of 287 Monte Carlo simulations based on an experimentally benchmarked model corresponding to the 16×16 PWR array used in Brazilian Angra type II and III fuel. Simulated relative responses are used to evaluate the functional form of the poison correction and determine parameters optimal for 16×16 PWR assemblies. This update is conducted using between 4–24 Gadolinia pins ranging 2–11 wt% Gd 2 O 3 with assemblies having mean enrichments ranging 2.5%–5%. Experimental validation of the updated coefficients using seven measurements shows bias is reduced by an order of magnitude and $\sigma_\text{R}$R reduced from 10% to less than 2%. Two updated sets of coefficients are provided, the most accurate of which is directly useable in the existing analysis code (INCC) in use by inspectorate at fuel fabrication facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Insights into palladium poisoning of Cu/SSZ-13 selective catalytic reduction catalysts

Here, the impacts of Pd poisoning to the activity, selectivity, and hydrothermal stability of Cu/SSZ-13 selective catalytic reduction (SCR) catalysts are reported. Pd lowers DeNOx efficiency of Cu/SSZ-13 via two mechanisms: (1) displacing SCR active sites in the form of isolated Pd-ions, and (2) catalyzing non-selective NH 3 oxidation in the form of PdO. The first mechanism works by the diffusion of isolated Pd-ions into chabazite cages to displace ZCu II OH SCR active species, and it occurs on Cu/SSZ-13 catalysts with and without external surface CuO clusters in similar fashion. In contrast, the second mechanism works differently with and without external surface CuO clusters. For Cu/SSZ-13 catalyst without external CuO clusters (i.e., primarily isolated Cu-ions), PdO leads to significant decrease of DeNOx efficiency at reaction temperatures above ~400°C due to its non-selective NH 3 oxidation activity at high temperatures. However, this poisoning effect becomes much less impactful on Cu/SSZ-13 catalyst containing CuO clusters. This is due to the formation of CuO-PdO solid solution via interactions between CuO and PdO, which reduces non-selective NH 3 oxidation potential. Furthermore, this solid solution formation even mitigates adverse effects caused by hydrothermal aging. Hence, the poisoning effects of Pd are closely related to Cu speciation and spatial distribution of a Cu/SSZ-13 catalyst. Finally, this study suggests a strategy in eliminating Pd poisoning, that is, the introduction of an oxide phase that effectively traps PdO but does not adversely influence SCR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Sulfur poisoning mechanism of LSCF cathode material in the presence of SO 2 : a computational and experimental study

Aiming at the comprehensive understanding of the single sulfur poisoning effect and, eventually, the multiple impurities poisoning phenomena on the SOFC (Solid Oxide Fuel Cell) cathode materials, the sulfur poisoning effect on the (La 0.6 Sr 0.4 ) 0.95 Co 0.2 Fe 0.8 O 3 (LSCF-6428) has been investigated in the presence of 10 ppm SO 2 at 800, 900, and 1000°C, respectively, with a combined computational and experimental approach. The good agreement between the CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry) simulations and the XRD (X-Ray Diffraction), SEM (Scanning Electron Microscopy), and TEM (Transmission Electron Microscopy) characterization results support the reliability of the CALPHAD approach in the SOFC field. Furthermore, comprehensive simulations were made to understand the impact of temperature, P(SO 2 ), P(O 2 ), and Sr concentration on the threshold of SrSO 4 stability. Results showed that the formation of SrSO4 is thermodynamically favored at lower temperatures, higher P(SO 2 ), higher P(O 2 ), and higher Sr concentration. Finally, comparisons were also made between LSCF-6428 and LSM20 (La 0.8 Sr 0.2 MnO 3 ) using simulations, which confirmed that LSCF-6428 is a poor sulfur-tolerant cathode, in agreement with the literature.

36 MATERIALS SCIENCE↗