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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Process design for recovering rare-earth elements from mine tailings with low rare-earth concentrations via sequential leaching and solvent extraction

Rare earth elements (REEs) are essential for advanced technologies and yet face significant supply chain risks due to their concentrated global production and limited domestic availability. Addressing this challenge requires efficient processes capable of upgrading low-grade secondary resources such as mine tailings. In this study, we developed a novel separation flowsheet that integrates sequential leaching and 2-stage solvent extraction (SX) processes to recover high-purity heavy REEs (HREEs) and light REEs (LREEs) from a simulated mine-tailing concentrate containing 2.4 wt% total REEs (TREEs; 0.6 wt% LREEs and 1.8 wt% HREEs). Sequential leaching with controlled pH adjustment selectively precipitated REEs while retaining the large amount of impurities in the solution, producing an REE-enriched leachate by following leaching processes with roughly twice the REE concentration and half the impurity concentration compared to that of single-step leaching. The optimized SX flowsheet employed Cyanex 572 to extract HREEs and Fe over LREEs, followed by Fe removal using tributyl phosphate (TBP), while the raffinate stream was processed by SX with di(2-ethylhexyl)phosphoric acid (D2EHPA) to recover LREEs under optimized conditions balancing both extraction efficiency and purity. Although increased extractant availability in the organic phase improved LREE recovery, it also increased co-extraction of Ca, underscoring trade-offs in process optimization. Both HREE- and LREE-rich solutions were subsequently precipitated into solid products via oxalate precipitation, resulting in high-purity REE solids containing ∼92.0 wt% HREEs (∼95.7 wt% TREEs) and ∼92.8 wt% LREEs (∼94.0 wt% TREEs). In conclusion, this proof-of-concept study using simulated mine tailings demonstrates a promising approach for upgrading low-grade REE resources, while highlighting the need for future validation with real materials.

Mine tailings↗
DOE OSTI2020

Optimizing Sub-Sampled STEM Imaging for Beam Sensitive Materials and Dynamic Processes

The goal of this research is to quantify how sub-sampling and inpainting (broadly classified as methods in Artificial Intelligence) can be used to obtain the highest resolution images under any experimental conditions, and to use this to reproducibly control dynamic in-situ processes in gases and liquids on the nanoscale. As atomic diffusion under non-extreme conditions is typically in the sub-ms time domain, the ability to use this sub-sampling approach to reduce the effect of the electron beam and to speed-up the imaging process represents the optimum combination of spatial and temporal resolution achievable in a conventional microscope. This LDRD funding demonstrated the feasibility of imaging dynamics in complex energy systems using this methodology by establishing the optimum experimental sampling conditions (optimizing the number of pixels, speed, contrast and resolution) for each experiment. For in-situ liquid cell experiments this analysis shows that simply by distributing the same dose and dose rate maximally in space and time, the kinetics for radiolysis products can be modified significantly. The final stage of this work, i.e. the experimental demonstration of its use for nucleation and growth, was severely curtailed by issues with COVID19. However, all the experiments are designed and currently underway, with the goal to complete the final demonstration and publication as soon as safety concerns for laboratory access are met.

36 MATERIALS SCIENCE↗
DOE OSTI2023

3D printable polyvinyltoluene-based plastic scintillators with pulse shape discrimination

A feasibility of preparing bulk photopolymerized plastics scintillators that contain vinyltoluene with multifunctional monomers, pentaerythritol tetraacrylate is shown. This formulation offers a simple and fast way to prepare polyvinyltoluene-based plastics with efficient fast neutron/gamma pulse shape discrimination (PSD) within minutes. 30 wt% of 2,5-diphenyloxazole (PPO) was added in the mixtures of vinyltoluene and pentaerythritol tetraacrylate with different secondary dyes to understand the effect of dyes on the scintillation. Prepared resins were photopolymerized under different conditions, and the scintillation performance was compared to a commercially available standard, EJ-276. Additional functionality for thermal neutron sensitivity was introduced by the incorporation of 6 Li and 6 B nuclei. With optimized conditions, prepared plastics showed light output up to 90% relative to the same size of EJ-276. Here, the best plastic scintillators had PSD figures of merit (FoMs) up to 2.77 compared to 3.25 of EJ-276. The 3D-printability of the tested formulations was demonstrated.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimal generation and isolation of attosecond pulses in an overdriven ionized medium

We identify optimal conditions for the generation and isolation of attosecond pulses in an overdriven ionized medium. In a high-pressure and highly ionized gas, the spatiotemporal wavefront rotation of a driving laser can be optimized, leading to complete spatial separation of successive attosecond bursts in the far field. The resulting isolated attosecond pulses (IAPs) are much more divergent such that they are spatially separated from the driving laser in the far field. We show that the time delay of near-field harmonic emission along the radial distance determines the divergence of the attosecond burst in the far field. Here, the generated IAPs are phase matched upon propagation in the second half of the gas medium. Validity of the generation scheme is tested at different carrier–envelope phases for a few-cycle laser pulse and by synthesizing the fundamental and its second harmonic field for a long-duration pulse.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A Comparative Study of Compressive Effects on the Morphology and Performance of Carbon Paper and Cloth Electrodes in Redox Flow Batteries

Compressing porous carbon electrodes is a common approach to improve flow battery performance, but the resulting impact on electrode structure, fluid dynamics, and cell performance is not well understood. Herein, microtomographic imaging, load cell testing, and flow cell diagnostics are employed to characterize how compression‐induced changes impact pressure drop, polarization, and mass‐transfer scaling. Five different compressions are tested, spanning ranges typically used in literature, for AvCarb 1071 cloth (0%, 9%, 20%, 25%, 32%) and Freudenberg H23 paper (0%, 8%, 12%, 17%, 22%). It is found that the two electrode structures have distinct responses to compression, resulting in differing optimal conditions identified for each material; specifically, the Freudenberg H23 exhibits lower combined ohmic, charge‐transfer, and mass‐transport values at 8% compression, resulting in improved electrochemical performance across all compressive values, as compared to the optimal AvCarb 1071 compression (20%). Overall, Freudenberg H23 exhibits a greater sensitivity to compression with peak electrochemical activity correlating with increased permeability, whereas AvCarb 1071 is insensitive to compressive loads but produces lower electrochemical performance. Herein, the trade‐offs of mechanical robustness on fluid‐dynamic and electrochemical performance between the two electrodes are demonstrated by the aforementioned findings, suggesting each could be used for specific operating environments.

25 ENERGY STORAGE↗
DOE OSTI2021

Deformation of pores in response to uniaxial and hydrostatic stress cycling in Marcellus Shale: Implications for gas recovery

One of the main challenges during gas production from shale reservoirs is low recovery rate. One contributing factor to this outcome is an insufficient understanding of pore systems, especially pore behaviour following changes in reservoir conditions or resulting from gas production practices. Because the pressure in the producing well can be controlled, understanding the effects of pressure variation on the pore size distribution and methane trapping is necessary to help design optimal conditions to improve the gas recovery rate. This work is the first systematic study of sub-millimeter pore deformation in shale caused by uniaxial and hydrostatic stress up to 100 MPa. Overmature samples from the Middle Devonian Marcellus Shale were analyzed using neutron scattering (SANS and USANS) techniques to interpret the response of nanopores to stress cycling of magnitude and duration compatible with the hydraulic fracturing treatments. Experiments reported here are performed at a series of uniaxial pressures up to 100 MPa and at hydrostatic pressures of deuterated methane 0 and 50 MPa. Since at the original depth of the shale samples’ burial of 2184 m the hydrostatic pressure is approximately 27 MPa and the lithostatic pressure is about 55 MPa, the experimental conditions reasonably well simulate the reservoir pressure regime. Our SANS and USANS results show that different pore sizes are affected by uniaxial stress in different ways. Specifically, in the pore size range from 1 nm to 800 nm, a decrease of pore density with pressure is observed, with the most depleted being mesopores of about 100 nm in diameter. The observed decrease is likely related to deformation of kerogen, followed by a loss of pore nano-volume, as well as methane trapped in the micropores. For pores larger than 5 μm, USANS data suggest that the negative trend is reversed at above 74 MPa, and the number density of large macropores may increase with increased stress even above the original value. The increased number of macropores at high pressure may create new interconnected conduits for gas migration, resulting in a better recovery rate. Another important finding of this study is an irreversible rearrangement of pore size distribution taking place after pressure cycling. Furthermore, this irreversible reorganization of pore size distribution should be taken into account during management of well production to maximize recovery rate.

03 NATURAL GAS↗
DOE OSTI2025

Autonomous organic synthesis for redox flow batteries via flexible batch Bayesian optimization

Traditional trial-and-error methods for materials discovery are inefficient to meet the urgent demands posed by the rapid progression of climate change. This urgency has driven the increasing interest in integrating robotics and machine learning into materials research to accelerate experimental learning. However, idealized decision-making frameworks to achieve maximum sampling efficiency are not always compatible with high-throughput experimental workflows inside a laboratory. For multi-step chemical processes, differences in hardware capacities can complicate the digital framework by introducing constraints on the maximum number of samples in each step of the experiment, hence causing varying batch sizes in variable selection within the same batch. Therefore, designing flexible sampling algorithms is necessary to accommodate the multi-step synthesis with practical constraints unique to each high-throughput workflow. In this work, we designed and employed three strategies on a high-throughput robotic platform to optimize the sulfonation reaction of redox-active molecules used in flow batteries. Our strategies adapt to the multi-step experimental workflow, where their formulation and heating steps are separate, causing varying batch size requirements. By strategically sampling using clustering and mixed-variable batch Bayesian optimization, we were able to iteratively identify optimal conditions that maximize the yields. Our work presents a flexible approach that allows tailoring the machine learning decision-making to suit the practical constraints in individual high-throughput experimental platforms, followed by performing resource-efficient yield optimization using available open-source Python libraries.

Tamura, Clara [Univ. of Washington, Seattle, WA (U↗
DOE OSTI2024

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Development of a hybrid neural network and transfer learning model for optimized ICP-MS/MS operation

Correct function and calibration of instrumentation is a crucial assumption for any scientific experiment. One such instrument, tandem inductively coupled plasma mass spectrometer (ICP-MS/MS), has in-depth calibration settings that range across 30+ different parameters, making it difficult to determine optimal conditions without expertise and some degree of trial and error. Often, these settings are hand-tuned, a time-intensive process prone to local maxima and human error. While some automation is available, the automation also may favor local optimizations over a global optimum. In addition to these difficulties, day to day instrument variability can further complicate the calibration process. We propose a solution to this problem as a machine learning (ML) algorithm that learns how each parameter helps determine the calibration sensitivity across several elements, and re-weights parameters over time as instrument variability changes (e.g., a global neural network (NN) with a time-dependent transfer learning (TL) component). This model would be able to generate a surface of predicted calibration sensitivities and their respective parameters, and a simple multivariate algorithm would be able to pull out the optimum results with the settings associated with them. Here-in, we describe our initial findings in working towards this goal, including data extraction from historical files, exploratory data analysis, and some initial model building to better describe the data and the feasibility of our goal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Collaborative Decision Approach for Electricity Pricing-demand Response Stackelberg Game

Demand response programs are considered as a valuable resource in smart grids that provide several advantages of load shifting, peak load reduction, mediating intermittency of renewable energy integration, etc. Flexible price-based incentives have been recognized as a critical strategy in motivating and compensating consumers' load adjustment actions for successful implementation of demand response. Game theoretical approaches, especially Stackelberg games are popularly adopted to model the relationship between electricity price and customers' demand response and solved by the classical centralized backward induction (BI) method. However, the BI method generally requires convexity of the follower's model for necessary optimality conditions, and the computational time of any centralized approach increases sharply with larger problem instances. In this paper, the Stackelberg game of electricity pricing-demand response between a distribution system operator (DSO) and load aggregators (LAs) is decomposed based on a collaborative optimization (CO) framework, where each LA is treated as a discipline with its own domain constraints (e.g. building temperature control), while the DSO at the system level tries to reduce the solution discrepancy and guide the searching towards optimality. Several groups of comparison experiments have demonstrated the effectiveness of the proposed collaborative decision approach in solving the demand response game.

Chen, Yang↗
DOE OSTI2020

Conversion of Polyolefin Waste to Liquid Alkanes with Ru-Based Catalysts under Mild Conditions

Chemical upcycling of waste polyolefins via hydrogenolysis offers unique opportunities for selective depolymerization compared to high temperature thermal deconstruction. Here, we demonstrate the hydrogenolysis of polyethylene into liquid alkanes under mild conditions using ruthenium nanoparticles supported on carbon (Ru/C). Reactivity studies on a model noctadecane substrate showed that Ru/C catalysts are highly active and selective for the hydrogenolysis of C(sp 3 )–C(sp 3 ) bonds at temperatures ranging from 200 to 250 °C. Under optimal conditions of 200 °C in 20 bar H 2 , polyethylene (average M w ~ 4000 Da) was converted into liquid n-alkanes with yields of up to 45% by mass after 16 h using a 5 wt % Ru/C catalyst with the remaining products comprising light alkane gases (C 1 –C 6 ). At 250 °C, nearly stoichiometric yields of CH 4 were obtained from polyethylene over the catalyst. The hydrogenolysis of long chain, low-density polyethylene (LDPE) and a postconsumer LDPE plastic bottle to produce C 7 –C 45 alkanes was also achieved over Ru/C, demonstrating the feasibility of this reaction for the valorization of realistic postconsumer plastic waste. By identifying Ru-based catalysts as a class of active materials for the hydrogenolysis of polyethylene, this study elucidates promising avenues for the valorization of plastic waste under mild conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Electrocoagulation Combined with Ultrafiltration Membranes as Pretreatment for RO Desalination of Synthetic Cooling Tower Blowdown Water

Electrocoagulation (EC), an electrochemical water treatment process, is commonly used to remove particulate and colloidal matter from water. Here, in this study, we demonstrate that EC, when coupled with membrane filtration, is also capable of removing dissolved species, such as Ca + , Mg 2+ , and SiO x . The removal of such species is important for downstream membrane-based desalination treatment of the water that can suffer from reduced performance due to membrane scaling. Here, we describe how EC can be combined with a low-pressure membrane (LPM) system to offer efficient (and potentially universal) pretreatment for downstream membrane desalination. Synthetic water, simulating cooling tower blowdown (CTBD) with elevated concentrations of hardness and silicates (Ca: 418 ppm, Mg: 63 ppm, SiO 2 : 50 ppm) is treated using EC coupled to ultrafiltration (UF) to remove Mg up to 30 ± 1%, Ca up to 29 ± 1%, and silica up to 99 ± 1%. We evaluated the effectiveness of the EC-UF pretreatment system in reducing downstream RO scaling using thermodynamic modeling to predict the saturation index (SI) at the RO membrane/water interface. An SI value below zero (SI < 0) indicates under-saturated conditions (with respect to a particular mineral) where mineral scaling does not take place, which correlates with improved water recovery. Our findings suggest that the EC-UF pretreatment system was able to increase water recovery by up to 30%, compared to 0% recovery without pretreatment, under optimal conditions (feed solution pH of 7 and an EC charge loading of 1800 C/L). Finally, we conducted an economic analysis showing that implementing an EC-UF system for CTBD water could yield a cost benefit of up to $\$$14.13 per m 3 compared to direct brine disposal.

cooling tower blowdown↗
DOE OSTI2020

Inverse point source location with the Helmholtz equation on a bounded domain

The problem of recovering acoustic sources, more specifically monopoles, from point-wise measurements of the corresponding acoustic pressure at a limited number of frequencies is addressed. To this purpose, a family of sparse optimization problems in measure space in combination with the Helmholtz equation on a bounded domain is considered in this study. A weighted norm with unbounded weight near the observation points is incorporated into the formulation. Optimality conditions and conditions for recovery in the small noise case are discussed, which motivates concrete choices of the weight. The numerical realization is based on an accelerated conditional gradient method in measure space and a finite element discretization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Biological conversion of methane to methanol at high H 2 S concentrations with an H 2 S-tolerant methanotrophic consortium

To develop biological biogas to methanol conversion technology without costly hydrogen sulfide (H 2 S) removal, a high H 2 S tolerant methanotrophic consortium (HTMC), was enriched from an anaerobic digester effluent in presence of 5.64 g/m 3 H 2 S in the gas phase. The HTMC can grow stably and produce methanol under conditions with CH 4 /air mixtures containing 5.64 g/m 3 of H 2 S. There is no significant (p>0.05) difference in cell yield or CH 4 to methanol conversion efficiency between trials with different H 2 S concentrations from 0 g/m 3 to 5.64 g/m 3 . Further, under optimal conditions, a cell yield of 0.333 g cells/g CH 4 , a methanol concentration of 0.28 mg/mL, and a CH 4 to methanol conversion efficiency of 0.22 mol/mol were obtained, respectively. Besides methanotrophs (14.85%) and other bacteria, Cyanobacteria were also identified in the HTMC with a high abundancy (32.16%), which could broaden the application of HTMC for simultaneous utilization of CH 4 and CO 2 from raw biogas.

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

One‐Pot Synthesis of Xanthone by Carbonylative Suzuki Coupling Reaction

Abstract Xanthone derivatives have a dibenzo‐y‐pyrone scaffold which has gained great interest in Medicinal Chemistry due to their diverse biological activities. Usually, its synthesis requires multi‐step synthetic routes using harsh conditions and high catalyst loadings. In this communication, we report for the first time a one‐pot synthesis of the xanthone scaffold based on a carbonylative Suzuki coupling. Iodophenol and (2‐methoxyphenyl)boronic acid were coupled under carbon monoxide, generated from a carbon monoxide surrogate. An experimental data‐based model was built to guide the reaction optimization. The optimized conditions were 1 mol% of a pincer complex as palladium catalyst, 5 equivalents of K 2 CO 3 as base, and DMF:water (7 : 3) as solvent. The robustness of the synthetic method, namely in terms of the reactants scope, was also evaluated. This approach provided the xanthone scaffold in high yields and provided a deep insight into the carbonylative Suzuki couplings.

Loureiro, Daniela R. P.↗
DOE OSTI2025

Refining seasonal performance metrics for room air-conditioning in emerging markets: Integrating building simulations with real-world equipment performance data

Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can vary significantly based on climate conditions, with observed CSPF ranging from 4.10 to 11.59 Wh/Wh across 577 Brazilian climates. The inclusion of UHI effects led to a reduction in CSPF values by up to 29% during nighttime operations in hot urban areas. Additionally, building envelope efficiency showed contrasting impacts on RAC performance, with CSPFs reaching up to 15.35 Wh/Wh under specific optimized conditions. These findings highlight the need for transparent policymaking in RAC performance databases, facilitating the application of approaches like those proposed in this study and supporting diverse stakeholders in decision-making.

Bavaresco, Mateus↗
DOE OSTI2024

Regulation of NMDAR activation efficiency by environmental factors and subunit composition

NMDA receptors (NMDAR) convert the major excitatory neurotransmitter glutamate into a synaptic signal. A key question is how efficiently the ion channel opens in response to the rapid exposure to presynaptic glutamate release. Here, we applied glutamate to single channel outside-out patches and measured the successes of channel openings and the latency to first opening to assay the activation efficiency of NMDARs under different physiological conditions and with different human subunit compositions. For GluN1/GluN2A receptors, we find that various factors, including intracellular ATP and GTP, can enhance the efficiency of activation presumably via the intracellular C-terminal domain. Notably, an energy-based internal solution or increasing the time between applications to increase recovery time improved efficiency. However, even under these optimized conditions and with a 1-s glutamate application, there remained around 10–15% inefficiency. Channel activation became more inefficient with brief synaptic-like pulses of glutamate at 2 ms. Of the different NMDAR subunit compositions, GluN2B-containing NMDARs showed the lowest success rate and longest latency to first openings, highlighting that they display the most distinct activation mechanism. In contrast, putative triheteromeric GluN1/GluN2A/GluN2B receptors showed high activation efficiency. Despite the low open probability, NMDARs containing either GluN2C or GluN2D subunits displayed high activation efficiency, nearly comparable with that for GluN2A-containing receptors. These results highlight that activation efficiency in NMDARs can be regulated by environmental surroundings and varies across different subunits.

He, Miaomiao (ORCID:0000000203179136)↗
DOE OSTI2022

Benzyl trichloroacetimidates as derivatizing agents for phosphonic acids related to nerve agents by EI-GC-MS during OPCW proficiency test scenarios

Abstract The use of benzyl trichloroacetimidates for the benzylation of phosphonic acid nerve agent markers under neutral, basic, and slightly acidic conditions is presented. The benzyl-derived phosphonic acids were detected and analyzed by Electron Ionization Gas Chromatography–Mass Spectrometry (EI-GC–MS). The phosphonic acids used in this work included ethyl-, cyclohexyl- and pinacolyl methylphosphonic acid, first pass hydrolysis products from the nerve agents ethyl N -2-diisopropylaminoethyl methylphosphonothiolate (VX), cyclosarin (GF) and soman (GD) respectively. Optimization of reaction parameters for the benzylation included reaction time and solvent, temperature and the effect of the absence or presence of catalytic acid. The optimized conditions for the derivatization of the phosphonic acids specifically for their benzylation, included neutral as well as catalytic acid (< 5 mol%) and benzyl 2,2,2-trichloroacetimidate in excess coupled to heating the mixture to 60 °C in acetonitrile for 4 h. While the neutral conditions for the method proved to be efficient for the preparation of the p -methoxybenzyl esters of the phosphonic acids, the acid-catalyzed process appeared to provide much lower yields of the products relative to its benzyl counterpart. The method’s efficiency was tested in the successful derivatization and identification of pinacolyl methylphosphonic acid (PMPA) as its benzyl ester when present at a concentration of ~ 5 μg/g in a soil matrix featured in the Organisation for the Prohibition of Chemical Weapons (OPCW) 44th proficiency test (PT). Additionally, the protocol was used in the detection and identification of PMPA when spiked at ~ 10 μg/mL concentration in a fatty acid-rich liquid matrix featured during the 38 th OPCW-PT. The benzyl derivative of PMPA was partially corroborated with the instrument's internal NIST spectral library and the OPCW central analytical database (OCAD v.21_2019) but unambiguously identified through comparison with a synthesized authentic standard. The method’s MDL (LOD) values for the benzyl and the p -methoxybenzyl pinacolyl methylphosphonic acids were determined to be 35 and 63 ng/mL respectively, while the method’s Limit of Quantitation (LOQ) was determined to be 104 and 189 ng/mL respectively in the OPCW-PT soil matrix evaluated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗