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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Agent-based modeling to evaluate the effects of harvesting biomass and hunting on ring-necked pheasant ( Phasianus colchicus ) populations

As the US strives to divest from fossil fuels, dedicated energy crops have increased in popularity because of their potential to serve as a renewable source of transportation fuel and biomass-generated electricity. Whereas the impacts of crop agriculture on biodiversity have been well-documented, less is known about the potential impacts that growing bioenergy crops could have on wildlife. Here we look specifically at the ring-necked pheasant (Phasianus colchicus) and how pheasant populations may be influenced by growing and harvesting bioenergy crops. We explored effects of temporal harvest strategies at the field scale on biomass yield and pheasant population size. To investigate, we developed an agent-based model (ABM) that simulates ring-necked pheasants, tractors, hunters, and vegetation classes. One such vegetation class is land that is enrolled in a Conservation Reserve Program (CRP) plan specifically targeting pheasant conservation. Using this ABM, we assessed four different landscapes—corn-dominated, CRP-dominated, grassland-dominated, and mixed landscape—under strategies that varied the time of harvest. We also used ecological valuation to compare scenario outcomes from an economic perspective. We determined that biomass yield and pheasant population size were sensitive to harvesting times. Our scenarios totaled between ~$931,000 (minimum) and $3.8 million (maximum) over all landscapes, though on average harvesting in late spring generated the most value ($2.45 million) and harvesting in fall was a close second in terms of profitability ($2.39 million).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Agentic framework for programmatic crystal structure generation using a fine-tuned worker–supervisor large language model

Platinum group metals (PGMs) underpin many catalytic technologies but face severe supply constraints, motivating the search for alternative materials and computational methods to accelerate discovery. While atomistic simulation tools such as Pymatgen and ASE have streamlined structure manipulation, they require detailed inputs, limiting accessibility for experimentalists and slowing early-stage exploration. Here, in this study, we present an AI-driven agentic framework that orchestrates worker–supervisor large language models (LLMs). The worker translates natural-language prompts of varying abstraction into valid crystallographic structures using a compact LLM fine-tuned with low-rank adaptation on a curated text–code–CIF dataset, emphasizing energy-efficient training. Benchmarking against the baseline CodeGen-350M-mono model shows that fine-tuning reduces hallucination rates from 100% to as low as 5% and improves structural match accuracy to up to 82% for fully specified inputs. Accuracy declines with decreasing prompt detail but remains nontrivial even when only stoichiometry and space group are provided, underscoring the LLM’s capacity for crystallographic inference. The supervisor Claude LLM evaluates the outputs and triggers iterative refinement through the worker’s built-in structure manipulation capabilities (e.g., supercell scaling, strain, vacancy, and substitution operations). We further demonstrate use cases for technologically relevant catalysts, including IrO 2 , pyrochlore Pb 2 Ir 2 O 7 , Ni 2 FeO 4 , and Ni 3 Mo, where the framework generates physically consistent structures that can be refined via geometry optimization. This work introduces a low-energy, language-driven pathway for integrating human and machine intelligence in materials design, paving the way for AI-assisted synthesis planning and high-throughput screening of complex oxides.

AI agent↗
DOE OSTI2018

An agent-based hardware-in-the-loop simulation framework for building controls

In general, a hardware-in-the-loop (HIL) building simulation has lower cost and fewer practical limitations (e.g., scheduling issues) than field tests in occupied buildings, while also overcoming limitations of simulations alone by capturing the full behavior of some physical systems, equipment, and components. However, the implementation of an HIL can be difficult due to the scarcity of appropriate tools. Here, this paper presents an agent-based framework for HIL simulation. It can be used for investigation of controller performance via controller-in-the-loop simulations and also HIL for system synthesis. In the latter case, both controllers and major equipment participate in tests to ensure that dynamics of equipment operation are correctly captured in addition to controller performance. The HIL simulation framework presented allows such actual physical parts to be included in the framework while representing others for which behaviors are better known and modeled in simulation models. The mechanism implemented in the framework to synchronize simulations in software with real-time operation of physical equipment is described. Lastly, as an example, use of the HIL simulation framework is illustrated through a brief study of speed control of the supply fan in the air handling unit of a variable-air-volume building heating, ventilating and air-conditioning system.

42 ENGINEERING↗
DOE OSTI2021

A multi-agent approach to distribution system fault section estimation in smart grid environment

We report that Multi-Agent Systems (MAS) are seen from different areas as one of the paramount trends for the next generation of power systems. Numerous published studies about MAS discuss its utilization in power distribution networks but none focuses on the prior step to restoration and self-healing that is fault section estimation. This paper aims to show how MAS can improve the utilities’ reliability indexes and consumer satisfaction by overcoming the multiple fault section estimation problem. In order to do this, the authors considered using MAS as a means of communication between smart meters. The purpose of smart meters usage is to employ devices that are already present in smart grids, mainly because of their reading and saving data capacity. The proposed method was tested on a radial feeder generated by the authors. The network was built on HYPERSIM, a software platform of OPAL-RT Technologies. The simulation results show that this MAS provides speed, efficiency, and automation for the process of fault section estimation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Assessment of two benzylation strategies for the analysis of nerve-agent derived ethyl- and pinacolyl methyl phosphonic acids in sandy loam soil by GC–MS

Despite their prohibition by the Chemical Weapons Convention, nerve agents (NAs) remain in use against military and civilian targets. Due to their high reactivity, NAs readily degrade to phosphonic acids, making them important markers in the inspection of areas of presumed NA use. In this work, we assess the use of benzylation to modify ethyl- and pinacolyl methylphosphonic acids, degradation products of VX and Soman respectively, for their efficient detection in a soil matrix at ~10 and ~1 μg/g using GC–MS. The soil matrix, Sandy Loam (SL), was chosen for its ubiquitous nature, complex composition with silica particles embedded in clay, and low organic content. In this study, we demonstrate that benzylation via benzyl bromide yields a LOD = 25.6 ng/mL for benzylated-EMPA and LOD = 30.1 ng/mL for benzylated-PMPA. This is superior to the use of p-methoxybenzyl trichloroacetimidate in providing stable phosphonic acid ester derivatives for analysis. A base-modified procedure for p-methoxybenzylation was explored in this study yielding a LOD = 29.1 ng/mL for p-methoxybenzylated-EMPA and LOD = 39.8 ng/mL for p-methoxybenzylated-PMPA. Both benzylation pathways (benzyl bromide and p-methoxybenzyl trichloroacetimidate) can be used to yield phosphonic acid derivatives that provide further confirmation of these Soman and VX degradation products in soil samples in investigative scenarios. The work herein represents the first application of benzylation methods for the analysis of these NA markers in the acidic, silicon-based SL soil.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Efficient derivatization of methylphosphonic and aminoethylsulfonic acids related to nerve agents simultaneously in soils using trimethyloxonium tetrafluoroborate for their enhanced, qualitative detection and identification by EI-GC–MS and GC–FPD

Trimethyloxonium tetrafluoroborate (TMO·BF 4 ) has been used here in the simultaneous derivatization of phosphonic and 2-aminoethylsulfonic acids related to nerve agents in different soils for their enhanced detection and identification by electron ionization gas chromatography-mass spectrometry (EI-GC–MS). The panel of acids consisted of five Schedule 2 phosphonic acids (methyl methylphosphonic acid, ethyl methylphosphonic acid, isopropyl methylphosphonic acid, pinacolyl methylphosphonic acid and cyclohexyl methylphosphonic acid) along with two sulfonic acids, N,N-diethyl-2-aminoethylsulfonic acid and N,N-diisopropyl-2-aminoethylsulfonic acid. The acids were converted to their corresponding methyl esters at ambient temperature when present at a 10 μg g -1 concentration in three separate soils: Virginia type A soil, Ottawa sand and Nebraska EPA soil. The concentration of the acids reflects values typically encountered during proficiency tests (PTs) administered annually by the Organisation for the Prohibition of Chemical Weapons (OPCW). Derivatization times to yield detectable signals for the methyl ester products for all the acids was found to vary among all three soil samples, however, it was found that generally the most optimal time across all the matrices involved was 3 h after the addition of TMO·BF 4 . Concomitantly, the analysis of the samples was complemented using GC coupled to flame photometric detection (GC–FPD). The inclusion of GC–FPD in the analysis yielded stronger signals for all seven methylated analytes making their detection after merely 3 h possible relative to the ones initially obtained with EI-GC–MS. Regarding the three soils employed in our study, a greater methylating efficiency was found in the Virginia type A soil and Ottawa sand yielding results that were significantly larger in magnitude to those found during the same time points for the Nebraska EPA soil sample. Prolonged reaction times (up to 72 h) were explored to find the time for the highest yield of methyl ester production were found instead to be deleterious to the process showcasing the importance of the fast yielding nature of the process specifically in situations where time-sensitive analysis is crucial (e.g. OPCW-PT).

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

Simulating policy interventions in the interfirm diffusion of low-carbon technologies: An agent-based evolutionary game model

Policy interventions are frequently used by authorities around the world to mitigate carbon emissions. However, economic systems are essentially complex adaptive systems, which often exhibit unexpected responses to exogenous interventions and leave intervenors in a dilemma, even if the interventions are elaborately designed. To explore the behaviors of the diffusion system regarding low-carbon technologies, this study builds an agent-based model (ABM) to simulate enterprises' reactions to multiple policy interventions aimed at spurring low-carbon technology diffusion. The simulated enterprises are in a complex network where they play evolutionary games with their neighbors, which enables the model to possess two critical features of economic systems: adaptiveness and equilibrium. The model reveals a dilemma of policy interventions: intuitively, carbon taxes, asymmetric penalties (only imposed on un-low-carbon enterprises) and subsidies can improve the diffusion, which is consistent with previous research; counter-intuitively, all these policies turn out to be inefficient or even harmful to low-carbon enterprises because of the diffusion system's high adaptiveness. Specifically, when carbon taxes and penalties increase, both the low-carbon and un-low-carbon enterprises end up with the equilibrium of equivalent but lower profits. In contrast, all the enterprises earn equivalent but more profits even though subsidies are only given to the low-carbon enterprises, which implies that the un-low-carbon enterprises (indirectly) grab a portion of the subsidies and accordingly weaken the incentive effect of subsidies. These system behaviors are summarized as "equalizing effect" because the system tends to equalize the impact of both positive and negative interventions among all enterprises even though the policy interventions are asymmetrically imposed on one type of the enterprises. The findings also indicate that policies implemented to enlarge green market sizes can help policymakers bypass the dilemma.

Agent-based modeling↗
DOE OSTI2019

Microstructural investigation of an extruded austenitic oxide dispersion strengthened steel containing a carbon-containing process control agent

The adhesion of austenitic oxide dispersion strengthened (ODS) steel during mechanical alloying and a decreased powder production yield can be overcome by the addition of a process control agent: stearic acid. Here, the influence of stearic acid and the introduction of carbon in an extruded and annealed austenitic ODS steel was investigated. In particular the impact of carbon on the precipitate formation, the stability of particle and grain sizes during a heat treatment of 2 h at temperatures in a range between 500 and 1100 °C and the resulting grain size were investigated. No direct influence of carbon on the formation of precipitates was detected in the as-extruded condition. The orientation relationship of oxide nano-particles and the austenitic matrix was found to be size dependent. Also, a surprising growth of oxide precipitates was recorded, which starts at annealing temperatures as low as 700 °C. Precipitates in other steels do not show a growth in this temperature regime at all. For that reason, a possible link between the unexpected growth and the formation of carbides was investigated. M 7 C 3 and M 23 C 6 carbides were found in every sample condition and we were able to show that their amount follows a trend suggested by thermodynamic simulations. The grain size of the extruded austenitic ODS steel was examined and a grain refinement was found after a heat treatment of 2 h at 700 °C or higher was performed. That is caused by the inhabitation of further grain growth after nucleation as part of the recrystallization process has happened. The dragging force exerted by precipitates is strong enough to pin grain boundaries. Furthermore, no direct impact of carbon on the oxide precipitate growth was found, an indirect impact of carbon on the growth of ODS precipitates is supposed but requires long-term annealing studies to be verified.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Agent-based modeling of supply disruptions in the global rare earths market

Several independent assessments have identified rare earth elements (REEs) as critical materials, notably neodymium (Nd), praseodymium (Pr), and dysprosium (Dy) used in permanent magnets. Factors affecting their criticality include expected growth in demand arising from their unique performance-enhancing properties in consumer, energy, and military applications and the supply risk associated with China's dominance in their production. We demonstrate the use of Argonne's Global Critical Materials (GCMat) agent-based model to explore the possible consequences to REE market dynamics of different types of regional supply disruptions including a temporary loss of production, shutdown of capacity, and diversion of supply. Results suggest that supply disruptions may foster earlier and more REE mine starts outside of China, although some of these mines may not be able to sustain operations post disruption. Further, price and associated market responses such as production, capacity, and demand tended to extend beyond the disruption period. Such market impacts in the magnet supply chain could affect the costs and availability of a number of emerging clean energy technology applications such as electric vehicles and wind turbines. In the future, GCMat could be used to evaluate the effectiveness of mitigation strategies - including recycling, conservation, product substitution, and diversification of supplies - on reducing the severity of disruptions in REE markets.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Methylation protocol for the retrospective detection of isopropyl-, pinacolyl- and cyclohexylmethylphosphonic acids, indicative markers for the nerve agents sarin, soman and cyclosarin, at low levels in soils using EI-GC–MS

A practical and efficient protocol for the derivatization and detection by GC-EI-MS of isopropyl-, pinacolyl- and cyclohexylmethylphosphonic acids, key diagnostic degradation products of the nerve agents sarin, soman and cyclosarin respectively, in six different types of soil matrices is presented here. The method involves the in situ conversion of the phosphonic acids to their respective methyl esters using trimethyloxonium tetrafluoroborate when present in the soils at low levels (10 μg g -1 ) without any prior extractions or soil preparation. The soils employed in our study were Nebraska EPA soil, Georgia soil, silt, Virginia type A soil, regular sand and Ottawa sand and were chosen for their vast differences in composition and physical features. Appealing attributes of the protocol include its rapidity (t < 30 min), mildness (ambient temperature), and practicality that includes the production of the phosphonic methyl esters that can be easily detected by GC-EI–MS and corroborated with the instrument&#x27;s internal NIST spectral library or the Organisation for the Prohibition of Chemical Weapons (OPCW) central analytical database (OCAD v.21_2019). The overall efficacy of the protocol was then tested on a soil sample featured in the 44th OPCW PT that our laboratory participated in. After preparing the soil so as to give pinacolyl methylphosphonic acid at a 5 μg g -1 concentration, the acid was successfully methylated and detected by GC-EI-MS. The protocol's performance mirrors that of the universally employed diazomethane protocol but accomplishes this without any of the explosive hazards and time consuming reagent preparation commonly associated with it.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

A comprehensive evaluation of the efficacy of leading oxime therapies in guinea pigs exposed to organophosphorus chemical warfare agents or pesticides

The currently fielded pre-hospital therapeutic regimen for the treatment of organophosphorus (OP) poisoning in the United States (U.S.) is the administration of atropine in combination with an oxime antidote (2-PAM Cl) to reactivate inhibited acetylcholinesterase (AChE). Depending on clinical symptoms, an anticonvulsant, e.g., diazepam, may also be administered. Unfortunately, 2-PAM Cl does not offer sufficient protection across the range of OP threat agents, and there is some question as to whether it is the most effective oxime compound available. The objective of the present study is to identify an oxime antidote, under standardized and comparable conditions, that offers protection at the FDA approved human equivalent dose (HED) of 2-PAM Cl against tabun (GA), sarin (GB), soman (GD), cyclosarin (GF), and VX, and the pesticides paraoxon, chlorpyrifos oxon, and phorate oxon. Male Hartley guinea pigs were subcutaneously challenged with a lethal level of OP and treated at approximately 1 min post challenge with atropine followed by equimolar oxime therapy (2-PAM Cl, HI-6 DMS, obidoxime Cl{sub 2}, TMB-4, MMB4-DMS, HLö-7 DMS, MINA, and RS194B) or therapeutic-index (TI) level therapy (HI-6 DMS, MMB4-DMS, MINA, and RS194B). Clinical signs of toxicity were observed for 24 h post challenge and blood cholinesterase [AChE and butyrylcholinesterase (BChE)] activity was analyzed utilizing a modified Ellman's method. When the oxime is standardized against the HED of 2-PAM Cl for guinea pigs, the evidence from clinical observations, lethality, quality of life (QOL) scores, and cholinesterase reactivation rates across all OPs indicated that MMB4 DMS and HLö-7 DMS were the two most consistently efficacious oximes. - Highlights: • First comprehensive evaluation of leading AChE oxime reactivators • All oximes are compared against current U.S. therapy 2-PAM Cl. • Relative therapeutic oxime efficacies against OP CWNA and pesticides • Contribution to more effective antidotes for civilian and military populations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Improved chemical synthesis, identification and evaluation of prospective centrally active oxime antidotes for the treatment of nerve agent exposure

In this study, an improved method for the synthesis of hydroxyiminoacetamide-based oximes, compounds rhat hold great promise as centrally-active nerve agent antidotes, is described. The method involves the coupling of hydroxyiminoacetic acid to various amines in the presence of HOBT or HATU and diisopropylcarbodiimide. The optimized protocol was found to work effectively for the coupling with amines to the activated form of the hydroxyiminoacetic acid with yields ranging between 84 and 90% for primary amines, 65–75% for α-substituted and cyclic amines, while producing decent 41–48% yields for the sterically hindered α,α-substituted amines, that can not be obtained using the previously established method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plans in terms of average delay, number of stops, and vehicular emissions at the network level.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

Here, we discuss the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Lastly, initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.

42 ENGINEERING↗
DOE OSTI2023

Linking transportation agent-based model ($\mathrm{ABM}$) outputs with micro-urban social types ($\mathrm{MUSTs}$) via typology transfer for improved community relevance

The human relationship with transportation is shaped by social, economic, demographic, and urban form variables, or socio-spatial factors. The spatial dynamics of these are key to generating and interpreting outputs of transportation models that are most relevant for a community and the diverse mobility needs of its members. Here we present a typology transfer framework, grounded in socio-spatial dynamics shaping people's mobility, to take transportation-themed regional mobility model outcomes, in this case from two agent-based models (ABMs), and extrapolate them to other cities, with less time and resource intensity than new ABM development. The typology transfer process first identifies micro-urban social types (MUSTs) using socio-spatial factors, then defines city types based on spatial patterns of MUSTs to assess across which cities transfer results are likely to best hold. Lastly, a typology transfer multiplier matrix extrapolates a given variable, in our case the Mobility Energy Productivity (MEP) metric, to another city. The full process demonstration uses ABM results from Chicago (POLARIS model) and San Francisco (BEAM model), applying them to New York City. We discuss how MEP or other outputs can be appropriately estimated and used for integrated, human-centered mobility analysis. Key findings include that this MUST framework of user-defined dependent and independent variables allows tailoring ABM results and interpretations to specific community needs and data availability. Findings clarify that positive outcomes can be targeted towards user groups, based on sociospatial characteristics, using a typology approach, such as inclusive access to mobility choices, transportation affordability, and greater efficiency in resource use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Laponite-Incorporated UiO-66-NH2-Polyethylene Oxide Composite Membranes for Protection against Chemical Warfare Agent Simulants

A strategy is developed to enhance the barrier protection of polyethylene oxide (PEO)-metal–organic framework (MOF) composite films against chemical warfare agent simulants. To achieve enhanced protection, an impermeable high-aspect-ratio filler in the form of Laponite RD (LRD) clay platelets was incorporated into a composite PEO film containing MOF UiO-66-NH 2 . The inclusion of the platelets aids in mitigating permeation of inert hydrocarbons (octane) and toxic chemicals (2-chloroethyl ethyl sulfide, 2-CEES) of dimensions/chemistry similar to prominent vesicant threats while still maintaining high water vapor transport rates (WVTR). By utilizing small-angle neutron scattering, small-angle X-ray scattering, and wide-angle X-ray scattering, the LRD platelet alignment of the films was determined, and the structure of the films was correlated with performance as a barrier material. Performance of the membranes against toxic chemical threats was assessed using permeation testing of octane and 2-CEES, a common simulant for the vesicant mustard gas, and breathability of the membranes was assessed using WVTR measurements. To assess their robustness, chemical exposure (in situ diffuse reflectance infrared Fourier transform spectroscopy) and mechanical (tensile strength) measurements were also performed. It was demonstrated that the barrier performance of the film upon inclusion of the LRD platelets exceeds that of other MOF-polymer composites found in the literature and that this approach establishes a new path for improving permselective materials for chemical protection applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Paramagnetic Mn 8 Fe 4 -co-Polystyrene Nanobeads as a Potential T 1 –T 2 Multimodal Magnetic Resonance Imaging Contrast Agent with In Vivo Studies

In developing a cluster-nanocarrier design, as a magnetic resonance imaging contrast agent, we have investigated the enhanced relaxivity of a manganese and iron-oxo cluster grafted within a porous polystyrene nanobead with increased relaxivity due to a higher surface area. The synthesis of the cluster-nanocarrier for the cluster Mn 8 Fe 4 O 12 (O 2 CC 6 H 4 CH=CH 2 ) 16 (H 2 O) 4 , cross-linked with polystyrene (the nano-carrier), under miniemulsion conditions is described. By including a branched hydrophobe, iso-octane, the resulting nanobeads are porous and similar to 70 nm in diameter. The increased surface area of the nanobeads compared to nonporous nanobeads leads to an enhancement in relaxivity; r 1 increases from 3.8 to 5.2 ± 0.1 mM -1 s -1 , and r 2 increases from 11.9 to 50.1 ± 4.8 mM -1 s -1 , at 9.4 teslas, strengthening the potential for T 1 and T 2 imaging. Several metrics were used to assess stability, and the porosity produced no reduction in metal stability. Synchrotron X-ray fluorescence microscopy was used to demonstrate that the nanobeads remain intact in vivo . In depth, physicochemical characteristics were determined, including extensive pharmacokinetics, in vivo imaging, and systemic biodistribution analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Adsorption and Destruction of the G-Series Nerve Agent Simulant Dimethyl Methylphosphonate on Zinc Oxide

Organophosphorus chemical warfare agents (CWAs) are extremely toxic compounds that are nominally mitigated with gas mask filtration employing metal oxide impregnated activated carbon filtration material. To develop more effective sorbents, it is important to understand the surface chemistry between these organophosphorus compounds and the individual components that make up these filtration materials. In this study, density functional theory (DFT) and Fourier transform infrared spectroscopy (FTIR) were employed to investigate the adsorption and decomposition mechanisms between a sarin simulant molecule, dimethyl methylphosphonate (DMMP), and zinc oxide, which is a component found in current filtration materials. Theoretical calculations show that DMMP readily adsorbs to a pristine and hydroxylated ZnO ($101\bar 0$) surface with average adsorption energies of 132 and 65 kJ mol –1 , respectively. Experimental diffuse reflectance fourier transform infrared spectroscopy (DRIFTS) reveals that ZnO adsorbs water and readily hydroxylates under ambient conditions, which can facilitate adsorption through hydrogen bonding of the P$=$O to ZnO surface hydroxyls. FTIR gas phase analysis also reveals that DMMP decomposes in the presence of ZnO nanoparticles (NPs) to produce methanol at room temperature. Assuming a fully hydroxylated surface of ZnO, DFT calculations reveal several plausible mechanisms for DMMP decomposition to form methanol with an activation energy barrier of 99.6 kJ mol –1 . Finally, on the basis of this energy barrier to decompose DMMP, a turnover frequency (TOF) of only 3.5 × 10 –7 s –1 is calculated assuming full coverage of DMMP on the ZnO nanoparticles tested. This value is qualitatively consistent with experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗