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Sarin simulations

Production, Import/Export, Use, Release, and Disposal. The risk for exposure of the general population to substantial levels of diisopropyl methylphosphonate is quite low. GB (Sarin) and diisopropyl methylphosphonate have not been produced in the United States since 1957, and there is no indication that U.S. production of these chemicals will resume (EPA 1989). No information exists regarding the import or export of diisopropyl methylphosphonate. Diisopropyl methylphosphonate has no known commercial uses, but has been used by the military as a simulant for chemical warfare agents (Van Voris et al. 1987). [Pg.127]

This material is a precursor for Sarin (C01-A002) and is also commonly found as a decomposition product/impurity (up to 20% ) in sarin. If fluoride ion is present and the pH falls below 7, sarin will be formed. This material has been used as a simulant for nerve agents in government tests. [Pg.44]

Figure 1 Structures of chemical warfare agents (sarin and soman), simulants (dimethyl methylphosphonate and diisoproyl fluorophosphate), and pesticides (paratliion and diazinon). Figure 1 Structures of chemical warfare agents (sarin and soman), simulants (dimethyl methylphosphonate and diisoproyl fluorophosphate), and pesticides (paratliion and diazinon).
Other industrially important uses of P4O10 include the reactions with ethers, an example of which is the formation of triethyl phosphate via reaction with diethyl ether followed by pyrolysis. The product (which has a worldwide production of many thousands of tons per annum) finds use as ketene synthesis, a flame retardant, and a plasticizer within the plastics industry a less conventional use is as a simulant for the sarin when modeling situations involving the latter nerve agent. [Pg.3709]

FIGURE 51.1. PBPK-PD model schematic of sarin in Hartley guinea pig. This model structure allows for the simulation of experimental studies with dosing hy intravenous or subcutaneous dosing, and inhalation exposure. This model design was after Gearhart et al. (1990) and was adapted to simulate the pharmacokinetics and pharmacodynamics of sarin in the guinea pig. [Pg.792]

FIGURE 51.9. PBPK-PD simulation of regenerated sarin in the guinea pig after an SC dose of 0.1 LD50 (0.0042 mg/kg body weight) and 0.4 LD50 (0.0168 mg/kg body weight). [Pg.796]

FIGURE 51.11. Overlay of the simulation of regenerated RBC sarin after a 0.1 LD50 SC dose of sarin vs IH dosing simulation at the inhalation concentration required to reproduce the SC data. [Pg.796]

FIGURE 62.4. RBC AChE inhibition in rhesus monkey following administration of sarin [0.75 LD50 (15 pg/kg) i.v.] and with 2-PAM (25.8mg/kg) administered IM at 9 min postsarin i.v. administration. Atropine was administered (0.4 mg/kg) IM 15 min prior to sarin administration. The filled circles indicate experimental data (Woodard et al, 1994) the curves show our PBPK model simulations of AChE activity after sarin, both with (upper curve) and without (lower curve) 2-PAM administration. [Pg.957]

Wolthuis, O.L., R.A. Vanwersch and H.P. Van Helden. 1986. Residual behavioral incapacitation after therapy of soman intoxication the effect of a soman simulator. Neurohehav Toxicol Teratol 8(2) 127-30. Yanagisawa, N., H. Morita and T. Nakajima. 2006. Sarin experiences in Japan acute toxicity and long-term... [Pg.652]

Following these CNT electronic gas sensor studies, many other methods have been explored focusing on the reduction of fabrication cost. Snow et al. demonstrated that a low-density random network of SWCNTs can be fabricated into p-type thin-fllm transistors [Figure 14.7(c)] with a fleld-effect mobility of about 10 cm / Vs and an on-to-off ratio of about 10 [65]. They demonstrated that such thin-fllm transistors can detect dimethyl methylphosphonate (DMMP), a simulant for the nerve agent sarin, at sub-ppb levels [45]. SWCNT network transistors have also been transferred to polymer substrates to form flexible electronic gas sensors [66]. Other resistive sensors based on random SWCNT network [47] or MWCNT films [41] have also been reported. Besides the cost, CNT network and thin-film sensors increase the statistical reliability by averaging out the response at many adsorption sites. This is particularly important when gas concentration is extremely small. [Pg.520]


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See also in sourсe #XX -- [ Pg.71 , Pg.75 ]




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