Predictive Methods for Environmental Screening of New Materials Randall J. Cramer, Ph.D. Indian Head Division Naval Surface Warfare Center Indian Head, MD Jay Clausen U.S. Army Corps of Engineers, ERDC-CRREL Hanover, NH 2005 Joint Services Environmental Management Conference and Exposition April 11-14, 2005 Tampa Convention Center Tampa, FL

World of Energetics apply as is define uncertainty adapt or alter Predictive Modeling and Characterization of Environmental and Human Health Issues ID Gaps Predictive assessment framework for human health and environmental F&T using a minimum of empirical measurements. How to address: unpredictable chronic effects? --salt accumulation in high water content plants Existing Risk Assessment Tools Was Used Currently In Use Possibly Soon Someday Maybe In high water

SERDP PP-1403 Synthesis, Evaluation, and Formulation Studies On New Oxidizers as Alternatives to Ammonium Perchlorate in DoD Missile Propulsion Applications. M. Dewey, ATK Thiokol; W. Koppes, Indian Head Division Naval Surface Warfare Center. Develop environmentally benign solid rocket propellant formulations that do no rely on the use of perchlorate.

Answer questions early: Is this the right thing to use? Objective Answer questions early: Is this the right thing to use? Use existing predictive models to estimate environmental properties of proposed perchlorate replacements Provide an initial assessment of model sensitivity to input parameters

Approach Step 1. Conduct Literature Search Conduct literature search to obtain fate, transport, and toxicity relevant information for target compounds. Step 2. Perform Screening Level Assessment Use EPA EPI-Suites QSAR Models (output derived from databases comparing compounds of similar structure). Step 3. Evaluate Model Certainty Compare predicted results with surrogate chemicals with published chemical data.

Structures in the Study Ammonium di(nitramido) amine (ADNA) Ammonium dinitramide (ADN)

Structures in the Study O 2 Tetranitrohexahydropyrimidine (DNNC) Cyclotrimethylenetrinitramine (RDX)

Structures in the Study O 2 Hexanitrodiazacyclooctane (HCO) Cyclotetramethylenetetranitramine (HMX)

Structures in the Study NO2 2HN Diammonium di(nitramido) dinitroethylene (ADNDNE) 1,1-Diamino-2,2-dinitro-ethylene (FOX-7)

Boundary Conditions Chemical in the ambient state Pure compound without additional interacting propellant ingredients Neat oxidizer not including combustion products

Results Step 1. Conduct Literature Search Results compiled in report to SERDP Environmental Screening Assessment of Perchlorate Replacements, 4 October, 2004 For a copy: randall.cramer@navy.mil

Results Step 2. Perform Screening Level Assessment Apply QSAR models to predict physical chemical properties Assess fate, transport, and aquatic toxicity of oxidizers using screening level tools Predict how chemical might partition to air, water, soil, and sediment if introduced into the environment

Estimation Program Interface (EPI) Suite* Publicly available Windows® based suite developed by EPA Comprised of individual modules designed to estimate a specific property Runs from a single input Simplified Molecular Input Line Entry System (SMILES) notation of the chemical structure * http://www.epa.gov/opptintr/exposure/docs/episuite.htm

Estimation Program Interface (EPI) Suite* KOWWINTM log Kow AOPWINTM gas-phase reaction rate AOPWINTM atmospheric half-lives HENRYWINTM Henry’s Law constant (air/water partition coefficient) MPBPWINTM melting point, boiling point, and vapor pressure BIOWINTM aerobic biodegradability PCKOCWINTM soil adsorption coefficient (Koc), WSKOWWINTM water solubility HYDROWINTM hydrolytic half-life BCFWINTM Bio Concentration Factor WVOLWINTM rate of volatilization STPWINTM removal in a Sewage Treatment Plant; LEV3EPITM: partitioning of chemicals between air, soil, sediment, and water * http://www.epa.gov/opptintr/exposure/docs/episuite.htm

SMILES NOTATION ADN O=[N+]([O-])N[N+]([O-])=O ADNA O=[N+]([O-])N\N=N\[N+]([O-])=O RDX O=[N+]([O-])N1CN([N+]([O-])=O)CN([N+]([O-])=O)C1 DNNC O=[N+]([O-])C1([N+]([O-])=O)CN([N+]([O-])=O)CN([N+]([O-])=O)C1 HMX O=[N+]([O-])N1CN([N+]([O-])=O)CN([N+]([O-])=O)CN([N+]([O-])=O)C1 HCO O=[N+]([O-])C1([N+]([O-])=O)CN([N+]([O-])=O)CC([N+]([O-])=O)([N+]([O-])=O)CN([N+]([O ])=O)C1 FOX-7 N/C(N)=C([N+]([O-])=O)\[N+]([O-])=O ADNDNE O=[N+]([O-])/C([N+]([O-])=O)=C(N[N+]([O-])=O)\N[N+]([O-])=O AP O=Cl(=O)(=O)ON(H)(H)(H)H

Results Step 3. Evaluate Model Certainty Run model with surrogate compounds using measured melting points and log Kow (if available) Obtained EPI Suite model output using the following inputs SMILES structural notation only SMILES notation and melting point SMILES notation, melting point, and log Kow

EPI-Suites Outputs AP Calculated mp 266 °C--reported mp 240 °C Highly water soluble High propensity to move through soil Not likely to accumulate in lipids and organic tissues nor magnify in the food chain Not likely to pose a hazard to aquatic biota Likely to photo degrade Not likely to volatize to atmosphere

EPI-Suites Outputs ADNA Calculated mp 266 °C--reported mp 266 °C Highly water soluble High propensity to move through soil Not likely to accumulate in lipids and organic tissues nor magnify in the food chain Not likely to pose a hazard to aquatic biota Likely to photo degrade Not likely to volatize to atmosphere

EPI-Suites Outputs DNNC Calculated mp 148 °C--reported mp 151 °C Highly water soluble, but least water soluble of the four candidates Low propensity to move through soil Not likely to accumulate in lipids and organic tissues nor magnify in the food chain Not likely to pose a hazard to aquatic biota Likely to photo degrade Not likely to volatize to atmosphere

EPI-Suites Outputs HCO Calculated mp 221 °C--reported mp 250 °C Highly water soluble Low propensity to move through soil Not likely to accumulate in lipids and organic tissues nor magnify in the food chain Not likely to pose a hazard to aquatic biota Likely to photo degrade Not likely to volatize to atmosphere

EPI-Suites Outputs ADNDNE Calculated mp 127 °C--reported mp unknown Highly water soluble Moderate propensity to move through soil Not likely to accumulate in lipids and organic tissues nor magnify in the food chain Not likely to pose a hazard to aquatic biota Likely to photo degrade Not likely to volatize to atmosphere

Predicted Environmental Results

Data Comparison ( ) values reported in literature Melting Point ( o C) Water Solubility (ppm) Log K ow K oc T 1/2 Water (hr) Soil Daphnid ADNA 273 1.2 X 10 5 -0.14 3.4 360 9.5 X10 3 ADN 245 (92) 1.0 X 10 6 (5 X 10 ) -1.29 10.53 8.4 X 10 4 DNNC 148 (151) 7.3 X 10 -1.14 1678 900 1.5 x 10 RDX 133 (204) 6.1 X 10 0.68 (0.94) 195 (1.86) 2.8 X 10 HCO 221 (250) 3.8 X 10 -2.8 1.4 X 10 1440 7.1 X 10 HMX 182 (276) 2.6 X 10 0.82 (0.06) 1850 (0.54) 900 (11-425) ADNDNE 127 2.3 X 10 -1.54 928 3.2 X 10 FOX-7 83 (205) -2.86 30.6 2.1 X 10 AP 266 -5.841 96.6 1.27 X 10 9 (59.9) (5) (370 yr) (7.5-2.2 X 108) (240) (6 X 107) (2.7 X 107) ( ) values reported in literature

Conclusions and Recommendations Some discrepancies were observed in melting points predicted from SMILES input compared to reported values. Modeled fate/transport/toxicity outputs were not sensitive to the discrepancy in mp. Empirical and modeled values for water solubility and vapor pressure were generally in agreement. Modeled outputs for half-life in air/water/soil appear useless. Caution: EPI Suites might be overestimating Koc so the compounds may be more mobile in soil than suggested.

Conclusions and Recommendations Low lipophilic nature suggest compounds will not bio accumulate Aquatic toxicity is expected to be low.

Other Related Efforts Mark Johnson (CHPPM) and William Ruppert (Hughes Associates), “Integration of ESOH Impacts as Performance Objectives in RDTE and Acquisition,” U.S. Army EQT Program 2005. Betsy Rice and Margaret Hurley (ARL), “Quantum Mechanical Predictors for Health Effects,” U.S. Army STO Program 2005

Next Steps Run EPI Suites with measured water solubilities. Evaluate QSAR model ADME for health and toxicological endpoints using this same approach. Test out TOPKAT health predictor (CHPPM) Compare QSAR results with those obtained by first principles (ARL).

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