Impact sensitivities of energetic materials derived from easy-to-compute ab initio rate constants.

New procedures to estimate the impact sensitivity of energetic materials are derived from an earlier semiempirical model correlating the drop weight impact height h50 to the rate constant k for the propagation of the decomposition process, assumed to be the limiting step. The new models are obtained by removing step by step the empiricism in the evaluation of k. We end up with a full ab initio expression for this constant in terms of theoretical activation energies and prefactors. The resulting model casts doubt on a previously introduced assumption regarding the temperature at the reaction front. Moreover, it questions possible interpretations of semiempirical estimates. A systematic comparison against alternative methods shows that although somewhat less accurate than its earlier semiempirical version, this ab initio model shows a predictive value similar to heavily parameterized approaches. The results imply that the decomposition kinetics accounts for at least 50% of the variation in the logarithms of drop height data.

Molecular Energies Derived from Deep Learning: Application to the Prediction of Formation Enthalpies Up to High Energy Compounds.

Total electronic energies and frequencies predicted using the deep learning models ANI-1x and ANI-1ccx are converted to gas-phase formation enthalpies Δf H0 using an atom equivalent (AE) scheme for a database of CHNO compounds. As expected from the accuracy of those models in predicting reference DFT frequencies and DLPNO-CCSD(T)/CBS energies, this procedure usually outperforms DFT-based AE schemes. However, for some compounds, including energetic molecules, significant deviations from experiment are observed, larger than obtained using DFT procedures. A close examination of the GDB-11 database from which the training data was drawn reveals that many structures of interest in the energetic materials community are excluded from this extensive compilation primarily focused on drug discovery and designed with stability constraints in mind. This points to the urgent need to set up a comparable database including energetic species of interest for the design of energetic materials such as propellants or explosives.

QSPR versus fragment-based methods to predict octanol-air partition coefficients: Revisiting a recent comparison of both approaches.

The octanol-air partition coefficient (KOA) is useful to assess the fate of organic chemicals in the environment. Very recently, an interesting comparison of current methods to predict this property (Chemosphere 148 (2016) 118-125) highlighted a newly introduced Quantitative Structure-Property Relationship (QSPR), as a group-contribution (GC) method and a quantum chemical solvation model were reported to yield significantly less accurate results. Based on the observation that the so-called GC method investigated in this earlier study was inconsistent with the temperature dependence of KOA, the previously recommended QSPR is presently compared to the geometrical fragment (GF) additivity scheme. In addition to providing some improvement in terms of accuracy, this fragment-based procedure exhibits many advantages in terms of simplicity, interpretability, applicability and availability.

Predicting dielectric constants of pure liquids: fragment-based Kirkwood-Fröhlich model applicable over a wide range of polarity.

In view of developing a procedure to predict the dielectric constant (εr) of pure liquids from molecular structure, a thorough analysis of prominent factors affecting this property is carried out. The results suggest that the orientational dipolar parameter gµ2 involved in the Kirkwood-Fröhlich theory may be estimated as a sum of additive contributions (gµ2)i associated with suitably defined polar fragments i. Associated with third-party models for the molar volume Vm and the refractive index nD, this provides a practical route to predicting εr for new compounds. Advantages over previous methods include: simplicity, as the present model relies on fragment-additivity and does not require 3D structures; sound physical bases; demonstrated applicability to polar liquids with εr values up to 200; predictive ability extensively demonstrated against large datasets (for a total of 1220 compounds) covering a broad structural diversity, resulting in values of the root mean square deviation/average percent error as low as 3.7/10% for data sets focused on simple organic compounds as considered in previous studies, although the inclusion of many alcohols in the data set leads to poorer statistics (5.0/32%) due to the lack of specific parameters for hydroxyl groups in distinct environments. The approach should be of special interest in the current search for new aprotic electrolytes aimed at improving the performances of electrochemical energy storage systems. Although its reliance on many fitting parameters restricts its domain of applicability, the present implementation is recommended over current procedures whenever possible. A Python script is provided to allow its straightforward application.

Improved model for the refractive index: application to potential components of ambient aerosol.

Understanding the impact of atmospheric aerosols on the global radiative balance requires knowing the refractive index (RI) of their components. Currently available methods to estimate this property from molecular structure are mostly empirical and exhibit significant errors (>10%). This work reports a more physically sound model leading to predictions within ±5% from experiment. The root mean square relative error is <1% for general organic compounds, and <2% for oxygen-rich compounds of special interest in aerosol chemistry. In this approach, the RI is obtained from the Lorentz-Lorenz equation. The molar volume and polarizability required as input are obtained from the addition of a so-called geometrical fragment (GF) associated with every non-hydrogen atom in the molecule. The value of this GF method to the study of ambient aerosol is demonstrated through extensive validation and application to compounds that may be present in aerosol droplets. In so doing, insight is provided into the origin of significant errors previously noted using earlier methods. Moreover, it is demonstrated that reference values of the refractive index reported in widely used compilations should be considered with caution. Finally, a Python script is provided as supplementary information for easy use of the present model to estimate molar volume and refractive index for any molecule.

Pencil and Paper Estimation of Hansen Solubility Parameters.

Simple procedures to estimate Hansen solubility parameter (HSP) components from structural formulas are investigated. The best results are obtained using a simple relationship with molar volume and refractivity for the dispersion component, and using additivity models based on tailored fragments specifically designed for the polar and hydrogen bonding components. Despite large errors for some classes of chemicals, including small inorganic molecules, ionic liquids, and high halogen compounds, these models yield average absolute deviations from reference on par with state-of-the-art models and lower than reported using molecular dynamics simulations or nonlinear quantitative structure-property relationship models based on a limited set of quantum chemical descriptors. In contrast to group contribution methods that are either more restricted in scope or heavily parameterized, they are thoroughly validated and very easy to apply. Furthermore, the errors observed are easy to rationalize and may usually be anticipated. This work sheds light on some limitations inherent to pure additivity approaches for HSP prediction and provides a first step toward better models. A Python script implementing the procedure and the fully detailed results are provided as the Supporting Information.

Atom Pair Contribution Method: Fast and General Procedure To Predict Molecular Formation Enthalpies.

An atom pair contribution (APC) model aimed at predicting the gas-phase formation enthalpy (ΔfH°) of molecules is reported. In contrast to bond contribution (BC) or group contribution (GC) methods, it relies on increments associated with pairs of bonded and geminal atoms along with 15 structural corrections. Another distinctive feature of the present APC method is the large amount of experimental and high-level theoretical data specially compiled in this work to fit and validate the model (2671 entries). Unlike GC methods, the present APC model has wide applicability with the number of adjustable parameters limited to 68. Although it requires only a structural formula as input and involves only back-of-the-envelope calculations, it is more reliable than state-of-the-art quantitative structure-property relationship methods, popular semiempirical Hamiltonians, and even low-level density functional theory approaches based on gradient-corrected functionals. It is therefore a valuable tool for fast screening applications or whenever chemical accuracy is not necessary.

Solubility of organic compounds in octanol: Improved predictions based on the geometrical fragment approach.

Two new models are introduced to predict the solubility of chemicals in octanol (Soct), taking advantage of the extensive character of log(Soct) through a decomposition of molecules into so-called geometrical fragments (GF). They are extensively validated and their compliance with regulatory requirements is demonstrated. The first model requires just a molecular formula as input. Despite an extreme simplicity, it performs as well as an advanced random forest model involving 86 descriptors, with a root mean square error (RMSE) of 0.64 log units for an external test set of 100 molecules. For the second one, which requires the melting point Tm as input, introducing GF descriptors reduces the RMSE from about 0.7 to <0.5 log units, a performance that could previously be obtained only through the use of Abraham descriptors. A script is provided for easy application of the models, taking into account the limits of their applicability domains.

Impact sensitivities of energetic materials: Exploring the limitations of a model based only on structural formulas.

Using a comprehensive set of drop weight impact test data (h50) newly compiled from literature for 308 materials, a recent approach to predict impact sensitivities of nitro compounds is generalized to most explosive substances of interest. Compared to previous ones, this procedure is more thoroughly validated and exhibits a good predictive value. Furthermore, it yields new insight into the physical mechanisms involved, explaining for instance the unexpected desensitization of some oxygen-deficient triazoles upon nitration.

Predicting impact sensitivities of nitro compounds on the basis of a semi-empirical rate constant.

A physically motivated model is put forward to estimate impact sensitivity of nitro compounds on the basis of the relationship h(50) ∝ k(pr)(-4) between drop weight impact test data h(50) and rate constant k(pr) for the propagation of the decomposition. An approximate expression involving two adjustable parameters is introduced to estimate k(pr) from molecular structure. As a result, using only a hand-held calculator, ln(h(50)) values are estimated with a good reliability (R(2) ≃ 0.8) compared to previous schemes. These results support the underlying assumption that sensitivity primarily depends on the ability of reacting species to propagate the decomposition before the released energy dissipates away.

Insight into the contribution of individual functional groups to the flash point of organic compounds.

Flash point temperatures of organic compounds are predicted on the basis of a power law involving 21 additive contributions associated with non-hydrogen atoms and ring structures. The model is parametrized against a previous data set of 287 simple organic molecules. An average absolute error of 8.6K and a maximal error of about 50K are obtained when applying this model to an external test set of 488 compounds within its applicability domain. The overall performances of the method are remarkable given its simplicity and the small number of parameters involved. In addition, the present work provides valuable insight into the influence of individual functional groups to flash point temperatures.

Toward a physically based quantitative modeling of impact sensitivities.

Among the subsequent steps leading from impact to explosive decomposition in nitro compounds, the ability of early exothermic reactions to trigger the decomposition of neighboring molecules before the released energy has dissipated away is assumed to be critical. The rate of this process is roughly estimated using as inputs the energy content and the dissociation energy of the weakest X-NO2 bonds. While the sensitivity index thus obtained was previously shown to exhibit striking correlations with gap test pressures, its correlation with drop weight impact test data is poorer. Nevertheless, considering four different subsets of molecules depending on the environment of the most labile nitro groups, straightforward regressions against this sensitivity index yield a practical method to estimate impact sensitivity, whose combination of fair performance and generality is provided by no alternative approach, except purely empirical models based on extensive parametrization.

Formation Enthalpies Derived from Pairwise Interactions: A Step toward More Transferable Reactive Potentials for Organic Compounds.

A new approach to the development and parametrization of reactive potentials for organic compounds is put forward. As a byproduct of preliminary efforts in this direction, the performance of a simple representation of the energy of equilibrium structures in term of pairwise atom-atom and bond-bond contributions is investigated. For now, each contribution is assumed constant, given the multiplicity of covalent bonds, rather than computed on-the-fly from geometries and bond orders. In spite of this rough approximation, the approach performs remarkably well by comparison with semiempirical quantum chemical methods. Nevertheless, further refinement proves necessary for some unstable species involved in chemical reactions. As it stands, the present model appears as a promising basis in view of less empirical and more versatile alternatives to group contribution methods for the fast prediction of heats of formation, although much work remains to be done to demonstrate its value as a starting point toward better reactive potentials.

Formation Enthalpies of Ions: Routine Prediction Using Atom Equivalents.

In view of identifying routine procedures to estimate formation enthalpies of ionic systems such as energetic salts or ionic liquids on the basis of density functional theory (DFT), various combinations of atom equivalent (AE) schemes, functionals, and basis sets are compared, using a specially designed training set to parametrize the models. After correction, none of the functionals considered proves significantly more reliable than B3LYP. A small but systematic improvement is noted as AE values are allowed to depend on the atomic environment. However, AE parameters fail to make up for basis set limitations, in constrast to previous observations for neutrals. Finally, a good trade-off between reliability and cost is obtained for ions using B3LYP/6-31++G** energies.

MATEO: a software package for the molecular design of energetic materials.

To satisfy the need of energetic materials chemists for reliable and efficient predictive tools in order to select the most promising candidates for synthesis, a custom software package is developed. Making extensive use of publicly available software, it integrates a wide range of models and can be used for a variety of tasks, from the calculation of molecular properties to the prediction of the performance of heterogeneous materials, such as propellant compositions based on ammonium perchlorate/aluminium mixtures. The package is very easy to use through a graphical desktop environment. According to the material provided as input, suitable models and parameters are automatically selected. Therefore, chemists can apply advanced predictive models without having to learn how to use complex computer codes. To make the package more versatile, a command-line interface is also provided. It facilitates the assessment of various procedures by model developers.

Virus-Associated Hemophagocytic Syndrome related to acute CMV and HBV sexual co-infection: a case report.

BACKGROUND: Secondary or reactive hemophagocytic syndrome is frequently related to viral infections and is named Virus-Associated Hemophagocytic Syndrome (VAHS). Cytomegalovirus (CMV) has been associated with hemophagocytic syndrome in healthy subjects, patients with inflammatory bowel diseases rheumatologic diseases, and transplant recipients. CMV and hepatitis B virus (HBV) can be sexually transmitted. However, co-infection with these viruses has never been reported and the clinical follow-up after acute HBV-CMV infection is not known. OBJECTIVES: To report on the first case of a VAHS related to acute CMV and HBV co-infection probably acquired after sexual contact. STUDY DESIGN: A 47-year-old woman, with no past medical history, complaining of severe asthenia, pneumonia, myalgia, and high fever, was hospitalized for the first time on July 5, 2008. During 20 days, her CMV viral load and HBV DNA were monitored. RESULTS: Ten days after her hospitalization, all signs and symptoms worsened. Twenty days after hospitalization, the patient had a natural recovery from acute HBV infection and a rapid clearance of CMV infection. Three weeks later, the patient was discharged without any complaints. CONCLUSION: This report points out the etiological role of CMV and HBV co-infection in VAHS due to probable sexual transmission.

Optimisation of the chemical generation of singlet oxygen (1O2, 1Deltag) from the hydrogen peroxide-lanthanum(III) catalytic system using an improved NIR spectrometer.

A near-IR chemiluminescence spectrometer designed to study chemical sources of singlet oxygen ((1)O(2), (1)Delta(g)), was built by coupling a reactor compartment to a nitrogen-cooled Ge diode through a bundle of optical fibres. This device was used to optimise the generation of (1)O(2) from the hydrogen peroxide-lanthanum(iii) catalytic system. The reaction kinetics were studied with a 2(3)3(3)//12 screening experimental design comprising twelve experiments. The influence of six factors was examined: the nature of the lanthanum salt (hydroxide, oxide or nitrate) and its concentration (0.05 or 0.1 mol L(-1)), the pH value (5, 7 or 9), the concentration of H(2)O(2) (0.5, 1 or 2 mol L(-1)), the temperature (20 or 30 degrees C) and the concentration of EDTA (0 or 5 mmol L(-1)). Two responses were measured: the rate of H(2)O(2) disproportionation and the intensity of the luminescence of (1)O(2) at 1270 nm. The essential factor is the nature of the lanthanum salt since La(NO(3))(3) induces the disproportionation of H(2)O(2) about 60 x faster than La(2)O(3) or La(OH)(3). Other influencing factors are the pH value, the concentration of H(2)O(2), the temperature and the concentration of the lanthanum salt whereas the concentration of EDTA has no effect on the reaction. The catalytic activity of La(NO(3))(3) was then investigated in further detail by studying the influence of two factors (pH and [H(2)O(2)]) thanks to a Doehlert design.

Diagnostic efficacy of gadoxetic acid (Primovist)-enhanced MRI and spiral CT for a therapeutic strategy: comparison with intraoperative and histopathologic findings in focal liver lesions.

A multicenter study has been employed to evaluate the diagnostic efficacy of magnetic resonance imaging (MRI) using the new liver-specific contrast agent gadoxetic acid (Gd-EOB-DTPA, Primovist), as opposed to contrast-enhanced biphasic spiral computed tomography (CT), in the diagnosis of focal liver lesions, compared with a standard of reference (SOR). One hundred and sixty-nine patients with hepatic lesions eligible for surgery underwent Gd-EOB-DTPA-enhanced MRI as well as CT within 6 weeks. Pathologic evaluation of the liver specimen combined with intraoperative ultrasound established the SOR. Data sets were evaluated on-site (14 investigators) and off-site (three independent blinded readers). Gd-EOB-DTPA was well tolerated. Three hundred and two lesions were detected in 131 patients valid for analysis by SOR. The frequency of correctly detected lesions was significantly higher on Gd-EOB-DTPA-enhanced MRI compared with CT in the clinical evaluation [10.44%; 95% confidence interval (CI): 4.88, 16.0]. In the blinded reading there was a trend towards Gd-EOB-DTPA-enhanced MRI, not reaching statistical significance (2.14%; 95% CI: -4.32, 8.6). However, the highest rate of correctly detected lesions with a diameter below 1 cm was achieved by Gd-EOB-DTPA-enhanced MRI. Differential diagnosis was superior for Gd-EOB-DTPA-enhanced MRI (82.1%) versus CT (71.0%). A change in surgical therapy was documented in 19 of 131 patients (14.5%) post Gd-EOB-DTPA-enhanced MRI. Gd-EOB-DTPA-enhanced MRI was superior in the diagnosis and therapeutic management of focal liver lesions compared with CT.

Split charge equilibration method with correct dissociation limits.

Analytic reactive potentials rely on electronegativity equalization to describe how the electron distribution is affected as chemical reactions occur. However, such models predict fractional charges for neutral species with different electronegativities. To overcome this well-known dissociation problem, an approach taking advantage of the concept of split charges [R. A. Nistor, J. G. Polihronov, M. H. Muser, and N. J. Mosey, J. Chem. Phys. 125, 094108 (2006)] is put forward. A first implementation is presented. Starting from a previous model [P. Bultinck, W. Langenaeker, P. Lahorte, F. D. Proft, P. Geerlings, M. Waroquier, and J. P. Tollenaere, J. Phys. Chem. A 106, 7887 (2002)], a new contribution to the total energy is introduced in order to make up for the lack of suitable constraints on the charge density. Its effect is to restrain charge transfer between remote atoms. As a consequence, systems in gas phase naturally decompose into neutral fragments. This result is achieved using two empirical parameters in addition to atomic electronegativities and hardnesses.

Optimal partitioning of molecular properties into additive contributions: the case of crystal volumes.

A systematic scheme to split the volume of molecular crystals into additive increments is discussed. In contrast to earlier procedures, it relies on the definition of atom types on the basis of their geometrical rather than chemical environment. In addition, the role of the relevant structural features of the compounds is explicitly taken into account. This approach provides insight into the relative influence of chemical bonds, hydrogen bonds and rings on the volume of organic crystals. Compared with group-contribution techniques, it yields very similar results with many fewer empirical parameters. Applied to estimate the densities of 42 880 crystals containing elements up to chlorine and measured at different temperatures, an average absolute deviation from experiment close to 2% is obtained.