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International audience; Understanding the distributions and behaviors of dopants in Si nanocrystal are the primary and necessary issues to realize the controllable doping at nanoscale and develop the next generation of optoelectronic devices. This work reports the atomic-scale distributions of phosphorus and boron dopants in Si nanocrystals mul- tilayers. The phosphorus-doped and boron-doped Si nanocrystals/SiO2 multilayers are fabricated by PECVD and subsequently annealed at 1000 ◦C. It is found that the locations of phosphorus are redistributed after the formation of Si nanocrystals due to the combined effects of formation energy and self-purification. Phosphorus dopants are mainly distributed at the Si nanocrystals surfaces to passivate the dangling bonds, while part of them incorporate into Si nanocrystals lattice sites to provide free electrons. However, boron dopants exhibit different distributions in contrast to phosphorus. The concentration of boron on Si nanocrystals surfaces can reach as high as 40.0 at. %, which forms a dopant-shell covering on Si nanocrystals. Meanwhile, the boron dopant-shell can modify the surface states of Si nano- crystals like Si-oxide related emission centers and dangling bonds, which is responsible for the luminescence properties. Moreover, the boron-aggregations with concentration near 74.8 at. % are appeared inside Si nanocrystals and led to the damage of crystalline lattice.

Doping in Si nanocrystals is an interesting topic and to directly study the dopants distribution in phosphorous/boron co-doping circumstance is one of the important issue nowadays. In this study, atom probe tomography is performed to study the structures and impurity distribution in phosphorous/boron co-doped Si nanocrystals/SiO2 multilayers. Comparing with phosphorous singly-doped Si nanocrystals, it is interesting to find the phosphorous concentration in co-doped samples can be significantly improved. Theoretical simulation suggests that phosphorous-boron pairs are formed in co-doped Si nanocrystals with the lowest formation energy, which also reduce the formation energy of phosphorous in Si nanocrystals. The results indicate co-doping can promote more phosphorous impurities enter into the near-surface and inner sites of Si nanocrystals, which provides an interesting way to regulate the electronic and optical properties of Si nanocrystals like the observed enhancement of conductivity and sub-band light emission.

3-Amino-4-amidoximinofurazan (AAOF) is an important precursor for the synthesis of high energy furazan energetic materials.

2,4,6-Trinitroresorcinol (TNR), one main by-product in the dinitrobenzene (DNB) production process, is self-reactive substance and has led to tragic explosion incidents in China. In this article, the formation mechanism of TNR during the DNB production process was studied employing HPLC and HPLC-MS technique. Thermal decomposition behavior of TNR was also systematically studied by differential scanning calorimeter (DSC). The decomposition kinetics of TNR were investigated employing both iso-conversional (Friedman and Ozawa method) and model-fitting method. The formation mechanism of TNR during the dinitrobenzene (DNB) production is confirmed: The two by-products of dinitrophenol (DNP) and trinitrophenol (TNP) produced in the benzene mononitration stage are further nitrated to form tetranitrophenol (TTNP) in the mononitrobenzene (MNB) nitration stage. Then most of TTNP will be hydrolyzed to form the TNR during the water washing process. The decomposition process of TNR has been proven to follow three consecutive steps (A→B1→B2→B). The former two steps present autocatalytic behavior while the last step obeys N-order reaction model. The accuracy of the developed decomposition model and the obtained model parameters have been demonstrated by the comparison of the simulated and experimental DSC data and the activation energy obtained by both the iso-conversional method and model-fitting method. The same trend of experimental and simulated results about isothermal reaction further verify the building model.

As a self-reactive substance, benzaldehyde oxime (BO) is prone to a highly exothermic runaway reaction and thermal hazard analysis and the reaction kinetics calculation of BO have great significance. In this work, the decomposition products of BO in nitrogen atmosphere were identified by GC–MS and HPLC techniques. The impact of the decomposition products on the decomposition behaviors of BO were analyzed by comparison of the ARC test results of pure BO and mixture of BO and decomposition products. It was found that N-benzylidene benzylamine was the intermediate decomposition product and benzoic acid, benzamide, N-benzyl benzamide, and 2,4,5-triphenylimidazole were the final products of BO. A two-step continuous autocatalytic reaction model was established to depict the decomposition process of BO. The kinetic parameters of the model were calculated by applying the nonlinear optimization method. Finally, thermal behaviors under different process temperature were predicted based on the kinetic model, and the time to maximum rate (TMRad) was predicted as 112.04 °C under 24 h, and 122.19 °C of 8 h, which offer crucial safety information to optimize the safety conditions of BO during usage, storage and transportation, which minimizes the industrial disasters.

Time to maximum rate under adiabatic condition (TMRad) and the corresponding initial temperatures such as TD24 (the initial temperature when TMRad equals 24 h) are essential parameters to evaluate thermal hazard of chemical process. The standard methods of calculating TMRad are based on the Nth-order model. To clarify the influence of the reaction type on TMRad, the heating-waiting-seeking (HWS) processes and the direct adiabatic process were simulated by numerical calculation according to a given kinetic parameters and adiabatic temperature rise (ΔTad). The relationship between TMRad and temperature (T) and its corresponding TD24 were obtained by using two standard methods for single step, two-steps parallel and continuous reactions. The calculation results show that: for single-step reaction, if it only involves Nth-order reaction, the deviation of TD24 is within 18 °C; if it involves autocatalytic reaction, the deviation of TD24 reaches to 300 °C under the calculation condition; the evaluation is not reliable and more risky at low temperature. The two-step reaction produced similar results. It can be judged that the standard methods are only applicable to the estimation of TMRad of Nth-order reactions. For the reactions involving autocatalysis, the method of co-fitting of multiple kinds of experimental data can be used with the help of analysis software.

Adiabatic calorimetry is one of the main experimental methods to quantitatively study the thermal hazard in chemical process. There are two problems in adiabatic calorimetry: (1) identification of the reaction model is difficult; (2) the equilibrium of system and the temperature uniformity of sample will be broken under the rapid temperature rise rate, especially at lower thermal inertia. In this work, the heat-quench-heat method in adiabatic calorimetry was proposed to determine the reaction model and slow the reaction rate to evaluate kinetic parameters accurately. A criterion was proposed to identify the reaction model which states that the decomposition is an n-order reaction if T0,stage1

Thermal runaway of chemical reactions often lead to secondary decomposition of the material, especially with autocatalytic decomposition characteristics. Autocatalytic decompositions are often characterized by drastic decomposition, intense heat release, high thermal risk and difficultly in control. Quantitative classification of different autocatalytic strengths is significant for the formulation of risk control measures and recognition of the most dangerous scenarios in relief system. In this work, the factor, which is the ratio of the heat released by the initial stage to that of the total reaction, has been defined to effectively and quantitatively assess the strength of autocatalytic decomposition based on the Perez-Benito model that includes two-stage competitive reactions. According to “3σ principle” of the normal distribution, the factor was classified into five grades: 0–5%, 5–18%, 18–82% 82–95%, 95–100% corresponding to the autocatalytic strength: strong, less strong, moderate, less weak and weak, respectively. This method is validated using cumyl hydro-peroxide and dicumyl peroxide, the autocatalytic strength of which are well known to be less strong (7.92%) and weak (100%), respectively. The results are consistent with the profile width, heat-quench-reheat test and the isothermal tests. This method was used to classify the autocatalytic strength of dimethyl sulfoxide, 29.5 mass% nitro-guanidine aqueous solution, and Benz aldoxime. The results show that the autocatalytic strengths of these three materials are strong (0.01%), moderate (31.52%) and less weak (82.67%), respectively. Through the classification assessment, it helps to get a more intuitive understanding of the degree of substance danger from the perspective of kinetics and thermodynamics.

As a major high-energy plasticizer in the production of propellant, the destructive nature and thermal hazards of DINA are enormous. To evaluate the potential thermal hazards for its decomposition, the non-isothermal DSC and ARC experiments were performed to determine the decomposition kinetic model and parameters. It can be seen from the DSC results that DINA underwent a melting process before thermal decomposition, the endothermic peak and exothermic peak are identified at about 49−52℃ and 153−162℃, respectively. Combined with the results of DSC and ARC tests, the reliable kinetic model of DINA consists of four consecutive autocatalytic reaction has been created and verified. Subsequently, kinetic-based numerical simulations were executed to evaluate the thermal explosion hazards of DINA under the different scenarios. Process safety parameters under adiabatic conditions including time to maximum rate as well as induction period were consequently retrieved. Furthermore, inherent safety recommendations were proposed to forestall the process accidents in storage and the applications of DINA.

The decomposition of many hazardous materials goes through autocatalytic mechanisms. Due to the unpredictably sudden heat evolution companied with the decomposition of these materials, it is of great importance to identify autocatalytic decompositions and treat them with caution. In this work, a kinetic-parameters-free criterion is proposed to determine the autocatalytic decomposition using adiabatic calorimeters. This criterion states that the decompositions are autocatalytic if the values of R T p 2 T f − T p obtained by adiabatic experiments in different conditions are variable; otherwise they follow n-order behavior. Mathematical simulations at different values of φ, α0 and Ton have been conducted for n-order and autocatalytic decompositions to validate the criterion. To further validate the criterion, this method is applied to four representative substances: DCP, 20 % DTBP in toluene, BO and CHP. Overall, the validity of this criterion has been verified by simulation and experiment results.

In adiabatic thermal analysis, correct measurement of temperature is usually ensured by means of a calibration procedure and thermal inertia corrections. However, there is a significant gradient within system, which not only makes the obtained test results inaccurate, but also causes serious errors in subsequent kinetic calculations and thermal risk assessment. Thus, estimations of the temperature gradients, which appear into the sample, are of highest interest to choose the right operational conditions that minimize that gradient. In this work, the CFD software has been applied to study this temperature gradient issue in adiabatic system. In view of the causes of temperature gradients, the influencing factors and the resulting analysis errors are all deeply researched. In addition, three different kinds of adiabaticity control model cases have also been simulated to explore the right operational conditions that minimize gradient and provide more reliable kinetics and thermal hazard parameters (Q∞, k0, Ea, n, TD24, TCL). After a comparative study, the authors define the more reliable operational conditions, which include selecting a suitable temperature response value and the adiabatic temperature control model. Finally, the reliability of the adiabaticity control model that achieves the minimum temperature gradients and provides the most accurate calculation results was verified through the different adiabatic tests.

Maximum temperature of synthesis reaction (MTSR) is an essential concept to assess the thermal runaway risk and design safe operating conditions for semibatch reactors (SBRs). According to the definition, the values of MTSR will change with the reaction temperature (T). So far, the behavior of MTSR for liquid–liquid semibatch reactions with arbitrary reaction order has not been thoroughly researched. In this work, it is theoretically and experimentally verified that MTSR versus T profiles are prone to present an ‘S’ shape for strongly exothermic kinetically controlled liquid–liquid reactions. That means that the dependence of MTSR on T is complex. A theoretical criterion to determine whether MTSR will increase with T increasing is developed in this work. This criterion states that if the criterion is negative, MTSR will increase as T increases. To validate this criterion, the nitration of 4-chloro benzotrifluorid by mixed acid was conducted. The theoretical criterion can contribute to design safe operating conditions for SBRs.

To reduce the fire and explosion accident of dicumyl peroxide (DCP) in experiment and production, the thermal hazards of DCP and 40% mass content DCP in ethyl benzene (40% DCP) have been studied by the differential scanning calorimeter (DSC) and the accelerating rate calorimeter (ARC) in this paper. DSC experiment showed that ethyl benzene has no effect on the characteristic parameters of thermal decomposition of DCP, such as the temperature of the exothermic peak (Tpeak) and the decomposition energy (Ea), and the thermal decomposition reaction of 40% DCP followed the one-step reaction principle. ARC experiment showed that with the increase of inertia factor (Φ), the measured initial decomposition temperature (Ton) would be higher and the caculated Ea and pre-exponential factor (A) would be greater. It was also proved that after modification of Φ, TD24 was relatively consistent near Ton, but different at higher temperatures. Fisher's correction method was used to verify the necessity of consistency between experimental conditions and prediction conditions.

International audience; Because of their innocuity, Au nanowires present an interesting field of applications in biology and, particularly, in cancer therapy. Since their morphology and distribution can greatly affect their performances, being able to control their mode of growth is important. Various elaboration techniques including “top-down” and “bottom-up” approaches have been developed. In this work, we propose an efficient maskless method to grow Au nanowires with the help of hydrogen plasma treatment of Au thin films. We have been able to grow Au nanowires by taking advantage of spinodal dewetting of an Au thin film and the supply of silicon radicals resulting from hydrogen plasma etching of amorphous silicon coating the walls of the reactor. A variety of techniques have been applied to study the microstructure and the optical properties of Au nanowires. A strong photothermal effect of Au nanowires has been demonstrated with the help of visible laser light. In order to study the nanowire growth, the transport of Au atoms is discussed, and a growth mechanism is proposed.

In the fine chemical industry, exothermic liquid–liquid reactions are commonly carried out in semibatch reactors (SBRs). It has been an essential issue to design thermally safe and productive operations for isoperibolic liquid–liquid SBRs. Because it is time-consuming and money-consuming to determinate accurate kinetic parameters, a kinetic-parameter-free approach for this issue is highly desired. In this work, we find that once MTSR in the isothermal liquid–liquid SBRs increase with the increase in the reaction temperature, the corresponding isoperibolic liquid–liquid SBRs with the jacket temperature being not lower than the isothermal reaction temperature must be in the QFS scenario. On the basis of this finding, a kinetic-parameter-free approach has been developed to design thermally safe and productive operating conditions for isoperibolic liquid–liquid SBRs.

We report on the growth of Sn-catalyzed GeSn nanowires (NWs) having a GeSn core and a c-Ge shell in the presence of germane plasma at substrate temperatures (TS) below the GeSn eutectic temperature (TE), containing an exceptional Sn concentration of 30 at. % in their core. The differences between the NWs produced at TS above and below TE of the GeSn alloy are highlighted. Two types of NW growth process are identified: the previously reported in-plane solid–liquid–solid (IPSLS) process for TS ≥ TE and a plasma-assisted IPSLS (PA-IPSLS) method taking place at TS < TE; the crucial role of plasma in providing the energy necessary to melt the Sn catalyst at substrate temperatures lower than TE is discussed. The thermal activation window for each method is determined. The PA-IPSLS process is shown to provide an efficient strategy for the growth of crystalline GeSn NWs with a high Sn incorporation in a growth duration of less than 3 min.

In and Sn are the type of catalysts which do not introduce deep level electrical defects within the bandgap of germanium (Ge). However, Ge nanowires produced using these catalysts usually have a large diameter, a tapered morphology, and mixed crystalline and amorphous phases. In this study, we show that plasma-assisted vapor–liquid–solid (PA-VLS) method can be used to synthesize Ge nanowires. Moreover, at certain parameter domains, the sidewall deposition issues of this synthesis method can be avoided and long, thin tapering-free monocrystalline Ge nanowires can be obtained with In and Sn catalysts. We find two quite different parameter domains where Ge nanowire growth can occur via PA-VLS using In and Sn catalysts: (i) a low temperature-low pressure domain, below ∼235 °C at a GeH4 partial pressure of ∼6 mTorr, where supersaturation in the catalyst occurs thanks to the low solubility of Ge in the catalysts, and (ii) a high temperature-high pressure domain, at ∼400 °C and a GeH4 partial pressure above ∼20 mTorr, where supersaturation occurs thanks to the high GeH4 concentration. While growth at 235 °C results in tapered short wires, operating at 400 °C enables cylindrical nanowire growth. With the increase of growth temperature, the crystalline structure of the nanowires changes from multi-crystalline to mono-crystalline and their growth rate increases from ∼0.3 nm s−1 to 5 nm s−1. The cylindrical Ge nanowires grown at 400°C usually have a length of few microns and a radius of around 10 nm, which is well below the Bohr exciton radius in bulk Ge (24.3 nm). To explain the growth mechanism, a detailed growth model based on the key chemical reactions is provided.

International audience; We report on a process to form micron-scale inverse cones in crystalline silicon without any masking steps using a selective, low temperature (

In this work, we report the same trends for the contact potential difference measured by Kelvin probe force microscopy and the effective carrier lifetime on crystalline silicon (c-Si) wafers passivated by AlOx layers of different thicknesses and submitted to annealing under various conditions. The changes in contact potential difference values and in the effective carrier lifetimes of the wafers are discussed in view of structural changes of the c-Si/SiO2/AlOx interface thanks to high resolution transmission electron microscopy. Indeed, we observed the presence of a crystalline silicon oxide interfacial layer in as-deposited (200 °C) AlOx, and a phase transformation from crystalline to amorphous silicon oxide when they were annealed in vacuum at 300 °C.

Alloying Ge with Sn is one of the promising ways for achieving Si compatible optoelectronics. Here, GeSn nanowires (NWs) are realized via nano-crystallization of a hydrogenated amorphous Ge (a-Ge:H) layer with the help of metal Sn droplets. The full process consists of three steps: (1) SnO2 nanoparticle (NP) reduction in a hydrogen plasma to produce Sn catalyst; (2) a-Ge:H deposition at 120 °C and (3) annealing. GeSn alloys with rich morphologies such as discrete nanocrystals (NCs), random, and straight NWs were successfully synthesized by changing process conditions. We show that annealing under Ar plasma favors the elaboration of straight GeSn NWs in contrast to the conventional random GeSn NWs obtained when annealing is performed under a H2 atmosphere. Interestingly, GeSn in the form of discrete NCs can be fabricated during the deposition of a-Ge:H at 180 °C. Even more, the synthesis of out-of-plane GeSn NWs has been demonstrated by reversing the deposition sequence of SnO2 NPs and a-Ge:H layer.

N-Nitrodiethanolamine dinitrate (DINA) is a nitramine explosive containing both O-nitro and N-nitro groups. In this work, the synthesis of DINA by nitration of diethanolamine hydrochloride (DEAHC) ...

In the fine chemicals industry, scaling up safely exothermic semibatch reactors (SBRs) is an essential issue. Since determination of reaction kinetics is time-consuming, it is highly desirable to d...

Optimization of the kinetic parameters with thermal analysis data is an essential issue. In this work, the conjugate direction particle swarm optimization (CDPSO) approach, as a global stochastic optimization algorithm that is suitable to high-dimension optimization problem, is first employed to estimate the kinetic parameters with DSC data. This algorithm combines the global optimization ability of the particle swarm optimization (PSO) and the ability to escape from the local extremum by the conjugate direction algorithm (CD) to find the globally optimal solutions. This algorithm does not require estimation of the initial values of the kinetic parameters. The validation of this method is verified by two cases: DCPO decomposition and CHP decomposition. By comparing the experimental and calculated heat flow results, the accuracy of the fitted kinetic parameters is verified. These two cases prove the effectiveness of CDPSO algorithm in the estimation of high-dimension kinetic parameters using DSC data.