Synthesis of calcium monosilicide nanowires by reactive deposition technique

The CaSi nanowires were synthesized on Si substrate by reactive deposition technique. A great amount of Ca vapor reacted with surface of cleaned Si substrate, and CaSi nanowires was grown on the as-synthesized CaSi film. The diameter of nanowires could achieve with a minimum value about 25 nm. The CaSi nanowire was self-orient along the <001> direction. We can control the length of nanowires by experimental parameter settings, such as quantity of Ca source, duration time and temperature. The formation mechanism of Ca-silicides on Si substrate was discussed in detail. Raman spectroscopy shows that the nanosized character for CaSi phase was confirmed. Meanwhile, the Ca-silicides layer showed a strong absorption in the ultraviolet (UV) region of the solar spectrum, indicating their potential applications.

Model design and parameter optimization of CNN for side-channel cryptanalysis

Background The side-channel cryptanalysis method based on convolutional neural network (CNNSCA) can effectively carry out cryptographic attacks. The CNNSCA network models that achieve cryptanalysis mainly include CNNSCA based on the VGG variant (VGG-CNNSCA) and CNNSCA based on the Alexnet variant (Alex-CNNSCA). The learning ability and cryptanalysis performance of these CNNSCA models are not optimal, and the trained model has low accuracy, too long training time, and takes up more computing resources. In order to improve the overall performance of CNNSCA, the paper will improve CNNSCA model design and hyperparameter optimization. Methods The paper first studied the CNN architecture composition in the SCA application scenario, and derives the calculation process of the CNN core algorithm for side-channel leakage of one-dimensional data. Secondly, a new basic model of CNNSCA was designed by comprehensively using the advantages of VGG-CNNSCA model classification and fitting efficiency and Alex-CNNSCA model occupying less computing resources, in order to better reduce the gradient dispersion problem of error back propagation in deep networks, the SE (Squeeze-and-Excitation) module is newly embedded in this basic model, this module is used for the first time in the CNNSCA model, which forms a new idea for the design of the CNNSCA model. Then apply this basic model to a known first-order masked dataset from the side-channel leak public database (ASCAD). In this application scenario, according to the model design rules and actual experimental results, exclude non-essential experimental parameters. Optimize the various hyperparameters of the basic model in the most objective experimental parameter interval to improve its cryptanalysis performance, which results in a hyper-parameter optimization scheme and a final benchmark for the determination of hyper-parameters. Results Finally, a new CNNSCA model optimized architecture for attacking unprotected encryption devices is obtained—CNNSCAnew. Through comparative experiments, CNNSCAnew’s guessing entropy evaluation results converged to 61. From model training to successful recovery of the key, the total time spent was shortened to about 30 min, and we obtained better performance than other CNNSCA models.

Systems Astrochemistry: A New Doctrine for Experimental Studies

Laboratory experiments play a key role in deciphering the chemistry of the interstellar medium (ISM) and the formation of complex organic molecules (COMs) relevant to life. To date, however, most studies in experimental astrochemistry have made use of a reductionist approach to experimental design in which chemical responses to variations in a single parameter are investigated while all other parameters are held constant. Although such work does afford insight into the chemistry of the ISM, it is likely that several important points (e.g., the possible influence of experimental parameter interaction) remain ambiguous. In light of this, we propose the adoption of a new “systems astrochemistry” approach for experimental studies and present the basic tenants and advantages of this approach in this perspective article. Such an approach has already been used for some time now and to great effect in the field of prebiotic chemistry, and so we anticipate that its application to experimental astrochemistry will uncover new data hitherto unknown which could aid in better linking laboratory work to observations and models.

New Methods for Studying Materials Under Shear with Nuclear Magnetic Resonance

<p>For over 30 years, nuclear magnetic resonance (NMR) techniques have been used to study materials under shear. Collectively referred to as Rheo-NMR, these methods measure material behaviour due to external stimuli and provide spatially and temporally resolved maps of NMR spectra, intrinsic NMR parameters (e.g. relaxation times) or motion (e.g. diffusion or flow). As a consequence, Rheo-NMR has been established as a complementary technique to conventional rheological measurements. In this thesis, new hardware and experimental methods are presented with the goal of advancing this exciting field through further integration of traditional rheometry techniques with NMR experiments. Three key areas of hardware development have been addressed, including: 1) integrating torque sensing into the Rheo-NMR experiment for simultaneous bulk shear stress measurements, 2) constructing shear devices with geometric parameters closer to those used on commercial rheometers and 3) implementing an advanced drive system which allows for new shear profiles including oscillatory shear. In addition to presenting the design and construction of various prototype instruments, results from validation and proof of concept studies are discussed. This information demonstrates that the hardware operates as expected and establishes an experimental parameter space for these new techniques. Furthermore, these methods have been applied to open questions in various physical systems. This includes exploring the influence of shear geometry curvature on the onset of shear banding in a wormlike micelle surfactant system, observing shear induced structural changes in a lyotropic nonionic surfactant simultaneously via deuterium spectroscopy and bulk viscosity as well as studying interactions of flowing granular materials. The interpretation and implication of these observations are discussed in addition to motivating further studies.</p>

New Methods for Studying Materials Under Shear with Nuclear Magnetic Resonance

<p>For over 30 years, nuclear magnetic resonance (NMR) techniques have been used to study materials under shear. Collectively referred to as Rheo-NMR, these methods measure material behaviour due to external stimuli and provide spatially and temporally resolved maps of NMR spectra, intrinsic NMR parameters (e.g. relaxation times) or motion (e.g. diffusion or flow). As a consequence, Rheo-NMR has been established as a complementary technique to conventional rheological measurements. In this thesis, new hardware and experimental methods are presented with the goal of advancing this exciting field through further integration of traditional rheometry techniques with NMR experiments. Three key areas of hardware development have been addressed, including: 1) integrating torque sensing into the Rheo-NMR experiment for simultaneous bulk shear stress measurements, 2) constructing shear devices with geometric parameters closer to those used on commercial rheometers and 3) implementing an advanced drive system which allows for new shear profiles including oscillatory shear. In addition to presenting the design and construction of various prototype instruments, results from validation and proof of concept studies are discussed. This information demonstrates that the hardware operates as expected and establishes an experimental parameter space for these new techniques. Furthermore, these methods have been applied to open questions in various physical systems. This includes exploring the influence of shear geometry curvature on the onset of shear banding in a wormlike micelle surfactant system, observing shear induced structural changes in a lyotropic nonionic surfactant simultaneously via deuterium spectroscopy and bulk viscosity as well as studying interactions of flowing granular materials. The interpretation and implication of these observations are discussed in addition to motivating further studies.</p>

Atom Probe Analysis of a Zr-based Bulk Metallic Glass

Zr-based bulk metallic glasses (BMGs) are amorphous alloys that can exhibit excellent mechanical properties, including high yield strength and fracture toughness. These properties are linked to local microstructural heterogeneities. Whether via microscopy-based techniques, synchrotron techniques, or calorimetric approaches, the amorphous structure of BMGs makes the characterisation of the details of these local structural and chemical heterogeneities extremely challenging. Our focus here is on atom probe tomography (APT), where considerable uncertainty remains in terms of how and when to apply this otherwise powerful technique to amorphous materials. This work reports a systematic evaluation of the experimental parameter space. We report results of BMG composition acquired against various APT operating parameters for Zr63.96Cu13.36Ni10.29Al11.04Nb1.25 (at. %). We demonstrate that a customised peak-based ranging approach yields satisfactory compositional accuracy with absolute errors of <1 at. %. Beyond composition, we have discussed the data quality in terms of attributes of the mass spectra: mass resolution, signal-to-thermal tail ratio, and overlapped peak ratio. We also assess the composition of the well-known clustered evaporation effects, common in APT data of BMGs. We conclude that these regions have negligible differences in composition from the surrounding “matrix” or bulk in these alloys.