Curvature and self-assembly of semi-conducting nanoplatelets

Semi-conducting nanoplatelets are two-dimensional nanoparticles whose thickness is in the nanometer range and controlled at the atomic level. They have come up as a new category of nanomaterial with promising optical properties due to the efficient confinement of the exciton in the thickness direction. In this perspective, we first describe the various conformations of these 2D nanoparticles which display a variety of bent and curved geometries and present experimental evidences linking their curvature to the ligand-induced surface stress. We then focus on the assembly of nanoplatelets into superlattices to harness the particularly efficient energy transfer between them, and discuss different approaches that allow for directional control and positioning in large scale assemblies. We emphasize on the fundamental aspects of the assembly at the colloidal scale in which ligand-induced forces and kinetic effects play a dominant role. Finally, we highlight the collective properties that can be studied when a fine control over the assembly of nanoplatelets is achieved.

TARA: Training and Representation Alteration for AI Fairness and Domain Generalization

We propose a novel method for enforcing AI fairness with respect to protected or sensitive factors. This method uses a dual strategy performing training and representation alteration (TARA) for the mitigation of prominent causes of AI bias. It includes the use of representation learning alteration via adversarial independence to suppress the bias-inducing dependence of the data representation from protected factors and training set alteration via intelligent augmentation to address bias-causing data imbalance by using generative models that allow the fine control of sensitive factors related to underrepresented populations via domain adaptation and latent space manipulation. When testing our methods on image analytics, experiments demonstrate that TARA significantly or fully debiases baseline models while outperforming competing debiasing methods that have the same amount of information—for example, with (% overall accuracy, % accuracy gap) = (78.8, 0.5) versus the baseline method's score of (71.8, 10.5) for Eye-PACS, and (73.7, 11.8) versus (69.1, 21.7) for CelebA. Furthermore, recognizing certain limitations in current metrics used for assessing debiasing performance, we propose novel conjunctive debiasing metrics. Our experiments also demonstrate the ability of these novel metrics in assessing the Pareto efficiency of the proposed methods.

Design of Testability Structures With Security For Machine Intelligence Based Cryptosystem

During testing utmost all appropriate and suitable strategy needs to be established for consistent fault coverage, improved controllability and observability. The scan chains used in BIST allows some fine control over data propagations that is used as a backdoor to break the security over cryptographic cores. To alleviate these scan-based side-channel attacks, implementing a more inclusive security strategy is required to confuse the attacker and to ensure the key management process which is always a difficult task to task in cryptographic research. In this work for testing AES core Design-for-Testability (DfT) is considered with some random response compaction, bit masking during the scan process. In the proposed scan architecture, scan-based attack does not allow finding out actual computations which are related to the cipher transformations and key sequence. And observing the data through the scan structure is secured. The experimental results validate the potential metrics of the proposed scan model in terms of robustness to the scan attack and penalty gap that exists due to the inclusion of scan designs in AES core. Also investigate the selection of appropriate location points to implement the bit level modification to avoid attack for retrieving a key.

A CMOS Integrator-Based Clock-Free Time-to-Digital Converter for Home-Monitoring LiDAR Sensors

This paper presents a nine-bit integrator-based time-to-digital converter (I-TDC) realized in a 180 nm CMOS technology for the applications of indoor home-monitoring light detection and ranging (LiDAR) sensors. The proposed I-TDC exploits a clock-free configuration so as to discard clock-related dynamic power consumption and some notorious issues such as skew, glitch, and synchronization. It consists of a one-dimensional (1D) flash TDC to generate coarse-control codes and an integrator with a peak detection and hold (PDH) circuit to produce fine-control codes. A thermometer-to-binary converter is added to the 1D flash TDC, yielding four-bit coarse codes so that the measured detection range can be represented by nine-bit digital codes in total. Test chips of the proposed I-TDC demonstrate the measured results of the 53 dB dynamic range, i.e., the maximum detection range of 33.6 m and the minimum range of 7.5 cm. The chip core occupies the area of 0.14 × 1.4 mm2, with the power dissipation of 1.6 mW from a single 1.2-V supply.

Color brightness modulation of responsive photonic liquid for multicolored electrochromic displays

Electrically responsive photonic crystals have drawn extensive interest in the growing demands in camouflages, displays, sensing, energy-saving building etc. due to their fine control, fast response and convenient implementation. Veiled...

Solvent-Induced Assembly of One-Patch Silica Nanoparticles into Robust Clusters, Wormlike Chains and Bilayers

We report the synthesis and solvent-induced assembly of one-patch silica nanoparticles in the size range of 100–150 nm. They consisted, as a first approximation, of silica half-spheres of which the truncated face was itself concave and carried in its center a polymeric patch made of grafted polystyrene chains. The multistage synthesis led to 98% pure batches and allowed a fine control of the patch-to-particle size ratio from 0.69 to 1.54. The self-assembly was performed in equivolume mixtures of tetrahydrofuran and ethanol, making the polymeric patches sticky and ready to coalesce together. The assembly kinetics was monitored by collecting samples over time and analyzing statistically their TEM images. Small clusters, such as dimers, trimers, and tetramers, were formed initially and then evolved in part into micelles. Accordingly to previous simulation studies, more or less branched wormlike chains and planar bilayers were observed in the long term, when the patch-to-particle size ratio was high enough. We focused also on the experimental conditions that could allow preparing small clusters in a good morphology yield.

Effect of Electrolytic Medium on the Electrochemical Reduction of Graphene Oxide on Si(111) as Probed by XPS

The wafer-scale integration of graphene is of great importance in view of its numerous applications proposed or underway. A good graphene–silicon interface requires the fine control of several parameters and may turn into a high-cost material, suitable for the most advanced applications. Procedures that can be of great use for a wide range of applications are already available, but others are to be found, in order to modulate the offer of different types of materials, at different levels of sophistication and use. We have been exploring different electrochemical approaches over the last 5 years, starting from graphene oxide and resulting in graphene deposited on silicon-oriented surfaces, with the aim of understanding the reactions leading to the re-establishment of the graphene network. Here, we report how a proper choice of both the chemical environment and electrochemical conditions can lead to a more controlled and tunable graphene–Si(111) interface. This can also lead to a deeper understanding of the electrochemical reactions involved in the evolution of graphene oxide to graphene under electrochemical reduction. Results from XPS, the most suitable tool to follow the presence and fate of functional groups at the graphene surface, are reported, together with electrochemical and Raman findings.

The Shape of Data: a Theory of the Representation of Information in the Cerebellar Cortex

This paper presents a model of rate coding in the cerebellar cortex. The pathway of input to output of the cerebellum forms an anatomically repeating, functionally modular network, whose basic wiring is preserved across vertebrate taxa. Each network is bisected centrally by a functionally defined cell group, a microzone, which forms part of the cerebellar circuit. Input to a network may be from tens of thousands of concurrently active mossy fibres. The model claims to quantify the conversion of input rates into the code received by a microzone. Recoding on entry converts input rates into an internal code which is homogenised in the functional equivalent of an imaginary plane, occupied by the centrally positioned microzone. Homogenised means the code exists in any random sample of parallel fibre signals over a minimum number. The nature of the code and the regimented architecture of the cerebellar cortex mean that the threshold can be represented by space so that the threshold can be met by the physical dimensions of the Purkinje cell dendritic arbour and planar interneuron networks. As a result, the whole population of a microzone receives the same code. This is part of a mechanism which orchestrates functionally indivisible behaviour of the cerebellar circuit and is necessary for coordinated control of the output cells of the circuit. In this model, fine control of Purkinje cells is by input rates to the system and not by learning so that it is in conflict with the for-years-dominant supervised learning model.

Dynamic tracking of a magnetic micro-roller using ultrasound phase analysis

Microrobots (MRs) have attracted significant interest for their potentialities in diagnosis and non-invasive intervention in hard-to-reach body areas. Fine control of biomedical MRs requires real-time feedback on their position and configuration. Ultrasound (US) imaging stands as a mature and advantageous technology for MRs tracking, but it suffers from disturbances due to low contrast resolution. To overcome these limitations and make US imaging suitable for monitoring and tracking MRs, we propose a US contrast enhancement mechanism for MR visualization in echogenic backgrounds (e.g., tissue). Our technique exploits the specific acoustic phase modulation produced by the MR characteristic motions. By applying this principle, we performed real-time visualization and position tracking of a magnetic MR rolling on a lumen boundary, both in static flow and opposing flow conditions, with an average error of 0.25 body-lengths. Overall, the reported results unveil countless possibilities to exploit the proposed approach as a robust feedback strategy for monitoring and tracking biomedical MRs in-vivo.

Intelligent Control for Pressurizer System in Nuclear Power Plants

Fine control of output power for nuclear power plants is the essential goal for safe operation. In this work, a Fuzzy analytical proportional-integral-derivative (FPID) controller with different configurations is designed to adjust and control the pressure of the PZR system. The stability analysis of the FPID controller with variable gains is established, and conditions for bounded-input bounded-output stability conditions (BIBO) are derived using the small gain theory. Two scenarios are applied for evaluating the dynamic response of applied controllers. In addition, performance indices are compared between the PZR model and data measured from the PCtran VVER-1200 simulator. Finally, a simulation platform is developed for MATLAB / Simulink to implement the three-region nonlinear non-equilibrium PZR model and the designed pressure controllers. The analysis and evaluation results showed good durability of the designed controllers and satisfactory performance of the control. These results further show that the nonlinear PZR model is accurate, feasible, and valuable for dynamic simulation and control unit design.