Existing Synthesis Approaches Research Articles

Perovskite Quantum Dots for Emerging Displays: Recent Progress and Perspectives.

The excellent luminescence properties of perovskite quantum dots (PQDs), including wide excitation wavelength range, adjustable emission wavelength, narrow full width at half maximum (FWHM), and high photoluminescence quantum yield (PLQY), highly match the application requirements in emerging displays. Starting from the fundamental structure and the related optical properties, this paper first introduces the existing synthesis approaches of PQDs that have been and will potentially be used for display devices, and then summarizes the stability improving approaches with high retention of PQDs’ optical performance. Based on the above, the recent research progress of PQDs in displays is further elaborated. For photoluminescent display applications, the PQDs can be embedded in the backlighting device or color filter for liquid crystal displays (LCD), or they may function as the color conversion layer for blue organic light-emitting diodes (OLED) and blue micro-scale light-emitting diodes (μLED). In terms of next-generation electroluminescent displays, notable progress in perovskite quantum-dot light emitting diodes (PeQLED) has been achieved within the past decade, especially the maximum external quantum efficiency (EQE). To conclude, the key directions for future PQD development are summarized for promising prospects and widespread applications in display fields.

A SEMIPARAMETRIC MULTIPLE IMPUTATION APPROACH TO FULLY SYNTHETIC DATA FOR COMPLEX SURVEYS.

Data synthesis is an effective statistical approach for reducing data disclosure risk. Generating fully synthetic data might minimize such risk, but its modeling and application can be difficult for data from large, complex surveys. This article extended the two-stage imputation to simultaneously impute item missing values and generate fully synthetic data. A new combining rule for making inferences using data generated in this manner was developed. Two semiparametric missing data imputation models were adapted to generate fully synthetic data for skewed continuous variable and sparse binary variable, respectively. The proposed approach was evaluated using simulated data and real longitudinal data from the Health and Retirement Study. The proposed approach was also compared with two existing synthesis approaches: (1) parametric regressions models as implemented in IVEware; and (2) nonparametric Classification and Regression Trees as implemented in synthpop package for R using real data. The results show that high data utility is maintained for a wide variety of descriptive and model-based statistics using the proposed strategy. The proposed strategy also performs better than existing methods for sophisticated analyses such as factor analysis.

An energy efficient synthesis flow for application specific SoC design

Multiple Supply Voltage (MSV) is a known design technique to deal with the power and thermal issues of Multi Processor System on Chips (MPSoCs). In this paper, an MSV driven synthesis flow is proposed in four phases for the design of application-specific MPSoCs. The first phase conducts the core-to-router allocation concerning the operating voltages of cores as well as the bandwidth/latency requirements of the data flowing between the cores. The second phase coordinates voltages of cores connected to the same router. The third phase refines the power delivery network using our proposed voltage-aware hierarchical floorplanning algorithm. Finally, router-to-router connection and path allocation are done by the use of existing methods in the last phase. For the first time, we perform the core to router allocation phase before the voltage islanding phase to find the highest number of design solutions satisfying the set of given constraints; this in turn, improves the flexibility and efficiency of our synthesis process. Exhaustive experimental evaluations have been done on real-world benchmarks. Results confirm achieving 90% more design solutions (to conduct a wiser design space exploration) and an average of 93% Energy Delay Product (EDP) improvement as compared to the existing synthesis approaches.

Type synthesis of plane-symmetric deployable grasping parallel mechanisms using constraint force parallelogram law

Type synthesis methods of parallel mechanisms or metamorphic mechanisms have drawn rising interest for mechanism designers. However, existing synthesis approaches cannot synthesize both parallel mechanisms and metamorphic mechanisms. This paper develops a synthesis method of metamorphic mechanisms, which enables it to construct a family of 2-degree-of-freedom (DOF) deployable grasping parallel mechanisms. Namely, the originality of this paper is that it explores a common synthesis method for both parallel mechanisms and metamorphic mechanisms. First, a new type of grasping sub-mechanisms is designed. Then, a kinematic sub-chain is constructed after assembly of a base, a platform, and the grasping sub-mechanism, whose constraint-screw system is obtained using reciprocal screw theory. This constraint-screw system is further applied to derive the desired constraints of auxiliary sub-mechanisms using the constraint force parallelogram law. Subsequently, auxiliary sub-mechanisms are type synthesized based on such desired constraints. Finally, a class of parallel mechanisms is constructed by assembling the auxiliary and the kinematic sub-chain. Thus, this paper and related work generate fresh insight into synthesizing both single-DOF metamorphic mechanisms and 2-DOF parallel mechanisms.

Independently Controlling Stochastic Field Realization Magnitude and Phase Statistics for the Construction of Novel Partially Coherent Sources

In this paper, we present a method to independently control the field and irradiance statistics of a partially coherent beam. Prior techniques focus on generating optical field realizations whose ensemble-averaged autocorrelation matches a specified second-order field moment known as the cross-spectral density (CSD) function. Since optical field realizations are assumed to obey Gaussian statistics, these methods do not consider the irradiance moments, as they, by the Gaussian moment theorem, are completely determined by the field’s first and second moments. Our work, by including control over the irradiance statistics (in addition to the CSD function), expands existing synthesis approaches and allows for the design, modeling, and simulation of new partially coherent beams, whose underlying field realizations are not Gaussian distributed. We start with our model for a random optical field realization and then derive expressions relating the ensemble moments of our fields to those of the desired partially coherent beam. We describe in detail how to generate random optical field realizations with the proper statistics. We lastly generate two example partially coherent beams using our method and compare the simulated field and irradiance moments theory to validate our technique.

An efficient module-less synthesis approach for Digital Microfluidic Biochip.

Digital Microfluidic Biochips (DMFBs) will require error-free synthesis techniques which can function at much higher speed while implementing on real-time systems and capable of tackling more complex assay operations. Until now various bio-assays are successfully implemented based on different mixing modules present on such lab-on-chips. In present work, the concept of such dedicated virtual modules has been eliminated and a novel module-less-synthesis (MLS) method is proposed for accomplishing high-performance bio-protocols. Various shift-patterns (movements) of the micro-droplets are identified to accomplish entire mixing in lesser time compared to earlier module-based synthesis methods. We have also computed the percentage of mixing accomplishment for each directional-shift of the mixer-droplet. However, path congestion problem and operational errors are inevitable in MLS approach. Hence, the path congestion and washing problem in MLS is addressed by tweaking the earlier MLS approach and a new modified-MLS (MMLS) method is proposed. Finally, washing optimization technique on MMLS method is also given. Different real-life bio assays like PCR, IVD are tested with the proposed technique as well as synthetic benchmarks (hard test benches) are also incorporated in the experiments. For both kind of benchmarks synthesis performance improved with bioassay completion time (T_{mathrm{max}}) significantly reduced compared to existing synthesis approaches on DMFB platform.

Growth of 12-inch uniform monolayer graphene film on molten glass and its application in PbI2-based photodetector

Direct growth of large area uniform graphene on functional insulating materials is essential for engineering versatile applications of graphene. However, the existing synthesis approaches can hardly avoid the generation of non-uniform multilayer graphene along the gas flow direction, affording huge challenges for further scaling up. Herein, by exploiting the molten state of soda-lime glass, we have accomplished the direct growth of large area uniform (up to 30 cm × 6 cm) graphene via a facile chemical vapor deposition route on low cost soda-lime glass. The use of molten glass eliminates the chemically active sites (surface corrugations, scratches, defects), and improves the mobility of carbon precursors, affording uniform nucleation and growth of monolayer graphene. Intriguingly, thus-obtained graphene acts as an ideal coating layer for the surface crystallographic modification of soda-lime glass, making it epitaxy substrates for synthesizing high-quality PbI2 nanoplates and continues films. Accordingly, a prototype photodetector was fabricated to present excellent photoelectrical properties of high responsivity (∼ 600 on/off current ratio) and fast response speed (18 µs). This work hereby paves ways for the batch production and the direct applications of graphene glass as platforms for constructing high performance electronic and optoelectronic devices.

Gram-scale synthesis of all-inorganic perovskite quantum dots with high Mn substitution ratio and enhanced dual-color emission

Mn-doped all-inorganic perovskite quantum dots (QDs) provide prominent applications in the fields of low-cost light source or display, because of their remarkable properties including dual-color emission and reduced lead content, as well as high photoluminescence quantum yields (PLQYs) and high stability. However, the existing synthesis approaches usually require hash conditions, such as high temperature and nitrogen protection, which is a major hurdler for the practical manufacturing. In addition, the significantly high Mn substitution ratio in CsPbX3 QDs is still challenging. The real dual-color emission with two strong emission peaks in the Mn-doped all-inorganic perovskite QDs has attracted great interest. Here we present a gram-scale approach to synthesize both CsPbxMn1−xCl3 and CsPb1−xMnxClyBr3−y QDs at 100 °C in the air with high Mn substitution ratio, up to 55.64% atomically. The as-prepared CsPb1−xMnxClyBr3−y QDs exhibit high PLQYs of 62.41% and dual-color emission with two strong emission peaks around at 400–450 nm and 600 nm, respectively. The enhanced peak at 400–450 nm is a result of the hybrid halides in CsPbBrxCl3−x host. Furthermore, the unique advantage of the optical emission and high PLQYs properties of the CsPbxMn1−xCl3 QDs has been demonstrated as invisible ink for encryption applications and polymer composites. Our gram-scale synthesis approach for Mn-doped all-inorganic perovskite QDs may boost the future research and practical applications of QDs-based white LED, spintronics, and molecular barcoding.

Iron oxide nanopowder synthesized by electroerosion dispersion (EED) – Properties and potential for microwave applications

Magnetic nanoparticles (MNP) have attracted considerable interest in many fields of research and applied science due to their impressive properties. In the past, especially biomedical problems have promoted the development of MNPs. For technical applications e.g. wastewater treatment and absorption of electromagnetic waves, the existing synthesis approaches are too expensive and/or the producible quantities are too low. In this work we present a method for simple preparation of size-controlled magnetic iron oxide nanoparticles by electroerosion dispersion (EED) of carbon steel in water. We describe the synthesis method, the laboratory installation and discuss the structural, chemical and electromagnetic properties of the synthetized EED powders as well as their applicability for microwave absorption compared to other available ferrite powders.

An iterative structure for synthesizing symmetric functions using quantum-dot cellular automata

In recent years, majority-logic received significant attention as a synthesis approach for large Boolean functions. This logic is easily implemented in Quantum-dot cellular automata (QCA) technology which is emerging as an alternative to CMOS technology. In fact, majority logic gate serves as the basic logic unit in the digital design of QCA circuits. This paper introduces a synthesis technique for implementing totally symmetric Boolean functions using majority logic. First, a simple regular module is designed to synthesize unate symmetric functions. The structure uses 3-input majority gates. General symmetric Boolean functions are then realized following a unate decomposition method. We study the synthesis of some well known benchmark symmetric functions using the proposed method. Comparison with existing synthesis approaches confirms the efficacy of our method.

One-step synthesis and deposition of few-layer graphene via facile, dry ball-free milling

ABSTRACTGraphene is a 2-D carbon material showing considerable prominence in a wide range of optoelectronics, energy storage, thermal and mechanical applications. However, due to its unique features which are typically associated with difficulty in handling (ultra-thin thickness and hydrophobic surface, to name a few), synthesis and subsequent deposition processes are thus critical to the material properties of the prepared graphene films. While existing synthesis approaches such as chemical vapor deposition and epitaxial growth can grow graphene with high degree of order, the costly high temperature and/or high vacuum process prohibit the widespread usage, and the subsequent graphene transfer from the growth substrates for deposition proves to be challenging. Herein, a low-cost one-step synthesis and deposition approach for preparing few-layer graphene (FLG) on flexible copper substrates based on dry ball-free milling of graphite powder is proposed. Different from previous reports, copper substrates are inserted into the milling crucible, thus accomplishing simultaneous synthesis and deposition of FLG and eliminating further deposition step. Furthermore, while all previously reported high energy milling processes involve using balls of various sizes, we adopt a ball-free milling process relying only on centrifugal forces, which significantly reduces the surface damage of the deposition substrates. Sample characterization indicates that the process yields FLG deposited uniformly across all tested specimens. Consequently, this work takes graphene synthesis and deposition a step closer to full automation with simple and low-cost process.

Synthesis of Partial Behavior Models from Properties and Scenarios

Synthesis of behavior models from software development artifacts such as scenario-based descriptions or requirements specifications helps reduce the effort of model construction. However, the models favored by existing synthesis approaches are not sufficiently expressive to describe both universal constraints provided by requirements and existential statements provided by scenarios. In this paper, we propose a novel synthesis technique that constructs behavior models in the form of modal transition systems (MTS) from a combination of safety properties and scenarios. MTSs distinguish required, possible, and proscribed behavior, and their elaboration not only guarantees the preservation of the properties and scenarios used for synthesis but also supports further elicitation of new requirements.

Synthesis of behavioral models from scenarios

Scenario-based specifications such as Message Sequence Charts (MSCs) are useful as part of a requirements specification. A scenario is a partial story, describing how system components, the environment, and users work concurrently and interact in order to provide system level functionality. Scenarios need to be combined to provide a more complete description of system behavior. Consequently, scenario synthesis is central to the effective use of scenario descriptions. How should a set of scenarios be interpreted? How do they relate to one another? What is the underlying semantics? What assumptions are made when synthesizing behavior models from multiple scenarios? In this paper, we present an approach to scenario synthesis based on a clear sound semantics, which can support and integrate many of the existing approaches to scenario synthesis. The contributions of the paper are threefold. We first define an MSC language with sound abstract semantics in terms of labeled transition systems and parallel composition. The language integrates existing approaches based on scenario composition by using high-level MSCs (hMSCs) and those based on state identification by introducing explicit component state labeling. This combination allows stakeholders to break up scenario specifications into manageable parts and reuse scenarios using hMCSs; it also allows them to introduce additional domain-specific information and general assumptions explicitly into the scenario specification using state labels. Second, we provide a sound synthesis algorithm which translates scenarios into a behavioral specification in the form of Finite Sequential Processes. This specification can be analyzed with the Labeled Transition System Analyzer using model checking and animation. Finally, we demonstrate how many of the assumptions embedded in existing synthesis approaches can be made explicit and modeled in our approach. Thus, we provide the basis for a common approach to scenario-based specification, synthesis, and analysis.