Discrimination and identification of dynamic catalytic reaction models via introduction of feedback

Linear and nonlinear feedback manipulations based on effluent concentration measurements from a catalytic CSTR are successfully used to discriminate between two rival models for catalytic N₂O decomposition. Introduction of feedback causes steady-state multiplicity and bifurcation to periodic solutions. Much greater differences between the alternative models are revealed by this approach than by steady-state and “transient response” methods. Limit cycles obtained with feedback have in some cases nonharmonic form near bifurcation which may be attributed to bifurcation phenomena of higher order than the usual Hopf case. The dynamic studies are systematically organized using a new “decrement diagram” technique which displays the influence of two feedback parameters on closed-loop system bifurcations.     

Engineering the temporal response of photoconductive photodetectors via selective introduction of surface trap states

Photoconductive photodetectors fabricated using simple solution-processing have recently been shown to exhibit high gains (>1000) and outstanding sensitivities ( D* > 10(13) Jones). One ostensible disadvantage of exploiting photoconductive gain is that the temporal response is limited by the release of carriers from trap states. Here we show that it is possible to introduce specific chemical species onto the surfaces of colloidal quantum dots to produce only a single, desired trap state having a carefully selected lifetime. In this way we demonstrate a device that exhibits an attractive photoconductive gain (>10) combined with a response time ( approximately 25 ms) useful in imaging. We achieve this by preserving a single surface species, lead sulfite, while eliminating lead sulfate and lead carboxylate. In doing so we preserve the outstanding sensitivity of these devices, achieving a specific detectivity of 10(12) Jones in the visible, while generating a temporal response suited to imaging applications.     

Sensitive solution-processed Bi2S3 nanocrystalline photodetectors

Solution-processed nanocrystal optoelectronic devices offer large-area coverage, low cost, and compatibility with a wide range of substrates. Recently, photodetectors and photovoltaics based on spin-coated nanoparticle films have shown tremendous progress in performance. However, high-performance devices reported to date have employed either Pb or Cd, raising concerns regarding environmental impact and regulatory acceptance. Herein we report a high-performance solution-processed photodetector based instead on Bi2S3 nanocrystals. The devices exhibit photoconductive gain on the order of 10 combined with temporal response on the 10 ms time scale. The resultant solution-processed Bi2S3 nanorod photoconductive photodetectors are of interest in visible and near-infrared (NIR) wavelength applications requiring video-frame-rate temporal response.     

Size Effects of Platinum Nanoparticles in the Photocatalytic Hydrogen Production Over 3D Mesoporous Networks of CdS and Pt Nanojunctions

Catalysts for the photogeneration of hydrogen from water are key for realizing solar energy conversion. Despite tremendous efforts, developing hydrogen evolution catalysts with high activity and long‐term stability remains a daunting challenge. Herein, the design and fabrication of mesoporous Pt‐decorated CdS nanocrystal assemblies (NCAs) are reported, and their excellent performance for the photocatalytic hydrogen production is demonstrated. These materials comprise varying particle size of Pt (ranging from 1.8 to 3.3 nm) and exhibit 3D nanoscale pore structure within the assembled network. Photocatalytic measurements coupled with UV–vis/NIR optical absorption, photoluminescence, and electrochemical impedance spectroscopy studies suggest that the performance enhancement of these catalytic systems arises from the efficient hole transport at the CdS/electrolyte interface and interparticle Pt/CdS electron‐transfer process as a result of the deposition of Pt. It is found that the Pt‐CdS NCAs catalyst at 5 wt% Pt loading content exerts a 1.2 mmol h^?1 H₂‐evolution rate under visible‐light irradiation (λ ≥ 420 nm) with an apparent quantum yield of over 70% at wavelength λ = 420 nm in alkaline solution (5 m NaOH), using ethanol (10% v/v) as sacrificial agent. This activity far exceeds those of the single CdS and binary noble metal/CdS systems, demonstrating the potential for practical photocatalytic hydrogen production.     

Kinetic modeling of a mixed culture of Pseudomonas denitrificans and Bacillus subtilis under aerobic and anoxic operating conditions

The kinetics of biological denitrification have been studied and several models, with varying degree of complexity, to be used for design purposes have been presented in the recent years. However, most of these kinetic studies were performed with mixed (and not well defined) microbial systems, such as activated sludge. In the present work, kinetic experiments were carried out in order to study the dynamic characteristics of a defined mixed culture of the denitrifiers Pseudomonas denitrificans and Bacillus subtilis under anoxic and aerobic conditions in a defined synthetic medium involving a mixture of organic substrates, in the presence of nitrates and/or nitrites. Denitrification was assumed to occur by the consecutive reduction of nitrates to nitrites and then to nitrogen gas without accumulation of intermediate gaseous products. The behavior of these defined mixed cultures was predicted using a kinetic model based on the kinetic models that have already been developed for each bacterium separately and the predictions were compared with the results from mixed culture experiments. The overall mathematical model that was developed and validated in the present work is capable of describing the behavior of the mixed culture in the above conditions, i.e. the nitrates and nitrites reduction kinetics, the cell growth, and the organic carbon utilization rates.     

Adsorption of dyes on Sahara desert sand

Sahara desert sand (SaDeS) was employed as a mineral sorbent for retaining organic dyes from aqueous solutions. Natural sand has demonstrated a strong affinity for organic dyes but significantly lost its adsorption capacity when it was washed with water. Therefore, characterization of both natural and water washed sand was performed by XRD, BET, SEM and FTIR techniques. It was found that water-soluble kyanite, which is detected in natural sand, is the dominant factor affecting adsorbance of cationic dyes. The sand adsorbs over 75% of cationic dyes but less than 21% for anionic ones. Among the dyes studied, Methylene Blue (MB) demonstrated the strongest affinity for Sahara desert sand (Q_e = 11.98 mg/g, for initial dye solution concentration 3.5 × 10⁻⁵ mol/L). The effects of initial dye concentration, the amount of the adsorbent, the temperature and the pH of the solution on adsorption capacity were tested by using Methylene Blue as model dye. Pseudo-first-order, pseudo-second-order and intraparticle diffusion models were applied. It was concluded that adsorption of Methylene Blue on Sahara desert sand followed pseudo-second order kinetics. Gibbs free energy, enthalpy change and entropy change were calculated and found −6411 J/mol, −30360 J/mol and −76.58 J/mol K, respectively. These values indicate that the adsorption is an exothermic process and has a spontaneous nature at low temperatures.     

Visually exploring movement data via similarity-based analysis

Data analysis and knowledge discovery over moving object databases discovers behavioral patterns of moving objects that can be exploited in applications like traffic management and location-based services. Similarity search over trajectories is imperative for supporting such tasks. Related works in the field, mainly inspired from the time-series domain, employ generic similarity metrics that ignore the peculiarity and complexity of the trajectory data type. Aiming at providing a powerful toolkit for analysts, in this paper we propose a framework that provides several trajectory similarity measures, based on primitive (space and time) as well as on derived parameters of trajectories (speed, acceleration, and direction), which quantify the distance between two trajectories and can be exploited for trajectory data mining, including clustering and classification. We evaluate the proposed similarity measures through an extensive experimental study over synthetic (for measuring efficiency) and real (for assessing effectiveness) trajectory datasets. In particular, the latter could serve as an iterative, combinational knowledge discovery methodology enhanced with visual analytics that provides analysts with a powerful tool for “hands-on” analysis for trajectory data.     

Models of computation for reactive control of autonomous mobile robots

The paper studies computation models for tasks performed by autonomous mobile robots. Such tasks can be accomplished by reactive control algorithms. Reactive control systems can be described using different models of computation which have as distinguishing feature the abstraction level of time. Thus, three computation models are defined: the untimed model, the synchronous model and the timed model. It is shown that the clocked-synchronous model of computation is more appropriate for describing the controller for a parallel parking task.