Electrochemical Process for Diazinon Removal from Aqueous Media: Design of Experiments, Optimization, and DLLME-GC-FID Method for Diazinon Determination

In the present study, electrochemical process was studied via removal of diazinon (O,O-diethyl O-2-isopropyl-6-methylpyrimidin-4-yl phosphorothioate) as an insecticide/ acaricide organic case study. Influences of three operational parameters including initial ferrous ion concentration, initial hydrogen peroxide concentration, and initial diazinon concentration were measured and optimized in diazinon removal process. Response surface methodology (RSM) was used to design the experiments. The experimental data collected in a laboratory-scaled batch reactor equipped with four graphite bar electrodes as cathode and an aluminum sheet electrode as an anode. Quantitative analysis of diazinon was done with gas chromatography equipped with flame photometric detector. Disperse liquid–liquid microextraction was used prior to gas chromatography in order to extraction and preconcentration of diazinon from aqueous media to extraction phase. Acetone and chlorobenzene were used as disperser and extraction solvent, respectively. Maximum diazinon removal efficiency of 87% (0.85mg mass removal) in C0 of 2mg/L and 80% (120mg mass removal) in C0 of 300mg/L was achieved under different experimental conditions. The obtained experimental data were used for model building by RSM approach. Finally, optimization process was carried out using RSM algorithm. © 2015, King Fahd University of Petroleum & Minerals

Neural networks in geophysical applications

Neural networks are increasingly popular in geophysics. Because they are universal approximators, these tools can approximate any continuous function with an arbitrary precision. Hence, they may yield important contributions to finding solutions to a variety of geophysical applications. However, knowledge of many methods and techniques recently developed to increase the performance and to facilitate the use of neural networks does not seem to be widespread in the geophysical community. Therefore, the power of these tools has not yet been explored to their full extent. In this paper, techniques are described for faster training, better overall performance, i.e., generalization,and the automatic estimation of network size and architecture

High efficiency coherent optical memory with warm rubidium vapour

By harnessing aspects of quantum mechanics, communication and information processing could be radically transformed. Promising forms of quantum information technology include optical quantum cryptographic systems and computing using photons for quantum logic operations. As with current information processing systems, some form of memory will be required. Quantum repeaters, which are required for long distance quantum key distribution, require optical memory as do deterministic logic gates for optical quantum computing. In this paper we present results from a coherent optical memory based on warm rubidium vapour and show 87% efficient recall of light pulses, the highest efficiency measured to date for any coherent optical memory. We also show storage recall of up to 20 pulses from our system. These results show that simple warm atomic vapour systems have clear potential as a platform for quantum memory

An AC Stark Gradient Echo Memory in Cold Atoms

The burgeoning fields of quantum computing and quantum key distribution have created a demand for a quantum memory. The gradient echo memory scheme is a quantum memory candidate for light storage that can boast efficiencies approaching unity, as well as the flexibility to work with either two or three level atoms. The key to this scheme is the frequency gradient that is placed across the memory. Currently the three level implementation uses a Zeeman gradient and warm atoms. In this paper we model a new gradient creation mechanism - the ac Stark effect - to provide an improvement in the flexibility of gradient creation and field switching times. We propose this scheme in concert with a move to cold atoms (~1 mK). These temperatures would increase the storage times possible, and the small ensemble volumes would enable large ac Stark shifts with reasonable laser power. We find that memory bandwidths on the order of MHz can be produced with experimentally achievable laser powers and trapping volumes, with high precision in gradient creation and switching times on the order of nanoseconds possible. By looking at the different decoherence mechanisms present in this system we determine that coherence times on the order of 10s of milliseconds are possible, as are delay-bandwidth products of approximately 50 and efficiencies over 90%

Storage and Manipulation of Light Using a Raman Gradient Echo Process

The Gradient Echo Memory (GEM) scheme has potential to be a suitable protocol for storage and retrieval of optical quantum information. In this paper, we review the properties of the $\Lambda$-GEM method that stores information in the ground states of three-level atomic ensembles via Raman coupling. The scheme is versatile in that it can store and re-sequence multiple pulses of light. To date, this scheme has been implemented using warm rubidium gas cells. There are different phenomena that can influence the performance of these atomic systems. We investigate the impact of atomic motion and four-wave mixing and present experiments that show how parasitic four-wave mixing can be mitigated. We also use the memory to demonstrate preservation of pulse shape and the backward retrieval of pulses.Comment: 26 pages, 13 figure