Multicomponent one-pot synthesis of (dihydro-1H-benzo[d]imidazole) phosphonate

Abstract

We present a multicomponent reaction strategy to synthesize a (dihydro-1H-benzo[d]imidazole)phosphonate family of compounds, using benzimidazoles, diethyl chlorophosphate and aliphatic amines as starting reactants. Giving its simplicity, our procedure involves reaction times of only few hours and avoid the usage of any catalyst agent. All the newly synthesized compounds were characterized by Nuclear Magnetic Resonance spectroscopy (¹H, ¹³C and ³¹P) and mass spectrometry by the DART method.     

Controlling the propagation of broadband light pulses by Electromagnetically Induced Transparency

We present an experimental and theoretical investigation, performed on hot sodium atoms in a ladder scheme, showing the control of the absorption and of the propagation velocity of a probe light pulse with a spectral bandwidth as large as 1.8 GHz. The predictions of the theoretical model compare favorably with the experimental results.     

Design of integrated and autonomous conductivity–temperature–depth (CTD) sensors

Impedance characterization of interfaces is a basic technique for a large class of chemical and biological sensors. This technique is often used to model interfaces between ion-based and electron-based conductive materials by means of electric variables such as voltage, current and charge. Conductivity–temperature–depth (CTD) sensors are sophisticated devices used in the environmental monitoring field to understand the effects of climate changes on oceans and on marine organisms. They usually require impedance sensing as readout technique. High-accuracy CTD sensors are present on the market but they are bulky and power hungry. However, the downscale of modern CMOS technology allows shrinking very complex bioelectronic interfaces into millimeter square size systems, thus opening a large ground of applications. This paper will describe an IC architecture and the related design approach to implement an electrochemical impedance spectroscopy (EIS) technique for CTD sensing and will propose a general approach for sensing complex impedance with low power consumption and high precision. The presented system is designed to achieve 15-bit resolution and power consumption to ensure lifetime up to 1 year using button-size batteries in ocean environment.     

Controlling 6-endo-selectivity in oxidation/bromocyclization cascades for synthesis of aplysiapyranoids and other 2,2,6,6-substituted tetrahydropyrans

A cascade, composed of (i) oxovanadium(V)-catalyzed oxidation of bromide by tert-butyl hydroperoxide and (ii) stereoselective 6-endo-bromocyclization, affords 3-bromo-2-aryl-2,6,6-trimethyltetrahydropyrans from styrene-type tertiary alkenols in synthetically useful yields. (E)-Alkenols add the bromo- and the alkoxy substituent anti-selectively across the double bond, indicating a bromonium ion-mechanism for the ring closure. 6-endo-control of the alkenol cyclization thereby arises from the polar effect of the aryl substituent. Two methyl substituents bound to the alkene terminus are not similarly able to favor 6-endo-cyclization, because strain arising from methyl group repulsion, as the bromonium-activated π-bond and the hydroxyl oxygen approach, directs bromocyclization of tertiary prenyl-type substrates toward tetrahydrofuran formation. A hexasubstituted bromotetrahydropyran prepared from the oxidation/bromocyclization cascade served as starting material for synthesis of racemic aplysiapyranoid A, in a sequence of free radical and polar functional group interconversion.     

Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.     

Thermoacoustic Emission from Carbon Nanotubes Imaged by Atomic Force Microscopy

The thermoacoustic effect of isolated single‐wall carbon nanotubes aligned between electrodes is experimentally observed for the first time by imaging the emitted acoustic wave using an atomic force microscopy‐based technique specifically developed for the task. The capability of such a technique for single‐point thermoacoustic measurements is first verified on carbon nanotubes layers with two electrodes for injecting alternate electric current. The technique is then demonstrated to allow the acquisition, simultaneously with the topography, of images reflecting the pressure of the acoustic wave at fixed distance from the sample. Such a capability is used to collect images reflecting the amplitude of acoustic waves generated by isolated nanotubes and nanotube bundles by the thermoacoustic effect.     

Modelling and design of a novel air-spring for a suspension seat

Air-springs used in conjunction with auxiliary volumes provide both spring stiffness and damping. The damping is introduced through the flow restriction connecting the two air volumes. This article presents a simplified model of an air-spring with an auxiliary volume derived from first principles for simulation and design of an air-spring coupled to an auxiliary volume for a suspension seat. Tests were performed on an experimental apparatus to validate the model. The simulation model of the air-spring and auxiliary volume followed the trend predicted by the literature but showed approximately 27% lower transmissibility amplitude and 21% lower system natural frequency than that obtained by tests when using large diameter flow restrictions. This inaccuracy is assumed to be introduced by the simplified mass transfer equations defining the flow restriction between air-spring and auxiliary volume. The model showed closer correlation to the experimental results when the auxiliary volume size was decreased by two-thirds of the volume actually used for the experiment. A procedure, using the developed simulation model, for the design of a prototype air-spring and auxiliary volume, is presented for application in a typical articulated or rigid frame dump truck. The goal of the study was to design a suspension seat for this application and to obtain a SEAT value below 1.1. The design was optimised by varying auxiliary volume size and flow restriction diameters for different loads. A SEAT value of less than 0.9 was achieved, clearly indicating the effectiveness of using an auxiliary volume with an air-spring as seat suspension.