43 research outputs found
Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment
The use of high-power industrial equipment, such as large-scale mixing equipment or a hydrocyclone for separation of particles in liquid suspension, demands careful monitoring to ensure correct operation. The fundamental task of state-estimation for the liquid suspension can be posed as a time-evolving inverse problem and solved with Bayesian statistical methods. In this article, we extend Bayesian methods to incorporate statistical models for the error that is incurred in the numerical solution of the physical governing equations. This enables full uncertainty quantification within a principled computation-precision trade-off, in contrast to the over-confident inferences that are obtained when all sources of numerical error are ignored. The method is cast within a sequential Monte Carlo framework and an optimized implementation is provided in Python
High Electron Mobility in Vacuum and Ambient for PDIF-CN2 Single-Crystal Transistors
We have investigated the electron mobility on field-effect transistors based
on PDIF-CN single crystals. The family of the small molecules
PDI8-CN has been chosen for the promising results obtained for
vapour-deposited thin film FETs. We used as gate dielectric a layer of PMMA
(spinned on top of the SiO), to reduce the possibility of electron
trapping by hydroxyl groups present at surface of the oxide. For these devices
we obtained a room temperature mobility of 6 cm/Vs in vacuum and 3
cm/Vs in air. Our measurements demonstrate the possibility to obtain
n-type OFETs with performances comparable to those of p-type devices.Comment: published online in JAC
Efficient spatio-temporal Gaussian regression via Kalman filtering
We study the non-parametric reconstruction of spatio-temporal dynamical processes via Gaussian Processes (GPs) regression from sparse and noisy data. GPs have been mainly applied to spatial regression where they represent one of the most powerful estimation approaches also thanks to their universal representing properties. Their extension to dynamical processes has been instead elusive so far since classical implementations lead to unscalable algorithms or require some sort of approximation. We propose a novel procedure to address this problem by coupling GPs regression and Kalman filtering. In particular, assuming space/time separability of the covariance (kernel) of the process and rational time spectrum, we build a finite-dimensional discrete-time state-space process representation amenable to Kalman filtering. With sampling over a finite set of fixed spatial locations, our major finding is that the current Kalman filter state represents a sufficient statistic to compute the minimum variance estimate of the process at any future time over the entire spatial domain. In machine learning, a representer theorem states that an important class of infinite-dimensional variational problems admits a computable and finite-dimensional exact solution. In view of this, our result can be interpreted as a novel Dynamic Representer Theorem for GPs. We then extend the study to situations where the spatial input locations set varies over time. The proposed algorithms are tested on both synthetic and real field data, providing comparisons with standard GP and truncated GP regression techniques
Q fever: a serological survey on the sheep population of Northern Italy following a human outbreak
Investigation of the Optoelectronic Properties of Organic Light-Emitting Transistors Based on an Intrinsically Ambipolar Material
Dimers of polar chromophores in solution: role of excitonic interactions in one- and two-photon absorption properties
Abstract: The possibility to exploit a bottom-up approach to design and synthesize multichromophoric structures from a single molecular unit is strategic for the targeted synthesis of molecular compounds with well defined linear and nonlinear absorption properties. In this view, it is important to be able to predict the properties of multichromophoric units, based on the knowledge of the properties of the individual chromophores and their mutual arrangement. To this end, we present a combined experimental and theoretical study on 4-(para-di-n-butylaminostyryl)-pyridine, a push-pull molecule, and its dimer, 4,4'-bis(para-di-n-butylaminostyryl)-2,2'-bipyridine, formed by connecting the two pyridine groups into a bipyridine structure. One photon absorption and fluorescence spectra are measured in solvents of different polarity, and two-photon absorption spectra are recorded in dichloromethane. Experimental results are compared with results of TDDFT (Time-Dependent Density Functional Theory) and CIS (Configuration Interaction with Single excitation) methods implemented in the Gaussian03 program suite. An essential-state analysis of optical spectra is used to rationalize the observed behavior
Optimal power flow studies in direct current grids: An application of the bio-inspired elephant swarm water search algorithm
Dimers of polar chromophores in solution: role of excitonic interactions in one- and two-photon absorption properties
The possibility to exploit a bottom-up approach to design and synthesize multichromophoric structures from a single molecular unit is strategic for the targeted synthesis of molecular compounds with well defined linear and nonlinear absorption properties. In this view, it is important to be able to predict the properties of multichromophoric units, based on the knowledge of the properties of the individual chromophores and their mutual arrangement. To this end, we present a combined experimental and theoretical study on 4-(para-di-n-butylaminostyryl)-pyridine, a push-pull molecule, and its dimer, 4,4'-bis(para-di-n-butylaminostyryl)-2,2'-bipyridine, formed by connecting the two pyridine groups into a bipyridine structure. One photon absorption and fluorescence spectra are measured in solvents of different polarity, and two-photon absorption spectra are recorded in dichloromethane. Experimental results are compared with results of TDDFT (Time-Dependent Density Functional Theory) and CIS (Configuration Interaction with Single excitation) methods implemented in the Gaussian03 program suite. An essential-state analysis of optical spectra is used to rationalize the observed behavior
Two-photon absorption properties and <sup>1</sup>O<inf>2</inf> generation ability of Ir complexes: An unexpected large cross section of [Ir(CO)<inf>2</inf>Cl(4-(para-di-n-butylaminostyryl)pyridine)]
The new complexes cis-[Ir(CO)(2)Cl(4-(para-di-n-butylaminostyryl)pyridine)] (1) and [Ir(cyclometallated-2-phenylpyridine) (2)(4,4'-(para-di-n-butylaminostyryl)-2,2'-bipyridine)][PF6] (3) were synthesized and fully characterized along with the known complex Ir(cyclometallated-2-phenylpyridine)(2)(5-Me-1,10-phenanthroline)][ PF6] (2). Remarkably, complex 1, with an Ir(I) centre, displays fluorescence - as opposed to the phosphorescence typical of many Ir(III) complexes -with a modestly high quantum yield in solution, opening a new route for the design of iridium-based emitters which should not be limited to the +3 oxidation state. It is also characterized by an unexpectedly large two-photon absorption (TPA) cross section, an order of magnitude higher than that previously reported for Ir(III) or Pt(II) complexes. The great potential of cyclometallated Ir(III) complexes for photodynamic therapy was confirmed, with 2 and 3 showing a good singlet oxygen generation ability, coupled with a modest TPA activity for 2