438 research outputs found
Dry impregnation in fluidized bed: Drying and calcination effect on nanoparticles dispersion and location in a porous support
The synthesis of metal nanoparticles dispersed inside the grains of a porous inorganic support was carried out by ‘‘dry impregnation’’ in a fluidized bed. The principle of this technique consists in the spraying of a solution containing a metal source into a hot fluidized bed of porous particles. The metal source can be of different nature such as metal salts, organometallic precursors or colloidal solutions. The experimental results obtained from iron oxide deposition on a porous silica gel as support, constitute the core of this article but others results concerning the deposition of rhodium from a colloidal suspension containing preformed rhodium nanoparticles are also described. More precisely, this study aims to understand the effect of the bed temperature during the impregnation step, the initial particle porosity and the calcination operating protocol on the metallic nanoparticles dispersion and location in the silica porous particles. The so-obtained products were characterized by various techniques in order to determine their morphology, their surface properties and the dispersion of the nanoparticles inside the support. The results showed that, under the chosen operating conditions, the deposit efficiency is close to 100% and the competition between the drying rate, depending on the process-related variables, and the capillary penetration rate, depending on the physicochemical-related variables, controls the deposit location. A quasi uniform deposit inside the support particles is observed for soft drying. The metal nanoparticles size is controlled by the pore mean diameter of the support as well as the calcination operating protocol
Synthesis of Supported Catalysts by Dry Impregnation in Fluidized Bed
The synthesis of catalytic or not composite materials by dry impregnation in fluidized bed is described. This process can be carried out under mild conditions from solutions of organometallic precursors or colloidal solutions of preformed nanoparticles giving rise to reproducible metallic nanoparticles containing composite materials with a high reproducibility. The adequate choice of the reaction conditions makes possible to deposit uniformly the metal precursor within the porous matrix or on the support surface. When the ratio between the drying time and the capillary penetration time (tsec/tcap) is higher than 10, the impregnation under soft drying conditions leads to a homogeneous deposit inside the pores of the particles of support. The efficiency of the metal deposition is close to 100%, and the size of the formed metal nanoparticles is controlled by the pores diameter. Finally, some of the presented composite materials have been tested as catalysts: iron-based materials were used in carbon-nanotubes synthesis, while Pd and Rh composite materials have been investigated in hydrogenation reactions
Transference Principles for Log-Sobolev and Spectral-Gap with Applications to Conservative Spin Systems
We obtain new principles for transferring log-Sobolev and Spectral-Gap
inequalities from a source metric-measure space to a target one, when the
curvature of the target space is bounded from below. As our main application,
we obtain explicit estimates for the log-Sobolev and Spectral-Gap constants of
various conservative spin system models, consisting of non-interacting and
weakly-interacting particles, constrained to conserve the mean-spin. When the
self-interaction is a perturbation of a strongly convex potential, this
partially recovers and partially extends previous results of Caputo,
Chafa\"{\i}, Grunewald, Landim, Lu, Menz, Otto, Panizo, Villani, Westdickenberg
and Yau. When the self-interaction is only assumed to be (non-strongly) convex,
as in the case of the two-sided exponential measure, we obtain sharp estimates
on the system's spectral-gap as a function of the mean-spin, independently of
the size of the system.Comment: 57 page
Maximizing the Conditional Expected Reward for Reaching the Goal
The paper addresses the problem of computing maximal conditional expected
accumulated rewards until reaching a target state (briefly called maximal
conditional expectations) in finite-state Markov decision processes where the
condition is given as a reachability constraint. Conditional expectations of
this type can, e.g., stand for the maximal expected termination time of
probabilistic programs with non-determinism, under the condition that the
program eventually terminates, or for the worst-case expected penalty to be
paid, assuming that at least three deadlines are missed. The main results of
the paper are (i) a polynomial-time algorithm to check the finiteness of
maximal conditional expectations, (ii) PSPACE-completeness for the threshold
problem in acyclic Markov decision processes where the task is to check whether
the maximal conditional expectation exceeds a given threshold, (iii) a
pseudo-polynomial-time algorithm for the threshold problem in the general
(cyclic) case, and (iv) an exponential-time algorithm for computing the maximal
conditional expectation and an optimal scheduler.Comment: 103 pages, extended version with appendices of a paper accepted at
TACAS 201
Towards a unified theory of Sobolev inequalities
We discuss our work on pointwise inequalities for the gradient which are
connected with the isoperimetric profile associated to a given geometry. We
show how they can be used to unify certain aspects of the theory of Sobolev
inequalities. In particular, we discuss our recent papers on fractional order
inequalities, Coulhon type inequalities, transference and dimensionless
inequalities and our forthcoming work on sharp higher order Sobolev
inequalities that can be obtained by iteration.Comment: 39 pages, made some changes to section 1
Stochastic Invariants for Probabilistic Termination
Termination is one of the basic liveness properties, and we study the
termination problem for probabilistic programs with real-valued variables.
Previous works focused on the qualitative problem that asks whether an input
program terminates with probability~1 (almost-sure termination). A powerful
approach for this qualitative problem is the notion of ranking supermartingales
with respect to a given set of invariants. The quantitative problem
(probabilistic termination) asks for bounds on the termination probability. A
fundamental and conceptual drawback of the existing approaches to address
probabilistic termination is that even though the supermartingales consider the
probabilistic behavior of the programs, the invariants are obtained completely
ignoring the probabilistic aspect.
In this work we address the probabilistic termination problem for
linear-arithmetic probabilistic programs with nondeterminism. We define the
notion of {\em stochastic invariants}, which are constraints along with a
probability bound that the constraints hold. We introduce a concept of {\em
repulsing supermartingales}. First, we show that repulsing supermartingales can
be used to obtain bounds on the probability of the stochastic invariants.
Second, we show the effectiveness of repulsing supermartingales in the
following three ways: (1)~With a combination of ranking and repulsing
supermartingales we can compute lower bounds on the probability of termination;
(2)~repulsing supermartingales provide witnesses for refutation of almost-sure
termination; and (3)~with a combination of ranking and repulsing
supermartingales we can establish persistence properties of probabilistic
programs.
We also present results on related computational problems and an experimental
evaluation of our approach on academic examples.Comment: Full version of a paper published at POPL 2017. 20 page
Automated Unbounded Analysis of Cryptographic Constructions in the Generic Group Model
We develop a new method to automatically prove security statements in the Generic Group Model as they occur in actual papers. We start by defining (i) a general language to describe security definitions, (ii) a class of logical formulas that characterize how an adversary can win, and (iii) a translation from security definitions to such formulas. We prove a Master Theorem that relates the security of the construction to the existence of a solution for the associated logical formulas. Moreover, we define a constraint solving algorithm that proves the security of a construction by proving the absence of solutions.
We implement our approach in a fully automated tool, the tool, and use it to verify different examples from the literature. The results improve on the tool by Barthe et al. (CRYPTO\u2714, PKC\u2715): for many constructions, succeeds in proving standard (unbounded) security, whereas Barthe\u27s tool is only able to prove security for a small number of oracle queries
A formally verified compiler back-end
This article describes the development and formal verification (proof of
semantic preservation) of a compiler back-end from Cminor (a simple imperative
intermediate language) to PowerPC assembly code, using the Coq proof assistant
both for programming the compiler and for proving its correctness. Such a
verified compiler is useful in the context of formal methods applied to the
certification of critical software: the verification of the compiler guarantees
that the safety properties proved on the source code hold for the executable
compiled code as well
Two remarks on generalized entropy power inequalities
This note contributes to the understanding of generalized entropy power
inequalities. Our main goal is to construct a counter-example regarding
monotonicity and entropy comparison of weighted sums of independent identically
distributed log-concave random variables. We also present a complex analogue of
a recent dependent entropy power inequality of Hao and Jog, and give a very
simple proof.Comment: arXiv:1811.00345 is split into 2 papers, with this being on
- …