output
19972026
most citedNoble-Metal-Free Photocatalytic Hydrogen Evolution Activity: The Impact of Ball Milling Anatase Nanopowders with TiH2

76 citations

24 papers

cond-mat.mtrl-sci2026

One-dimensional self-organization of water molecules in proton conducting Andersson-Wadsley titanates

Mathilde Arnaud, Guillaume Benas, Narimane Meziani +13

Layered alkali titanates with M 2 Ti 2 O 5 chemical formula (MTO, M=K,Rb) belonging to the Andersson-Wadsley perovskite family spontaneously incorporate water to form MTO.(H 2 O) x…

math.ST2026

Non-asymptotic Tail Bounds for the Kostlan--Shub--Smale Field: Tensor PCA and Spherical -Spin Complexity

Jean-Marc Azaïs, Federico Dalmao, Yohann De Castro

This paper builds a hierarchy of explicit, non-asymptotic tail bounds for the supremum of the Kostlan--Shub--Smale (KSS) random field on the sphere, and applies it to two problems:…

math.OC2026

Fast Spawn\&Prune (FS\&P): Global convergence of stochastic conic particle gradient descent via birth/death process

Yohann De Castro, Sébastien Gadat, Clément Marteau

We investigate the global optimization of the objective function arising in continuous sparse regression, specifically the Beurling LASSO (BLASSO), over the space of measures. Whil…

math.PR2025

Derivative formula for capacities

Amine Asselah, Bruno Schapira, Perla Sousi

We obtain a derivative formula for various notions of capacity. Namely we identify the second order term in the asymptotic expansion of the capacity of a union of two sets, as thei…

cond-mat.mtrl-sci2025

Metallurgy at the nanoscale: domain walls in nanoalloys

Grégoire Breyton, Hakim Amara, Jaysen Nelayah +8

In binary alloys, domain walls play a central role not only on the phase transitions but also on their physical properties and were at the heart of the 70's metallurgy research. Wh…

math.ST2025

Gaussian Mixture Model with unknown diagonal covariances via continuous sparse regularization

Romane Giard, Yohann de Castro, Clément Marteau

This paper addresses the statistical estimation of Gaussian Mixture Models (GMMs) with unknown diagonal covariances from independent and identically distributed samples. We employ…