How interface properties control the equilibrium shape of core–shell Fe–Au and Fe–Ag nanoparticles

Abstract

While combining two metals in the same nanoparticle can lead to remarkable novel applications, the resulting structure in terms of crystallinity and shape remains difficult to predict. It is thus...

Kinetically Stable Nonequilibrium Gold‐Cobalt Alloy Nanoparticles with Magnetic and Plasmonic Properties Obtained by Laser Ablation in Liquid

“…One of the frontier topics in nanoscience and nanotechnology is the synthesis, study and technological exploitation of metastable phases at the nanoscale, such as nonequilibrium alloys [1–3] . This endeavour is challenging for the synthetic difficulties related to the stabilization of thermodynamically forbidden compositions and/or crystalline structures in objects with nanometric dimensions, [2,3] but also for the open questions about the relation of physical‐chemical behaviours with the actual atomic arrangement in nonequilibrium compounds [4,5] and the experimental techniques with subnanometric resolution required for their assessment, preferably at the single nanoparticle (NP) level [6] . Nonetheless, metal alloys are appealing for optics, plasmonics, catalysis, nanomedicine, magnetism or biosensing [1,7,8] .…”

Self-organization mechanisms in a Fe-Au film: from isolated core-shell to multicore nanoparticles

“…More precisely, for low shell/core volume ratios, a polyhedral shape is adopted both for the core (iron) and the shell (gold), while, when this ratio is greater than 1, the Fe core adopts a quasi-cube shape and is surrounded by 6 truncated Au square pyramids forming the shell. We demonstrated that these different morphologies correspond to equilibrium shapes resulting from the combination of three driving forces: wetting, gold surface energy minimization, and Au/Fe interface energy minimization [18,19]. These driving forces come from three characteristics of the Au-Fe system: (i) the high ability of Au to completely wet Fe nanocrystals, thanks to the large difference in their surface energies, 1.500 J.m −2 for (111) Au compared to 2.417 J.m −2 for (110) Fe (experimental values) [20]; (ii) the difference in the Fe and Au crystal structures, respectively the body-centered cubic (bcc) structure for Fe and the face-centered cubic (fcc) structure for Au; (iii) the existence of two preferred Au/Fe interfaces respectively coherent and semi-coherent, that determines the effective interfacial misfit.…”

“…As observed in the figure, this interface, referred as P N W , is highly misfitted along the 110 F e direction in the {110} F e plane. Clearly, the P B and P N W interfaces compete in the core@shell geometry [18,19].…”

“…Is it possible to achieve a large density of small NPs, or does the deposit evolve towards a low density of large NPs ? To address these questions, in the present paper, we analyze the structural behavior of films including a much larger quantity of Fe than in our previous studies of this system [16][17][18][19], in view of increasing the NPs density or size. Pure Fe and Au capped Fe (Fe-Au) films, deposited at a temperature favoring the 3D growth of both metals, are compared.…”

Non-classical nucleation of zinc oxide from a physically-motivated machine-learning approach

“…Prompted by this large body of fundamental achievements, it becomes timely to reach the same level of understanding for crystallization with more complex materials in order to target more diverse technological applications. So far, the need for large scale simulations have prevented from using quantum accurate modeling including density functional theory (DFT), and the research field dedicated to constructing novel interaction potentials to bridge this computational gap has been ever * julien.lam@cemes.fr expanding [33][34][35][36][37][38][39][40]. In particular, the past decade has seen the emergence of innovative types of interaction potentials based on machine-learning algorithms [41].…”