Exploring the formation of gold/silver nanoalloys with gas-phase synthesis and machine-learning assisted simulations

While nanoalloys are of paramount scientific and practical interest, the main processes leading to their formation are still poorly understood. Key structural features in the alloy systems, including the crystal phase, chemical ordering, and morphology, are challenging to control at the nanoscale, making it difficult to extend their use to industrial applications. In this contribution, we focus on the gold/silver system that has two of the most prevalent noble metals and combine experiments with simulations to uncover the formation mechanisms at the atomic level. Nanoparticles were produced using a state-of-the-art inert-gas aggregation source and analyzed using transmission electron microscopy and energy-dispersive X-ray spectroscopy. Machine-learning-assisted molecular dynamics simulations were employed to model the crystallization process from liquid droplets to nanocrystals. Our study finds a preponderance of nanoparticles with five-fold symmetric morphology, including icosahedra and decahedra which is consistent with previous results on mono-metallic nanoparticles. However, we observed that gold atoms, rather than silver atoms, segregate at the surface of the obtained nanoparticles for all the considered alloy compositions. These segregation tendencies are in contrast to previous studies and have consequences on the crystallization dynamics and the subsequent crystal ordering. We finally showed that the underpinning of this surprising segregation dynamics is due to charge transfer and electrostatic interactions rather than surface energy considerations.

Monometallic and alloy nanoparticles: a review of biomedical applications

Current intrinsic deficiencies in biomedicine promote the rapid development of alternative multitasking approaches. Recently, monometallic and alloy nanoparticles (NPs) have been widely studied for their potential biomedical applications. However, the research mainly focuses on monometallic compounds and metal oxide NPs that have already been studied. In this review, we investigate promising modified mono- and bimetallic NPs for improving the current state of materials science in medicine. It was contended that effective general biomedical applications can be enhanced by intelligent NP design. Particularly, we discuss transition and platinum metal compositions, iron-based and non-iron compounds, along with liquid alloys. Subsequently, we explore the capabilities provided by modifications such as inorganic and organic coatings, polymers, and biomolecules that can invent new NP designs for precise applications, ultimately resulting in an improved patient outcome. We provide a comprehensive assessment of the advantages and limitations of monometallic and alloy nanomaterials and possible solutions to problems that delay their development.

Atomistic Mechanisms of Binary Alloy Surface Segregation from Nanoseconds to Seconds Using Accelerated Dynamics

Although the equilibrium composition of many alloy surfaces is well understood, the rate of transient surface segregation during annealing is not known, despite its crucial effect on alloy corrosion and catalytic reactions occurring on overlapping timescales. In this work, CuNi bimetallic alloys representing (100) surface facets are annealed in vacuum using atomistic simulations to observe the effect of vacancy diffusion on surface separation. We employ multi-timescale methods to sample the early transient, intermediate, and equilibrium states of slab surfaces during the separation process, including standard MD as well as three methods to perform atomistic, long-time dynamics: parallel trajectory splicing (ParSplice), adaptive kinetic Monte Carlo (AKMC), and kinetic Monte Carlo (KMC). From nanosecond (ns) to second timescales, our multiscale computational methodology can observe rare stochastic events not typically seen with standard MD, closing the gap between computational and experimental timescales for surface segregation. Rapid diffusion of a vacancy to the slab is resolved by all four methods in tens of nanoseconds. Stochastic re-entry of vacancies into the subsurface, however, is only seen on the microsecond timescale in the two KMC methods. Kinetic vacancy trapping on the surface and its effect on the segregation rate are discussed. The equilibrium composition profile of CuNi after segregation during annealing is estimated to occur on a timescale of seconds as determined by KMC, a result directly comparable to nanoscale experiments.

Atom Probe Study of the Miscibility Gap in CuNi Thin Films and Microstructure Development

The unclear miscibility of CuNi alloys was investigated with atom probe tomography (APT). Multilayered thin film samples were prepared by ion beam sputtering (IBS) and focused ion beam (FIB) shaping. Long-term isothermal annealing treatments in a UHV furnace were conducted at temperatures of 573, 623, and 673 K to investigate the mixing process. The effective interdiffusion coefficient of the nanocrystalline microstructure (including defect diffusion) was determined to be Deff = 1.86 × 10−10 m2/s × exp(−164 kJ/mol/RT) by fitting periodic composition profiles through a Fourier series. In nonequilibrium states, microstructural defects like grain boundaries and precipitates were observed. While at the two higher temperatures total mixing is observed, a clear experimental evidence is found for a miscibility gap at 573 K with the boundary concentrations of 26 and 66 at%. These two compositions are used in a subregular solution model to reconstruct the phase miscibility gap. So, the critical temperature TC of the miscibility gap is found to be 608 K at a concentration of 45 at% Ni.

A theoretical investigation of 38-atom CuPd clusters: the effect of potential parameterisation on structure and segregation

Understanding the structure of bimetallic clusters is increasingly important due to their emerging practical applications. Herein we investigate the structure of 38-atom CuPd clusters using a genetic algorithm with cluster energies described by the semi-empirical Gupta potential. Selected clusters are then refined with density functional theory. Three different parameterisations of the Gupta potential are used and their performance assessed to understand what features of bulk and surfaces are necessary to capture for accurate description of small clusters. Three general regions of motif stability exist; for the Pd majority clusters (Pd38 to Cu4Pd34) the truncated octahedron is most stable, while for clusters of intermediate compositions (Cu5Pd33 to Cu25Pd13) a "pancake" icosahedron is most stable, and for the Cu majority clusters (Cu26Pd12 to Cu38) again the truncated octahedron is most stable. CuPd clusters tend to segregate to a Cu-core, Pd-shell structure if possible, and at higher Cu compositions, the Pd segregates to the faces of the cluster. Using multiple parameterisations of the Gupta potential ensures the full variety of possible structures is found, and improves the search for the most stable CuPd clusters.

Thermal properties and segregation phenomena in transition metals and alloys: modeling based on modified cohesive-energies

In spite of free-atom electronic-relaxation contributions to transition-metal cohesive-energies, numerous studies have misused the latter instead of using the solid-state interatomic bond-energy in modeling bulk and surface properties. This work reveals that eliminating the free-atom contributions from experimental cohesive-energies leads to highly accurate linear correlations of the resultant bond-energies with melting temperatures and enthalpies, as well as with inverse thermal-expansion coefficients, specifically for the fcc transition-metals. Likewise, predictions of surface segregation phenomena in Cu-Pd and Au-Pd alloys on the basis of the modified energetics are in much better agreement with reported low-energy ion scattering spectroscopy (LEISS) experimental results, as compared to the use of cohesive-energy values. A last demonstration of the problem and its solution involves the significant impact of the modification on segregation (separation) phase transitions in Cu-Ni model nanoparticles.

Growth and shape stability of Cu-Ni core-shell nanoparticles: an atomistic perspective

The growth and shape stability of bi-metallic cubic Cu-Ni nanoparticles are studied using atomic-level simulations. Cubic nano-crystals coated with an ultra-thin Cu layer can be readily obtained when Ni cubic nanoparticles are used as the seeds. At elevated temperatures, the Cu seed with extending Ni branches preserves its shape compared to the Ni seed with extending Cu branches.

Tunable Magnetism in Nanoporous CuNi Alloys by Reversible Voltage-Driven Element-Selective Redox Processes

Voltage-driven manipulation of magnetism in electrodeposited 200 nm thick nanoporous single-phase solid solution Cu₂₀ Ni₈₀ (at%) alloy films (with sub 10 nm pore size) is accomplished by controlled reduction-oxidation (i.e., redox) processes in a protic solvent, namely 1 m NaOH aqueous solution. Owing to the selectivity of the electrochemical processes, the oxidation of the CuNi film mainly occurs on the Cu counterpart of the solid solution, resulting in a Ni-enriched alloy. As a consequence, the magnetic moment at saturation significantly increases (up to 33% enhancement with respect to the as-prepared sample), while only slight changes in coercivity are observed. Conversely, the reduction process brings Cu back to its metallic state and, remarkably, it becomes alloyed to Ni again. The reported phenomenon is fully reversible, thus allowing for the precise adjustment of the magnetic properties of this system through the sign and amplitude of the applied voltage.