Fractal structures in two-metal electrodeposition systems I: Pb and Zn

Predicting Outcomes of Nanoparticle Attachment by Connecting Atomistic, Interfacial, Particle, and Aggregate Scales

Predicting nanoparticle aggregation and attachment phenomena requires a rigorous understanding of the interplay among crystal structure, particle morphology, surface chemistry, solution conditions, and interparticle forces, yet no comprehensive picture exists. We used an integrated suite of experimental, theoretical, and simulation methods to resolve the effect of solution pH on the aggregation of boehmite nanoplatelets, a case study with important implications for the environmental management of legacy nuclear waste. Real-time observations showed that the particles attach preferentially along the (010) planes at pH 8.5 and the (101) planes at pH 11. To rationalize these results, we established the connection between key physicochemical phenomena across the relevant length scales. Starting from molecular-scale simulations of surface hydroxyl reactivity, we developed an interfacial-scale model of the corresponding electrostatic potentials, with subsequent particle-scale calculations of the resulting driving forces allowing successful prediction of the attachment modes. Finally, we scaled these phenomena to understand the collective structure at the aggregate-scale. Our results indicate that facet-specific differences in surface chemistry produce heterogeneous surface charge distributions that are coupled to particle anisotropy and shape-dependent hydrodynamic forces, to play a key role in controlling aggregation behavior.

Turing patterns by supramolecular self-assembly of a single salphen building block

In the 1950s, Alan Turing showed that concerted reactions and diffusion of activating and inhibiting chemical species can autonomously generate patterns without previous positional information, thus providing a chemical basis for morphogenesis in Nature. However, access to these patterns from only one molecular component that contained all the necessary information to execute agonistic and antagonistic signaling is so far an elusive goal, since two or more participants with different diffusivities are a must. Here, we report on a single-molecule system that generates Turing patterns arrested in the solid state, where supramolecular interactions are used instead of chemical reactions, whereas diffusional differences arise from heterogeneously populated self-assembled products. We employ a family of hydroxylated organic salphen building blocks based on a bis-Schiff-base scaffold with portions responsible for either activation or inhibition of assemblies at different hierarchies through purely supramolecular reactions, only depending upon the solvent dielectric constant and evaporation as fuel.

Random Spacing between Metal Tree Electrodeposits in Linear DLA Arrays

When we examine the random growth of trees along a linear alley in a rural area, we wonder what governs the location of those trees, and hence the distance between adjacent ones. The same question arises when we observe the growth of metal electro-deposition trees along a linear cathode in a rectangular film of solution. We carry out different sets of experiments wherein zinc trees are grown by electrolysis from a linear graphite cathode in a 2D film of zinc sulfate solution toward a thick zinc metal anode. We measure the distance between adjacent trees, calculate the average for each set, and correlate the latter with probability and entropy. We also obtain a computational image of the grown trees as a function of parameters such as the cell size, number of particles, and sticking probability. The dependence of average distance on concentration is studied and assessed.

Ag fractal structures in electroless metal deposition systems with and without magnetic field

Metal electrodeposition systems display tree-like structures with extensive ramification and a fractal character. Electrolysis is not a necessary route for the growth of such dendritic metal deposits. We can grow beautiful ramification patterns via a simple redox reaction. We present here a study of silver (Ag) deposits from the reduction of Ag⁺ in (AgNO₃) solution by metallic copper. The experiments are carried out in discotic geometry, in a Petri dish hosting a thin AgNO₃ solution film. A variety of deposited structures and patterns is obtained at different Ag⁺ concentrations, yet with essentially the same fractal dimension averaged at 1.64, typical of diffusion-limited aggregation (DLA). A linear magnetic field of low induction (0.50-1.0 T) applied across the medium causes a notable transformation in the morphology of the deposits. In both the field off and the field on cases, the effect of vertical (hence 3D) heaving seems to be dominant, perhaps explaining the nearly constant fractal dimension.

Self-organization in precipitation reactions far from the equilibrium

Far from the thermodynamic equilibrium, many precipitation reactions create complex product structures with fascinating features caused by their unusual origins. Unlike the dissipative patterns in other self-organizing reactions, these features can be permanent, suggesting potential applications in materials science and engineering. We review four distinct classes of precipitation reactions, describe similarities and differences, and discuss related challenges for theoretical studies. These classes are hollow micro- and macrotubes in chemical gardens, polycrystalline silica carbonate aggregates (biomorphs), Liesegang bands, and propagating precipitation-dissolution fronts. In many cases, these systems show intricate structural hierarchies that span from the nanometer scale into the macroscopic world. We summarize recent experimental progress that often involves growth under tightly regulated conditions by means of wet stamping, holographic heating, and controlled electric, magnetic, or pH perturbations. In this research field, progress requires mechanistic insights that cannot be derived from experiments alone. We discuss how mesoscopic aspects of the product structures can be modeled by reaction-transport equations and suggest important targets for future studies that should also include materials features at the nanoscale.

Fractal structures in two-metal electrodeposition systems II: Cu and Zn

In this second part of our study on fractal co-electrochemical deposition, we investigate the Cu-Zn system. Macroscopic and microscopic inspection shows a sensitive dependence of the morphology of the final pattern on initial concentrations. The pattern is seen to undergo a transition from classical dendrites to randomly ramified deposits, with each slight increase in [Cu(2+)](0), while [Zn(2+)](0) is maintained constant. The variational trends in chemical composition, growth velocity, and fractal dimension with increasing [Cu(2+)](0) are analyzed. The latter is seen to generally increase with copper (II) ion concentration. In contrast, the growth rate of the deposits is seen to decrease with increasing concentration of Cu(2+) ions. A new probe of dense ramified morphology, the pattern density, is introduced and seen to increase with [Cu(2+)](0). XRD measurements reveal that the observed properties correlate with the birth of copper-rich nuclei, which disrupt the crystalline anisotropy of the two-metal alloy.