Publications

Mesoporous silica was synthesized in the presence of metal (Au, Pt, and Ag) nanoparticles in the 2−20 nm range. Sample characterization was performed by X-ray diffraction and electron microscopy. The metal nanoparticles in the 2−10 nm range were successfully incorporated into the ordered mesoporous SBA-15 structures; 20 nm particles, whose diameter is larger than the SBA-15 pore size, could not be inserted. In the case of 5 and 10 nm diameter nanoparticles, regardless of which metal, the mesopore channels expanded in order to accommodate the metal particles. By using mixtures of metal nanoparticles of two different sizes, it was found that the inclusion and the resultant pore size were controlled by the larger size metal particles.

Quantitative understanding of nanoscale interactions is a prerequisite for harnessing the remarkable collective properties of nanoparticle systems. Here, we report the combined use of liquid-phase transmission electron microscopy and electron beam lithography to elucidate the interactions between charged nanorods in a predefined potential energy landscape. In situ site-selective lift-off of surface-functionalized lithographed gold nanorods is achieved by patterning them with adhesion layer materials that undergo etching at different rates. Analysis of the subsequent nanorod motion, which is two-dimensionally confined as a result of the particle-substrate attraction, allows quantification of interparticle interactions in a lithographically engineered environment. For lithographed nanorods patterned with the same adhesion layer material, their self-assembly behavior following lift-off is tuned by changing their starting spatial arrangement. Our approach facilitates investigation of interparticle interactions in designed nanoparticle systems and affords fundamental insights into the role of the potential energy landscape in determining the kinetic pathway for nanoparticle self-assembly.

The goal of this work is to identify factors which modulate structural order in 2D self-assembled superlattices of polygon-shaped colloidal nanocrystals. Using combined experimental and simulation techniques, we quantify order in superlattices of hexagonal prism-shaped CdSe/CdS nanocrystals and cube-shaped CsPbBr₃ nanocrystals. Superlattices derived from cube-shaped nanocrystals display less translational order compared to hexagonal prism-shaped nanocrystals both experimentally and in simulations. This effect can be attributed to geometric considerations inherent to the combined rotational and translational symmetries of different polygonal shapes and their superlattices. Cubes form a simple cubic lattice where nanocrystals can slide without steric overlap, whereas hexagonal prisms interlock, preventing translation. Regarding orientational order, cube assemblies display a narrower orientation distribution. Intuitively, hexagonal prisms are a more "spherical" shape compared to cubes. The results presented here outline a conceptual framework for identifying superlattice structures which favor translationally and orientationally ordered self-assembled superlattices.

Images of individual Te chiral nanoparticles and labels of their handedness for classifier training.

The synthesis quality of artificial inorganic nanocrystals is most often assessed by transmission electron microscopy (TEM) for which new high-throughput advances have dramatically increased both the quantity and information richness of metal nanoparticle (mNP) characterization. Existing automated data analysis algorithms of TEM mNP images generally adopt a supervised approach, requiring a significant effort in human preparation of labelled data that reduces objectivity, efficiency, and generalizability. We have developed an unsupervised algorithm AutoDetect-mNP for automated analysis of TEM images that objectively extracts morphological information of convex mNPs from TEM images based on their shape attributes, requiring little to no human input in the process. The performance of AutoDetect-mNP is tested on two datasets of bright field TEM images of Au nanoparticles with different shapes, demonstrating that the algorithm is quantitatively reliable, and can thus serve as a generalizable measure of the morphology distributions of any mNP synthesis. The AutoDetect-mNP algorithm will aid in future developments of high-throughput characterization of newly synthesized mNPs, and the future advent of time-resolved TEM studies that can investigate reaction mechanisms of mNP synthesis and reactivity.

We present experimental evidence that silver nanoparticles in the size range of 5-10 nm undergo a reversible structural transformation under hydrostatic pressures up to 10 GPa. We have used x-ray diffraction with a synchrotron light source to investigate pressure-dependent and size-dependent trends in the crystal structure of silver nanoparticles in a hydrostatic medium compressed in a diamond-anvil cell. Results suggest a reversible linear pressure-dependent rhombohedral distortion which has not been previously observed in bulk silver. We propose a mechanism for this transition that considers the bond-length distribution in idealized multiply twinned icosahedral particles. To further support this hypothesis, we also show that similar measurements of single-crystal platinum nanoparticles reveal no such distortions.

We report on high-resolution transmission electron microscope structural studies of InAs colloidal semiconductor nanocrystal quantum dots (NCQDs) on ultrathin GaAs (001) semiconductor single-crystal substrates. We employ a benign method for preparing electron transparent specimens that is suitable for the study of such fragile samples. The image contrast comprises contributions from electron scattering from both the NCs and the GaAs substrate. Long-term electron exposure studies reveal different damage mechanisms operative in the nanocrystals and the substrate.

Polarization-resolved magnetophotoluminescence spectroscopy is used to study exciton spin states in 40--80 \AA{} diameter chemically synthesized CdSe quantum dots (QDs) at temperatures $T=1.2--50\mathrm{K}.$ The spin polarization is found not to saturate in magnetic fields to 60 T and time-resolved studies indicate a thermal population of exciton states. A simple model incorporating the angle-dependent Zeeman splitting and bright-dark level mixing in these randomly oriented quantum dots is constructed in quantitative agreement with the data. Fits using this model yield a dark exciton g factor of \ensuremath{\sim}0.9 at $T=1.45\mathrm{K},$ which is independent of QD diameter and exhibits a surprising increase with increasing temperature.