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We utilize a combined computational-experimental approach to examine the influence of indium nanoparticle (NP) array distributions on deep-ultraviolet (UV) plasmon resonances. For photon energies < 5.7 eV, analysis of ellipsometric spectra reveals an increase in silicon reflectance induced by indium NP arrays on silicon. For various energies in the range 5.7–7.0 eV, a decrease in reflectance is induced by the NP arrays. Similar trends in reflectance are predicted from finite-difference time-domain (FDTD) simulations using NP size distributions extracted from atomic-force micrographs as input. In addition, in the energy range of 7.4–9.2 eV, the FDTD simulations reveal reflectance minima, characteristic of localized surface plasmon resonances. Electron energy-loss spectroscopy collected from individual indium NPs reveals the presence of LSPR at ≈ 8 eV, further supporting the promise of indium NP arrays on silicon for deep-UV plasmonics. 

Semiconductor quantum dots (QDs) are nanostructures that can enhance the performance of electronic devices due to their 3D quantization. Typically, heterovalent impurities, or dopants, are added to semiconducting QDs to provide extra electrons and improve conductivity. Since each QD is expected to contain a few dopants, the extra electrons and their parent dopants have been difficult to locate. In this work, we investigate the spatial distribution of the extra electrons and their parent donors in epitaxial InAs/GaAs QDs using local-electrode atom-probe tomography and self-consistent Schrödinger–Poisson simulations in the effective mass approximation. Although dopants are provided in both layers, the ionized donors primarily reside outside of the QDs, providing extra electrons that are contained within the QDs. Indeed, due to the quantum confinement-induced enhancement of the donor ionization energy within the QDs, a lower fraction of dopants within the QDs are ionized. These findings suggest a pathway toward the development of 3D modulation-doped nanostructures. 

We have examined the origins of polytype selection during metal-mediated molecular-beam epitaxy of GaN nanowires (NWs). High-angle annular dark-field scanning transmission electron microscopy reveals [111]-oriented zinc blende (ZB) NWs and [0001]-oriented wurtzite (WZ) NWs, with SixNy at the interface between individual NWs and the Si (001) substrate. Quantitative energy dispersive x-ray spectroscopy reveals a notably higher Si concentration of 7.0% ± 2.3% in zinc blende (ZB) NWs than 2.3% ± 1.2% in wurtzite (WZ) NWs. Meanwhile, density functional theory calculations show that incorporation of 8 at. % Si on the Ga sublattice inverts the difference in formation energies between WZ and ZB GaN, such that the ZB polytype of GaN is stabilized. This identification of Si and other ZB polytype stabilizers will enable the development of polytype heterostructures in a wide variety of WZ-preferring compounds. 

We have investigated the origins of photoluminescence from quantum dot (QD) layers prepared by alternating depositions of sub-monolayers and a few monolayers of size-mismatched species, termed as sub-monolayer (SML) epitaxy, in comparison with their Stranski–Krastanov (SK) QD counterparts. Using measured nanostructure sizes and local In-compositions from local-electrode atom probe tomography as input into self-consistent Schrödinger–Poisson simulations, we compute the 3D confinement energies, probability densities, and photoluminescence (PL) spectra for both InAs/GaAs SML- and SK-QD layers. A comparison of the computed and measured PL spectra suggests one-dimensional electron confinement, with significant 3D hole localization in the SML-QD layers that contribute to their enhanced PL efficiency in comparison to their SK-QD counterparts. 

N incorporation mechanisms in GaAs1−xNx alloys are probed using combined experimental and computational Rutherford backscattering spectrometry and nuclear reaction analysis angular yield scans. For xN < 0.025, in addition to substitutional nitrogen, NAs, (N-N)As, and (N-As)As split-interstitials are observed. However, for xN ≥ 0.025, evidence for N tetrahedral interstitials, Ntetra, emerges. We propose a mechanism for stabilization of Ntetra in which the elastic interaction between Ntetra and NAs is induced by the opposite signs of their misfit volumes. This work opens opportunities for exploring the formation of Ntetra and its influence on the properties of a variety of highly mismatched alloys. 

We have investigated the influence of non-stoichiometry and local atomic environments on carrier transport in GaAs(N)Bi alloy films using local-electrode atom probe tomography (LEAP) in conjunction with time-resolved terahertz photoconductivity measurements. The local concentrations of N, Bi, and excess As, as well as Bi pair correlations, are quantified using LEAP. Using time-resolved THz photoconductivity measurements, we show that carrier transport is primarily limited by excess As, with the highest carrier mobilities for layers with yBi > 0.035. 

We probe the conduction-band offsets (CBOs) and confined states at GaAs/GaAsNBi quantum wells (QWs). Using a combination of capacitance–voltage (C–V) measurements and self-consistent Schrödinger–Poisson simulations based on the effective mass approximation, we identify an N-fraction dependent increase in CBO, consistent with trends predicted by the band anti-crossing model. Using the computed confined electron states in conjunction with photoluminescence spectroscopy data, we show that N mainly influences the conduction band and confined electron states, with a relatively small effect on the valence band and confined hole states in the quaternary QWs. This work provides important insight toward tailoring CBO and confined electron energies, both needed for optimizing infrared optoelectronic devices. 

Abstract We examine the impact of writing-to-learn (WTL) on promoting conceptual understanding of introductory materials science and engineering, including crystal structures, stress–strain behavior, phase diagrams, and corrosion. We use an analysis of writing products in comparison with pre/post concept-inventory-style assessments. For all topics, statistically significant improvements between draft and revision scores are apparent. For the stress–strain and phase diagram WTL assignments that require synthesis of qualitative data into quantitative formats, while emphasizing microstructure-properties correlations, the highest WTL effect sizes and medium-to-high gains on corresponding assessments are observed. We present these findings and suggest strategies for future WTL design and implementation. Graphic abstract