Atomic hydrogen cleaning of GaSb(001) surfaces

We show that the (001) surface of GaSb can be cleaned efficiently by exposure to atomic hydrogen at substrate temperatures in the range 400–470 °C. This treatment removes carbon and oxygen contamination, leaving a clean, ordered surface with a symmetric (1 × 3) reconstruction after a total H2 dose of approximately 150 kL. An ordered but partially oxidized surface is generated during cleaning, and the removal of this residual oxide is the most difficult part of the process. Auger electron spectroscopy and low energy electron diffraction were used to monitor the chemical cleanliness and the ordering of the surface during the cleaning process, whereas high resolution electron energy loss spectroscopy was used to probe the electronic structure in the near-surface region. The results obtained indicates that this cleaning procedure leaves no residual electronic damage in the near-surface region of the Te-doped (n ~ 5 × 1017 cm – 3) samples of GaSb(001) studied

Epitaxial growth and surface reconstruction of CrSb(0001)

Smooth CrSb(0001) films have been grown by molecular beam epitaxy on MnSb(0001) – GaAs(111) substrates. CrSb(0001) shows (2 × 2), triple domain (1 × 4) and (√3×√3)R30° reconstructed surfaces as well as a (1 × 1) phase. The dependence of reconstruction on substrate temperature and incident fluxes is very similar to MnSb(0001)

Organopalladium catalyst on S-terminated GaAs(001)-(2×6) surface

Organopalladium molecules, such as Pd(CH3COO)2 ({Pd}), immobilized on the S-terminated GaAs(001), termed GaAs–S–{Pd} have high catalytic activity and cycle durability in the Mizoroki–Heck reaction. It is thought that the presence of Ga–S bonds in the single atomic layer S-termination is essential for these catalytic properties despite the much higher thickness (~100 nm) of the {Pd} films. In this study, the authors demonstrate the retention of Ga–S bonds in ultrathin GaAs–S–{Pd} by using reflection high-energy electron diffraction and scanning tunneling microscopy (STM). The ultrathin GaAs–S–{Pd} was prepared by using a vapor-deposition technique. Deposited {Pd} was observed as ~1 nm dotlike structures with STM. The adsorption rate of {Pd} was also investigated

Accumulation layer profiles at InAs polar surfaces

High resolution electron energy loss spectroscopy, dielectric theory simulations, and charge profile calculations have been used to study the accumulation layer and surface plasmon excitations at the In-terminated (001)-(4 × 1) and (111)A-(2 × 2) surfaces of InAs. For the (001) surface, the surface state density is 4.0 ± 2.0 × 1011 cm – 2, while for the (111)A surface it is 7.5 ± 2.0 × 1011 cm – 2, these values being independent of the surface preparation procedure, bulk doping level, and substrate temperature. Changes of the bulk Fermi level with temperature and bulk doping level do, however, alter the position of the surface Fermi level. Ion bombardment and annealing of the surface affect the accumulation layer only through changes in the effective bulk doping level and the bulk momentum scattering rate, with no discernible changes in the surface charge density

Enhancement of island size by dynamic substrate disorder in simulations of graphene growth

We demonstrate a new mechanism in the early stages of sub-monolayer epitaxial island growth, using Monte Carlo simulations motivated by experimental observations on the growth of graphene on copper foil. In our model, the substrate is “dynamically rough”, by which we mean (i) the interaction strength between Cu and C varies randomly from site to site, and (ii) these variable strengths themselves migrate from site to site. The dynamic roughness provides a simple representation of the near-molten state of the Cu substrate in the case of real graphene growth. Counterintuitively, the graphene island size increases when dynamic roughness is included, compared to a static and smooth substrate. We attribute this effect to destabilisation of small graphene islands by fluctuations in the substrate, allowing them to break up and join larger islands which are more stable against roughness. In the case of static roughness, when process (ii) is switched off, island growth is strongly inhibited and the scale-free behaviour of island size distributions, present in the smooth-static and rough-dynamic cases, is destroyed. The effects of the dynamic substrate roughness cannot be mimicked by parameter changes in the static cases

van der Waals epitaxy of monolayer hexagonal boron nitride on copper foil : growth, crystallography and electronic band structure

We investigate the growth of hexagonal boron nitride (h-BN) on copper foil by low pressure chemical vapour deposition (LP-CVD). At low pressure, h-BN growth proceeds through the nucleation and growth of triangular islands. Comparison between the orientation of the islands and the local crystallographic orientation of the polycrystalline copper foil reveals an epitaxial relation between the copper and h-BN, even on Cu(100) and Cu(110) regions whose symmetry is not matched to the h-BN. However, the growth rate is faster and the islands more uniformly oriented on Cu(111) grains. Angle resolved photoemission spectroscopy measurements reveal a well-defined band structure for the h-BN, consistent with a band gap of 6 eV, that is decoupled from the copper surface beneath. These results indicate that, despite a weak interaction between h-BN and copper, van der Waals epitaxy defines the long range ordering of h-BN even on polycrystalline copper foils and suggest that large area, single crystal, monolayer h-BN could be readily and cheaply produced

The thermodynamics of prediction

A system responding to a stochastic driving signal can be interpreted as computing, by means of its dynamics, an implicit model of the environmental variables. The system's state retains information about past environmental fluctuations, and a fraction of this information is predictive of future ones. The remaining nonpredictive information reflects model complexity that does not improve predictive power, and thus represents the ineffectiveness of the model. We expose the fundamental equivalence between this model inefficiency and thermodynamic inefficiency, measured by dissipation. Our results hold arbitrarily far from thermodynamic equilibrium and are applicable to a wide range of systems, including biomolecular machines. They highlight a profound connection between the effective use of information and efficient thermodynamic operation: any system constructed to keep memory about its environment and to operate with maximal energetic efficiency has to be predictive.Comment: 5 pages, 1 figur

Composition profiles of InAs–GaAs quantum dots determined by medium-energy ion scattering

The composition profile along the [001] growth direction of low-growth-rate InAs–GaAs quantum dots (QDs) has been determined using medium-energy ion scattering (MEIS). A linear profile of In concentration from 100% In at the top of the QDs to 20% at their base provides the best fit to MEIS energy spectra

The c(4×4)–a(1×3) surface reconstruction transition on InSb(001) : static versus dynamic conditions

The transition between the a(1 × 3) and c(4 × 4) surface reconstructions of InSb(0 0 1) has been carefully monitored by reflection high energy electron diffraction as a function of temperature and Sb2 flux, without incident In flux. Arrhenius-like behaviour is observed across the whole range of Sb2 fluxes and temperatures, allowing accurate internal calibration of substrate temperature. This behaviour is in contrast to aggregated data obtained under dynamic molecular beam epitaxy conditions, which show two regimes rather than a single Arrhenius-like phase boundary. The results are explained qualitatively by the atomistic kinetics in static versus dynamic conditions