Pressure-enabled phonon engineering in metals.

We present a combined first-principles and experimental study of the electrical resistivity in aluminum and copper samples under pressures up to 2 GPa. The calculations are based on first-principles density functional perturbation theory, whereas the experimental setup uses a solid media piston-cylinder apparatus at room temperature. We find that upon pressurizing each metal, the phonon spectra are blue-shifted and the net electron-phonon interaction is suppressed relative to the unstrained crystal. This reduction in electron-phonon scattering results in a decrease in the electrical resistivity under pressure, which is more pronounced for aluminum than for copper. We show that density functional perturbation theory can be used to accurately predict the pressure response of the electrical resistivity in these metals. This work demonstrates how the phonon spectra in metals can be engineered through pressure to achieve more attractive electrical properties.

Additive Lithography-Organic Monolayer Patterning Coupled with an Area-Selective Deposition.

The combination of area-selective deposition (ASD) with a patternable organic monolayer provides a versatile additive lithography platform, enabling the generation of a variety of nanoscale feature geometries. Stearate hydroxamic acid self-assembled monolayers (SAMs) were patterned with extreme ultraviolet (λ = 13.5 nm) or electron beam irradiation and developed with ASD to achieve line space patterns as small as 50 nm. Density functional theory was employed to aid in the synthesis of hydroxamic acid derivatives with optimized packing density to enhance the imaging contrast and improve dose sensitivity. Near-edge X-ray absorption fine structure spectroscopy and infrared spectroscopy reveal that the imaging mechanism is based on improved deposition inhibition provided by the cross-linking of the SAM to produce a more effective barrier during a subsequent deposition step. With patterned substrates composed of coplanar copper lines and silicon spacers, hydroxamic acids selectively formed monolayers on the metal portions and could undergo a pattern-wise exposure followed by ASD in the first combination of a patternable monolayer with ASD. This material system presents an additional capability compared to traditional ASD approaches that generally reflect a starting patterned surface. Furthermore, this bottoms-up additive approach to lithography may be a viable alternative to subtractive nanoscale feature generation.

Surface Initiated Polymer Thin Films for the Area Selective Deposition and Etching of Metal Oxides.

The area selective growth of polymers and their use as inhibiting layers for inorganic film depositions may provide a valuable self-aligned process for fabrication. Polynorbornene (PNB) thin films were grown from surface-bound initiators and show inhibitory properties against the atomic layer deposition (ALD) of ZnO and TiO2. Area selective control of the polymerization was achieved through the synthesis of initiators that incorporate surface-binding ligands, enabling their selective attachment to metal oxide features versus silicon dielectrics, which were then used to initiate surface polymerizations. The subsequent use of these films in an ALD process enabled the area selective deposition (ASD) of up to 39 nm of ZnO. In addition, polymer thickness was found to play a key role, where films that underwent longer polymerization times were more effective at inhibiting higher numbers of ALD cycles. Finally, while the ASD of a TiO2 film was not achieved despite blanket studies showing inhibition, the ALD deposition on polymer regions of a patterned film produced a different quality metal oxide and therefore altered its etch resistance. This property was exploited in the area selective etch of a metal feature. This demonstration of an area selective surface-grown polymer to enable ASD and selective etch has implications for the fabrication of both micro- and nanoscale features and surfaces.

Development of a Web-Enabled SVR-Based Machine Learning Platform and its Application on Modeling Transgene Expression Activity of Aminoglycoside-Derived Polycations.

OBJECTIVE: Support Vector Regression (SVR) has become increasingly popular in cheminformatics modeling. As a result, SVR-based machine learning algorithms, including Fuzzy-SVR and Least Square-SVR (LS-SVR) have been developed and applied in various research areas. However, at present, few downloadable packages or public-domain software are available for these algorithms. To address this need, we developed the Support vector regression-based Online Learning Equipment (SOLE) web tool (available at http://reccr.chem.rpi.edu/SOLE/index.html) as an online learning system to support predictive cheminformatics and materials informatics studies. RESULTS: In this work, we employed the SOLE system to model transgene expression efficacy of polymers obtained from aminoglycoside antibiotics, which allowed the results of several modeling approaches to be easily compared. All models had test set r2 of 0.96-0.98 and test set R2 of 0.79-0.84. Y-scrambling test showed the models were stable and not over-fitted. CONCLUSION: SOLE has a user-friendly interface and includes routine elements of performing QSAR/QSPR studies that can be applied in various research areas. It utilizes rational and sophisticated feature selection, model selection and model evaluation processes.

Band gap engineering in polymers through chemical doping and applied mechanical strain.

We report simulations based on density functional theory and many-body perturbation theory exploring the band gaps of common crystalline polymers including polyethylene, polypropylene and polystyrene. Our reported band gaps of 8.6 eV for single-chain polyethylene and 9.1 eV for bulk crystalline polyethylene are in excellent agreement with experiment. The effects of chemical doping along the polymer backbone and side-groups are explored, and the use mechanical strain as a means to modify the band gaps of these polymers over a range of several eV while leaving the dielectric constant unchanged is discussed. This work highlights some of the opportunities available to engineer the electronic properties of polymers with wide-reaching implications for polymeric dielectric materials used for capacitive energy storage.

Strain engineering the work function in monolayer metal dichalcogenides.

We use first-principles density functional theory to investigate the effect of both tensile and compressive strain on the work functions of various metal dichalcogenide monolayers. We find that for all six species considered, including MoS2, WS2, SnS2, VS2, MoSe2 and MoTe2, that compressive strain of up to 10% decreases the work function continuously by as much as 1.0 eV. Large enough tensile strain is also found to decrease the work function, although in some cases we observe an increase in the work function for intermediate values of tensile strain. This work function modulation is attributed to a weakening of the chalcogenide-metal bonds and an increase in total energy of each system as a function of strain. Values of strain which bring the metal atoms closer together lead to an increase in electrostatic potential energy, which in turn results in an increase in the vacuum potential level. The net effect on the work function can be explained in terms of the balance between the increases in the vacuum potential levels and Fermi energy.

Substrate-induced band gap renormalization in semiconducting carbon nanotubes.

The quasiparticle band gaps of semiconducting carbon nanotubes (CNTs) supported on a weakly-interacting hexagonal boron nitride (h-BN) substrate are computed using density functional theory and the GW Approximation. We find that the direct band gaps of the (7,0), (8,0) and (10,0) carbon nanotubes are renormalized to smaller values in the presence of the dielectric h-BN substrate. The decrease in the band gap is the result of a polarization-induced screening effect, which alters the correlation energy of the frontier CNT orbitals and stabilizes valence band maximum and conduction band minimum. The value of the band gap renormalization is on the order of 0.25 to 0.5 eV in each case. Accounting for polarization-induced band gap changes is crucial in comparing computed values with experiment, since nanotubes are almost always grown on substrates.