Metastable Atomic Layer Deposition: 3D Self-Assembly toward Ultradark Materials

Black body materials are promising candidates to meet future energy demands, as they are able to harvest energy from the total bandwidth of solar radiation. Here, we report on high-absorption near-blackbody-like structures (>98% for a wide solar spectrum range from 220 to 2500 nm) consisting of a silica scaffold and Ag nanoparticles with a layer thickness below 10 μm, fabricated using metastable atomic layer deposition (MS-ALD). Several effects contribute collectively and in a synergistic manner to the ultrahigh absorption, including the pronounced heterogeneity of the nanoparticles in size and shape, particle plasmon hybridization, and the trapping of omnidirectionally scattered light in the 3D hierarchical hybrid structures. We propose that, in the future, MS-ALD needs to be considered as a simple and promising method to fabricate blackbody materials with excellent broadband absorption.

Time-Resolved Study of Site-Specific Corrosion in a Single Crystalline Silver Nanoparticle

We followed over 24 h a corrosion process in monocrystalline triangular-shaped nanoparticles at a single-particle level by atomic force microscopy and optical spectroscopy techniques under ambient laboratory conditions. The triangular-shaped form of the particles was selected, because the crystallographic orientation of the particles is well defined upon their deposition on a substrate. We observed that the particles already start to alter within this time frame. Surprisingly, the corrosion starts predominantly from the tips of the particles and it creates within few hours large protrusions, which strongly suppress the plasmon character of the particles. These observations support the crystallographic model of these particles consisting of a high-defect hexagonal closed packed layer, and they could help material scientists to design more stable silver nanoparticles. Moreover, this described technique can be used to reveal kinetics of the corrosion in the nanoscale of other materials.

Plasmonic Nanosensor Array for Multiplexed DNA-based Pathogen Detection

In this research we introduce a plasmonic nanoparticle based optical biosensor for monitoring of molecular binding events. The sensor utilizes spotted gold nanoparticle arrays as sensing platform. The nanoparticle spots are functionalized with capture DNA sequences complementary to the analyte (target) DNA. Upon incubation with the target sequence, it will bind on the respectively complementary functionalized particle spot. This binding changes the local refractive index, which is detected spectroscopically as the resulting changes of the localized surface plasmon resonance (LSPR) peak wavelength. In order to increase the signal, a small gold nanoparticle label is introduced. The binding can be reversed using chemical means (10 mM HCl). It is demonstrated that multiplexed detection and identification of several fungal pathogen DNA sequences subsequently on one sensor array are possible by this approach.

AFM-Based Probing of the Flexibility and Surface Attachment of Immobilized DNA Origami

The flexible and precise immobilization of self-organizing DNA nanostructures represents a key step in the integration of DNA-based material for potential electronic or sensor applications. However, the involved processes have still not been well studied and are not yet fully understood. Thus, we investigated the potential for the mechanical manipulation of DNA origami by atomic force microscopy (AFM) in order to study the interaction between intramolecular flexibility and surface-attachment forces. AFM is particularly suitable for nanoscale manipulation. Previous studies showed the potential for pushing, bending, and cutting double-stranded DNA (dsDNA) with an AFM tip. Understanding the involved parameters may enable control over different processes such as nanointegration, precise cutting, and stretching of preassembled DNA origami. We demonstrate the defined manipulation and flexibility of DNA origami immobilized on mica in the nanometer range: controlled cutting, folding, and stretching as a function of the magnesium concentration.

Plasmon response evaluation based on image-derived arbitrary nanostructures

The optical response of realistic 3D plasmonic substrates composed of randomly shaped particles of different size and interparticle distance distributions in addition to nanometer scale surface roughness is intrinsically challenging to simulate due to computational limitations. Here, we present a Finite Element Method (FEM)-based methodology that bridges in-depth theoretical investigations and experimental optical response of plasmonic substrates composed of such silver nanoparticles. Parametrized scanning electron microscopy (SEM) images of surface enhanced Raman spectroscopy (SERS) active substrate and tip-enhanced Raman spectroscopy (TERS) probes are used to simulate the far-and near-field optical response. Far-field calculations are consistent with experimental dark field spectra and charge distribution images reveal for the first time in arbitrary structures the contributions of interparticle hybridized modes such as sub-radiant and super-radiant modes that also locally organize as basic units for Fano resonances. Near-field simulations expose the spatial position-dependent impact of hybridization on field enhancement. Simulations of representative sections of TERS tips are shown to exhibit the same unexpected coupling modes. Near-field simulations suggest that these modes can contribute up to 50% of the amplitude of the plasmon resonance at the tip apex but, interestingly, have a small effect on its frequency in the visible range. The band position is shown to be extremely sensitive to particle nanoscale roughness, highlighting the necessity to preserve detailed information at both the largest and the smallest scales. To the best of our knowledge, no currently available method enables reaching such a detailed description of large scale realistic 3D plasmonic systems.

Electrically Excited Plasmonic Nanoruler for Biomolecule Detection

Plasmon-based sensors are excellent tools for a label-free detection of small biomolecules. An interesting group of such sensors are plasmonic nanorulers that rely on the plasmon hybridization upon modification of their morphology to sense nanoscale distances. Sensor geometries based on the interaction of plasmons in a flat metallic layer together with metal nanoparticles inherit unique advantages but need a special optical excitation configuration that is not easy to miniaturize. Herein, we introduce the concept of nanoruler excitation by direct, electrically induced generation of surface plasmons based on the quantum shot noise of tunneling currents. An electron tunneling junction consisting of a metal-dielectric-semiconductor heterostructure is directly incorporated into the nanoruler basic geometry. With the application of voltage on this modified nanoruler, the plasmon modes are directly excited without any additional optical component as a light source. We demonstrate via several experiments that this electrically driven nanoruler possesses similar properties as an optically exited one and confirm its sensing capabilities by the detection of the binding of small biomolecules such as antibodies. This new sensing principle could open the way to a new platform of highly miniaturized, integrated plasmonic sensors compatible with monolithic integrated circuits.

Impact of axial root growth angles on nitrogen acquisition in maize depends on environmental conditions

BACKGROUNDS AND AIMS

Crops with reduced requirement for nitrogen (N) fertilizer would have substantial benefits in developed nations, while improving food security in developing nations. This study employs the functional structural plant model SimRoot to test the hypothesis that variation in the growth angles of axial roots of maize (Zea mays L.) is an important determinant of N capture.

METHODS

Six phenotypes contrasting in axial root growth angles were modelled for 42 d at seven soil nitrate levels from 10 to 250 kg ha(-1) in a sand and a silt loam, and five precipitation regimes ranging from 0·5× to 1·5× of an ambient rainfall pattern. Model results were compared with soil N measurements of field sites with silt loam and loamy sand textures.

KEY RESULTS

For optimal nitrate uptake, root foraging must coincide with nitrate availability in the soil profile, which depends on soil type and precipitation regime. The benefit of specific root architectures for efficient N uptake increases with decreasing soil N content, while the effect of soil type increases with increasing soil N level. Extreme root architectures are beneficial under extreme environmental conditions. Extremely shallow root systems perform well under reduced precipitation, but perform poorly with ambient and greater precipitation. Dimorphic phenotypes with normal or shallow seminal and very steep nodal roots performed well in all scenarios, and consistently outperformed the steep phenotypes. Nitrate uptake increased under reduced leaching conditions in the silt loam and with low precipitation.

CONCLUSIONS

Results support the hypothesis that root growth angles are primary determinants of N acquisition in maize. With decreasing soil N status, optimal angles resulted in 15-50 % greater N acquisition over 42 d. Optimal root phenotypes for N capture varied with soil and precipitation regimes, suggesting that genetic selection for root phenotypes could be tailored to specific environments.

Electrical tomography using atomic force microscopy and its application towards carbon nanotube-based interconnects

The fabrication and integration of low-resistance carbon nanotubes (CNTs) for interconnects in future integrated circuits requires characterization techniques providing structural and electrical information at the nanometer scale. In this paper we present a slice-and-view approach based on electrical atomic force microscopy. Material removal achieved by successive scanning using doped ultra-sharp full-diamond probes, manufactured in-house, enables us to acquire two-dimensional (2D) resistance maps originating from different depths (equivalently different CNT lengths) on CNT-based interconnects. Stacking and interpolating these 2D resistance maps results in a three-dimensional (3D) representation (tomogram). This allows insight from a structural (e.g. size, density, distribution, straightness) and electrical point of view simultaneously. By extracting the resistance evolution over the length of an individual CNT we derive quantitative information about the resistivity and the contact resistance between the CNT and bottom electrode.

Capillary pressure in a porous medium with distinct pore surface and pore volume fractal dimensions

The relationship between capillary pressure and saturation in a porous medium often exhibits a power-law dependence. The physical basis for this relation has been substantiated by assuming that capillary pressure is directly related to the pore radius. When the pore space of a medium exhibits fractal structure this approach results in a power-law relation with an exponent of 3-D(v), where D(v) is the pore volume fractal dimension. However, larger values of the exponent than are realistically allowed by this result have long been known to occur. Using a thermodynamic formulation for equilibrium capillary pressure we show that the standard result is a special case of the more general exponent (3-D(v))(3-D(s)) where D(s) is the surface fractal dimension of the pores. The analysis reduces to the standard result when D(s)=2, indicating a Euclidean relationship between a pore's surface area and the volume it encloses, and allows for a larger value for the exponent than the standard result when D(s)>2 .

Influence of image resolution and evaluation algorithm on estimates of the lacunarity of porous media

In recent years, experience has demonstrated that the classical fractal dimensions are not sufficient to describe uniquely the interstitial geometry of porous media. At least one additional index or dimension is necessary. Lacunarity, a measure of the degree to which a data set is translationally invariant, is a possible candidate. Unfortunately, several approaches exist to evaluate it on the basis of binary images of the object under study, and it is unclear to what extent the lacunarity estimates that these methods produce are dependent on the resolution of the images used. In the present work, the gliding-box algorithm of Allain and Cloitre [Phys. Rev. A 44, 3552 (1991)] and two variants of the sandbox algorithm of Chappard et al. [J. Pathol. 195, 515 (2001)], along with three additional algorithms, are used to evaluate the lacunarity of images of a textbook fractal, the Sierpinski carpet, of scanning electron micrographs of a thin section of a European soil, and of light transmission photographs of a Togolese soil. The results suggest that lacunarity estimates, as well as the ranking of the three tested systems according to their lacunarity, are affected strongly by the algorithm used, by the resolution of the images to which these algorithms are applied, and, at least for three of the algorithms (producing scale-dependent lacunarity estimates), by the scale at which the images are observed. Depending on the conditions under which the estimation of the lacunarity is carried out, lacunarity values range from 1.02 to 2.14 for the three systems tested, and all three of the systems used can be viewed alternatively as the most or the least "lacunar." Some of this indeterminacy and dependence on image resolution is alleviated in the averaged lacunarity estimates yielded by Chappard et al.'s algorithm. Further research will be needed to determine if these lacunarity estimates allow an improved, unique characterization of porous media.