Electrostatic Selectivity of Volatile Organic Compounds Using Electrostatically Formed Nanowire Sensor.

For the past several decades, there is growing demand for the development of low-power gas sensing technology for the selective detection of volatile organic compounds (VOCs), important for monitoring safety, pollution, and healthcare. Here we report the selective detection of homologous alcohols and different functional groups containing VOCs using the electrostatically formed nanowire (EFN) sensor without any surface modification of the device. Selectivity toward specific VOC is achieved by training machine-learning based classifiers using the calculated changes in the threshold voltage and the drain-source on current, obtained from systematically controlled biasing of the surrounding gates (junction and back gates) of the field-effect transistors (FET). This work paves the way for a Si complementary metal-oxide-semiconductor (CMOS)-based FET device as an electrostatically selective sensor suitable for mass production and low-power sensing technology.

Biophotonics of Native Silk Fibrils.

Native silk fibroin (NSF) is a unique biomaterial with extraordinary mechanical and biochemical properties. These key characteristics are directly associated with the physical transformation of unstructured, soluble NSF into highly organized nano- and microscale fibrils rich in ß-sheet content. Here, it is shown that this NSF fibrillation process is accompanied by the development of intrinsic fluorescence in the visible range, upon near-UV excitation, a phenomenon that has not been investigated in detail to date. Here, the optical and fluorescence characteristics of NSF fibrils are probed and a route for potential applications in the field of self-assembled optically active biomaterials and systems is explored. In particular, it is demonstrated that NSF can be structured into autofluorescent microcapsules with a controllable level of ß-sheet content and fluorescence properties. Furthermore, a facile and efficient fabrication route that permits arbitrary patterns of NSF microcapsules to be deposited on substrates under ambient conditions is shown. The resulting fluorescent NSF patterns display a high level of photostability. These results demonstrate the potential of using native silk as a new class of biocompatible photonic material.

Control of the Intrinsic Sensor Response to Volatile Organic Compounds with Fringing Electric Fields.

The ability to control surface-analyte interaction allows tailoring chemical sensor sensitivity to specific target molecules. By adjusting the bias of the shallow p-n junctions in the electrostatically formed nanowire (EFN) chemical sensor, a multiple gate transistor with an exposed top dielectric layer allows tuning of the fringing electric field strength (from 0.5 × 107 to 2.5 × 107 V/m) above the EFN surface. Herein, we report that the magnitude and distribution of this fringing electric field correlate with the intrinsic sensor response to volatile organic compounds. The local variations of the surface electric field influence the analyte-surface interaction affecting the work function of the sensor surface, assessed by Kelvin probe force microscopy on the nanometer scale. We show that the sensitivity to fixed vapor analyte concentrations can be nullified and even reversed by varying the fringing field strength, and demonstrate selectivity between ethanol and n-butylamine at room temperature using a single transistor without any extrinsic chemical modification of the exposed SiO2 surface. The results imply an electric-field-controlled analyte reaction with a dielectric surface extremely compelling for sensitivity and selectivity enhancement in chemical sensors.

Materials Informatics: Statistical Modeling in Material Science.

Material informatics is engaged with the application of informatic principles to materials science in order to assist in the discovery and development of new materials. Central to the field is the application of data mining techniques and in particular machine learning approaches, often referred to as Quantitative Structure Activity Relationship (QSAR) modeling, to derive predictive models for a variety of materials-related "activities". Such models can accelerate the development of new materials with favorable properties and provide insight into the factors governing these properties. Here we provide a comparison between medicinal chemistry/drug design and materials-related QSAR modeling and highlight the importance of developing new, materials-specific descriptors. We survey some of the most recent QSAR models developed in materials science with focus on energetic materials and on solar cells. Finally we present new examples of material-informatic analyses of solar cells libraries produced from metal oxides using combinatorial material synthesis. Different analyses lead to interesting physical insights as well as to the design of new cells with potentially improved photovoltaic parameters.

A combined computational and experimental investigation of Mg doped α-Fe2O3.

In the current work, pristine α-Fe2O3 metal oxide was doped with Mg in an attempt to modulate its electronic properties. To this end, we employed an experimental high throughput strategy, including scanning XRD and optical spectroscopy, which were complimented by atomistic density functional theory (DFT) calculations. The combined study reveals that at Mg/Fe atomic ratios up to ∼1/3, the bandgaps of the hematite-Mg composite materials are similar to that of the pure material. The observed bandgaps are rationalized by electronic band structure and density of states calculations. Additional rationale for the similar bandgaps in pure and doped hematite is provided by topological Bader charge analyses, which indicate that the Mg and Fe ions in the hematite matrix have similar partial atomic charges. Nonetheless, the small charge density difference between the Mg and Fe ions induces a slight spin polarization on both oxygen and Fe ions, resulting in changes in the band edges. Further charge density analyses, using charge density maps and chemical-bonding analyses with the crystal orbital Hamiltonian population scheme, indicate that Mg forms ionic bonds with the neighboring oxygen atoms. This change from iron-oxygen covalent bonds to a more ionic nature for magnesium-oxygen bonds is probably responsible for the reduction observed in the computed bulk modulus of α-Mg(0.17)Fe(1.83)O3 (193 GPa) compared to α-Fe2O3 (202 GPa).

Utilizing pulsed laser deposition lateral inhomogeneity as a tool in combinatorial material science.

Pulsed laser deposition (PLD) is widely used in combinatorial material science, as it enables rapid fabrication of different composite materials. Nevertheless, this method was usually limited to small substrates, since PLD deposition on large substrate areas results in severe lateral inhomogeneity. A few technical solutions for this problem have been suggested, including the use of different designs of masks, which were meant to prevent inhomogeneity in the thickness, density, and oxidation state of a layer, while only the composition is allowed to be changed. In this study, a possible way to take advantage of the large scale deposition inhomogeneity is demonstrated, choosing an iron oxide PLD-deposited library with continuous compositional spread (CCS) as a model system. An Fe2O3-Nb2O5 library was fabricated using PLD, without any mask between the targets and the substrate. The library was measured using high-throughput scanners for electrical, structural, and optical properties. A decrease in electrical resistivity that is several orders of magnitude lower than pure α-Fe2O3 was achieved at ∼20% Nb-O (measured at 47 and 267 °C) but only at points that are distanced from the center of the PLD plasma plume. Using hierarchical clustering analysis, we show that the PLD inhomogeneity can be used as an additional degree of freedom, helping, in this case, to achieve iron oxide with much lower resistivity.

Four-point probe electrical resistivity scanning system for large area conductivity and activation energy mapping.

The electrical properties of metal oxides play a crucial role in the development of new photovoltaic (PV) systems. Here we demonstrate a general approach for the determination and analysis of these properties in thin films of new metal oxide based PV materials. A high throughput electrical scanning system, which facilitates temperature dependent measurements at different atmospheres for highly resistive samples, was designed and constructed. The instrument is capable of determining conductivity and activation energy values for relatively large sample areas, of about 72 × 72 mm(2), with the implementation of geometrical correction factors. The efficiency of our scanning system was tested using two different samples of CuO and commercially available Fluorine doped tin oxide coated glass substrates. Our high throughput tool was able to identify the electrical properties of both resistive metal oxide thin film samples with high precision and accuracy. The scanning system enabled us to gain insight into transport mechanisms with novel compositions and to use those insights to make smart choices when choosing materials for our multilayer thin film all oxide photovoltaic cells.