Abstract: This work reports the study of photoconductivity and visible light activated room temperature gas sensors properties of nanocrystalline ZnO thick films sensitized with colloidal CdSe quantum dots (QDs). Nanocrystalline zinc oxide (ZnO) was synthesized by the precipitation method. Colloidal CdSe quantum dots were obtained by high temperature colloidal synthesis. Sensitization was effectuated by three different procedures including direct adsorption of CdSe QDs stabilized with oleic acid on ZnO surface, anchoring to the ZnO surface through a bifunctional molecule of mercaptopropionic acid (MPA), and coating of CdSe QDs with a monolayer of MPA with subsequent adsorption on ZnO surface. Sensor measurements demonstrated that obtained QD CdSe/ZnO nanocomposites can be used for NO2 detection under visible (green) light illumination at room temperature without any thermal heating. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: The development of sensor materials of which gas sensitivity activates under light illumination is of great importance for the design of portable gas analyzers with low power consumption. In the present work a ZnO/CsPbBr3 nanocomposite based on nanocrystalline ZnO and colloidal cubic-shaped perovskite CsPbBr3 nanocrystals (NCs) capped by oleic acide and oleylamine was synthesized. The individual materials and obtained nanocomposite are characterized by x-ray diffraction, low-temperature nitrogen adsorption, x-ray photoelectron spectroscopy, high angle annular dark field scanning transmission electron microscopy with energy-dispersive Xray spectroscopy mapping and UV-vis absorption spectroscopy. The spectral dependence of the photoconductivity of the ZnO/CsPbBr3 nanocomposite reveals a well-defined peak that strongly correlates with the its optical absorption spectrum. The nanocomposite ZnO/CsPbBr3 shows enhanced photoresponse under visible light illumination (lambda(max) = 470 nm, 8 mW/cm(2)) in air, oxygen and argone, compared with pure nanocrystalline ZnO. Under periodic illumination in the temperature range of 25-100 degrees C, the ZnO/CsPbBr3 nanocomposite shows a sensor response to 0.5-3.0 ppm NO2, unlike pure nanocrystalline ZnO matrix, which demonstrates sensor sensitivity to NO2 under the same conditions above 100 degrees C. The effects of humidity on the sensor signal and photoresponse are also discussed.

Abstract: Extensive use of titanium alloys is partly hindered by a lack of ductility, strain hardening, and fracture toughness. Recently, several beta -metastable titanium alloys were designed to simultaneously activate both transformation-induced plasticity and twinning-induced plasticity effects, resulting in significant improvements to their strain hardening capacity and resistance to plastic localization. Here, we report an ultra-large fracture resistance in a Ti-12Mo alloy (wt.%), that results from a high resistance to damage nucleation, with an unexpected fracture phenomenology under quasi-static loading. Necking develops at a large uniform true strain of 0.3 while fracture initiates at a true fracture strain of 1.0 by intense through-thickness shear within a thin localized shear band. Transmission electron microscopy reveals that dynamic recrystallization occurs in this band, while local partial melting is observed on the fracture surface. Shear band temperatures of 1250-2450 degrees C are estimated by the fusible coating method. The reported high ductility combined to the unconventional fracture process opens alternative avenues toward Ti alloys toughening. Specific titanium alloys combine transformation-induced plasticity and twinning-induced plasticity for improved work hardening. Here, the authors show that these alloys also have an ultra-large fracture resistance and an unexpected fracture mechanism via dynamic recrystallization and local melting in a deformation band.

Abstract: Solar energy plays an important role in solving serious environmental
problems and meeting the high energy demand. However, the lack of suitable
materials hinders further progress of this technology. Here, we present the largest
inorganic solar cell material search till date using density functional theory (DFT) and
machine-learning approaches. We calculated the spectroscopic limited maximum
efficiency (SLME) using the Tran−Blaha-modified Becke−Johnson potential for 5097
nonmetallic materials and identified 1997 candidates with an SLME higher than 10%,
including 934 candidates with a suitable convex-hull stability and an effective carrier
mass. Screening for two-dimensional-layered cases, we found 58 potential materials
and performed G0W0 calculations on a subset to estimate the prediction uncertainty. As the above DFT methods are still computationally expensive, we developed a high accuracy machine-learning model to prescreen efficient materials and applied it to over a million materials. Our results provide a general framework and universal strategy for the design of high-efficiency solar
cell materials. The data and tools are publicly distributed at: https://www.ctcms.nist.gov/~knc6/JVASP.html, https://www.
ctcms.nist.gov/jarvisml/, https://jarvis.nist.gov/, and https://github.com/usnistgov/jarvis.

Abstract: Immunoassays exploiting magnetization dynamics of magnetic nanoparticles are highly promising for mix-and-measure, quantitative, and point-of-care diagnostics. However, how single-core magnetic nanoparticles can be employed to reduce particle concentration and concomitantly maximize assay sensitivity is not fully understood. Here, we design monodisperse Néel and Brownian relaxing magnetic nanocubes (MNCs) of different sizes and compositions. We provide insights into how to decouple physical properties of these MNCs to achieve ultrahigh sensitivity. We find that tri-component-based Zn0.06 Co0.80Fe2.14 O4 particles, with out-of-phase to initial magnetic susceptibility χ /χ ratio of 0.47 out of 0.50 for magnetically blocked ideal particles, show the ultrahigh magnetic sensitivity by providing rich magnetic particle spectroscopy (MPS) harmonics spectrum despite bearing lower saturation magnetization than di-component Zn0.1Fe2.9O4 having high saturation magnetization. The Zn0.06Co0.80Fe2.14O4 MNCs, coated with catechol-based polyethylene glycol ligands, measured by our benchtop MPS show three orders of magnitude better particle LOD than that of commercial nanoparticles of comparable size.

Abstract: A hitherto unknown composition is highlighted in the red and black inks preserved on ancient Egyptian papyri from the Roman period (circa 100 to 200 CE). Synchrotron-based macro-X-ray fluo-rescence (XRF) mapping brings to light the presence of iron (Fe) and lead (Pb) compounds in the majority of the red inks inscribed on 12 papyrus fragments from the Tebtunis temple library. The iron-based compounds in the inks can be assigned to ocher, notably due to the colocalization of Fe with aluminum, and the detection of hematite (Fe2O3) by micro-X-ray diffraction. Using the same techniques together with micro-Fourier transform infrared spectroscopy, Pb is shown to be associated with fatty acid phosphate, sulfate, chloride, and carboxylate ions. Moreover, microXRF maps reveal a peculiar distribution and colocalization of Pb, phosphorus (P), and sulfur (S), which are present at the micrometric scale resembling diffused “coffee rings” surrounding the ocher particles imbedded in the red letters, and at the submicrometric scale concentrated in the papyrus cell walls. A similar Pb, P, and S composition was found in three black inks, suggesting that the same lead components were employed in the manufacture of carbon-based inks. Bearing in mind that pigments such as red lead (Pb3O4) and lead white (hydrocerussite [Pb-3(CO3)(2)(OH)(2)] and/or cerussite [PbCO3]) were not detected, the results presented here suggest that the lead compound in the ink was used as a drier rather than as a pigment. Accordingly, the study calls for a reassessment of the composition of lead-based components in ancient Mediterranean pigments.

Abstract: Sustainable Materials Management (SMM) strategies, such as reuse, recycling and energy recovery aim, to capture more of the embedded resource or material value in products and waste streams. Reuse, recycling and energy recovery are existing activities in every society but they are poorly reflected in official statistics. Reaching higher levels of reuse, recycling and energy recovery may provide economic and environmental opportunities (i.e., in terms of GDP, jobs, reduced impacts), but not all options will have a net win-win-win property in practice, as they reduce the need for producing new commodities. In open economies, many primary resources, components and products are imported from abroad, and many goods produced are exported abroad. This paper describes a top-down methodology for estimating the substitution potential of intensifying specific SMM-strategies and material efficiency strategies. We combined both regional and multi-regional EE-IO (environmentally extended input-output) models to link industrial sectors to SMM-strategies. Our method enables us to compare the different SMM and material efficiency strategies in terms of the maximum available budgets for reaching them on a break even basis, maximum savings in global warming emissions and substituted employment effects, both through a regional and global perspective. We add a case on Flanders (Northern region in Belgium) to illustrate the methodology. Flanders is currently developing a policy for SMM. Selecting new regional actions for a Sustainable Materials Management policy can benefit from a good understanding of the international entangled value chains. It is important to understand how much of the chain is within reach of domestic policies and also to assess the consequences in terms of potential winners and losers, regarding GDP, jobs and environmental impacts, both domestically and abroad. We illustrated the potential outcomes for Flanders from four generic SMM-strategies: energy recovery, food waste prevention, recycling and reuse. From a strict regional self-interest perspective, it is preferable to substitute foreign value chains with local economic activities. Reuse creates by far the largest budget for new activities to realize the strategy (31.2% of Flemish GDP compared to 8.3% for food waste prevention, 6.2% for energy recovery and 4.2% for recycling). All four strategies have similar and significant potentials to reduce greenhouse gas emissions. However, food waste prevention and reuse have higher potentials to reduce Flemish territorial GHG-emissions. From a pure Flemish employment perspective, the energy recovery and recycling strategies could replace the fewest Flemish jobs, and from a global perspective, all strategies most likely imply losses of jobs abroad. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: The effect of the electric field on an exciton confined in a pair of vertically coupled quantum dots is studied. We use a single-band approximation and a parabolic model potential. As a result of these idealizations, we obtain a numerically solvable model, which is used to describe the influence of the electron-hole interaction on the Stark effect for the lowest-energy photo luminescence lines. We show that for intermediate tunnel coupling between the dots this interaction leads to an anomalous Stark effect with an essential deviation of the recombination energy from the usual quadratic dependence on the electric field. (c) 2004 Elsevier B.V. All rights reserved.

Abstract: Herein, an isothermal padlock probe-based assay for the simple and portable detection of pathogens coupled with a glucose oxidase (GOx)-based electrochemical readout is reported. Infectious diseases remain a constant threat on a global scale, as in recurring pandemics. Rapid and portable diagnostics hold the promise to tackle the spreading of diseases and decentralising healthcare to point-of-care needs. Ebola, a hypervariable RNA virus causing fatalities of up to 90% for recent outbreaks in Africa, demands immediate attention for bedside diagnostics. The design of the demonstrated assay consists of a rolling circle amplification (RCA) technique, responsible for the generation of nucleic acid amplicons as RCA products (RCPs). The RCPs are generated on magnetic beads (MB) and subsequently, connected via streptavidin-biotin bonds to GOx. The enzymatic catalysis of glucose by the bound GOx allows for an indirect electrochemical measurement of the DNA target. The RCPs generated on the surface of the MB were confirmed by scanning electron microscopy, and among other experimental conditions such as the type of buffer, temperature, concentration of GOx, sampling and measurement time were evaluated for the optimum electrochemical detection. Accordingly, 125 μg mL−1 of GOx with 5 mM glucose using phosphate buffer saline (PBS), monitored for 1 min were selected as the ideal conditions. Finally, we assessed the analytical performance of the biosensing strategy by using clinical samples of Ebola virus from patients. Overall, this work provides a proof-of-concept bioassay for simple and portable molecular diagnostics of emerging pathogens using electrochemical detection, especially in resource-limited settings.

Abstract: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic‐resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state‐of‐the‐art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark‐field scanning transmission electron microscopy enables the acquisition of ten high‐resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allows resolving the real‐time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions.