Edible Electronics: Biocompatible and Biodegradable Materials for Organic Field‐Effect Transistors (Adv. Funct. Mater. 23/2010)

Biocompatible‐ingestible electronic circuits and capsules for medical diagnosis and monitoring are currently based on traditional silicon technology. Organic electronics has huge potential for developing biodegradable, biocompatible, bioresorbable, or even metabolizable products. An ideal pathway for such electronic devices involves fabrication with materials from nature, or materials found in common commodity products. Transistors with an operational voltage as low as 4–5 V, a source drain current of up to 0.5 μA and an on‐off ratio of 3–5 orders of magnitude have been fabricated with such materials. This work comprises steps towards environmentally safe devices in low‐cost, large volume, disposable or throwaway electronic applications, such as in food packaging, plastic bags, and disposable dishware. In addition, there is significant potential to use such electronic items in biomedical implants.     

Wear behavior of TiB<Subscript>2</Subscript> inoculated 20Cr–3Mo–4C high chromium white cast irons

FeTi, B₂O₃, Al, and FeW particulates, approximately 40–60 μm in size, were mixed in stoichiometric ratio and sintered at 1,200 °C. The sintered particulates were added as 5 wt% to molten high chromium white cast iron over 50 C-deg above the melting temperature, and stirred at 1,000 rpm. The samples were investigated in three groups: (1) high Cr white cast iron inoculated by the particulates sintered from Al–FeTi–B₂O₃ particulates; (2) high Cr white cast iron inoculated by the sintered particulates derived from Al–FeTi, B₂O₃, and FeW particulates; and (3) specimens of the second group that were subsequently homogenized. The microhardness of ceramic particulates was measured as 2,800–3,400 HV₁₀. The effect of sintered particulate volume fraction on the abrasive wear resistance of the high chromium white cast iron was determined. The wear resistance and hardness of the composites improved significantly as a result of particulate inoculation. The application of the homogenization heat treatment to the inoculated samples produced a microstructure having homogeneously distributed particulates.     

Alkali activation of a slag at ambient and elevated temperatures

Strength development of alkali activated slag (AAS) mortars, activated using alkali hydroxide and sodium silicate, was investigated at room and elevated temperatures. Heat evolution at room temperature was measured using isothermal calorimetry. Important differences were observed between critical activation parameters. Heat cured specimens gain strength rapidly, humid oven conditions being favorable, but given sufficient time room temperature curing yields comparable strengths. Both activators are needed for high strength at room temperature, NaOH solution is more critical and its concentration greatly influences strength. At 80 °C however, sodium silicate is essential and even sufficient. KOH is more effective than NaOH at 80 °C, but not at room temperature. Lower water-to-slag ratios give higher strength at early ages. AAS hydration evolves less heat than Portland cement hydration. Time to significant strength gain of mixtures can be predicted using their time and heat evolution at setting. Twenty eight-day strength of AAS mortars is roughly related to total evolved heat and increases nearly linearly with the amount of NaOH activator for fixed water glass content.     

Photovoltaic characterization of hybrid solar cells using surface modified TiO(2) nanoparticles and poly(3-hexyl)thiophene

We report on the photovoltaic performance of bulk heterojunction solar cells using novel nanoparticles of 6-palmitate ascorbic acid surface modified TiO(2) as an electron acceptor embedded into the donor poly(3-hexyl)thiophene (P3HT) matrix. Devices were fabricated by using P3HT with varying amounts of red TiO(2) nanoparticles (1:1, 1:2, 1:3?w-w ratio). The devices were characterized by measuring current-voltage characteristics under simulated AM 1.5 conditions. Incident photon to current efficiency (IPCE) was spectrally resolved. The nanoscale morphology of such organic/inorganic hybrid blends was also investigated using atomic force microscopy (AFM).     

Secrecy outage probability of inter‐vehicular cognitive radio networks

Herein, we consider an underlay cognitive radio network (CRN) where mobile secondary user wishes to transmit a confidential information to the secondary destination in the presence of an illegitimate eavesdropper which is trying to steal the classified message signal. The proposed scenario can be viable for a secondary safety task force working with a primary regiment, which wishes to transmit the confidential information to the commander while an eavesdropper is trying to intercept the classified information. In the analysis, two novel power allocation methods are considered by assuming perfect and limited feedback channels of the primary network, and for both methods, exact and asymptotic expressions of secrecy outage probability (SOP) are derived for N*Nakagami‐m fading channels which are used to model fading channels such as mobile‐to‐mobile/vehicle‐to‐vehicle communication systems where the nodes are moving into a rich scattering environment. We further verified our analytic results through Monte‐Carlo simulations. It is shown from the numerical results that the cascading degree of the channels has a worsening effect on the secrecy outage performance of the CRN systems.     

Coupled nonparametric shape and moment-based intershape pose priors for multiple basal ganglia structure segmentation

This paper presents a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. In biological tissues, such as the human brain, neighboring structures exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and intershape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance images. We present a set of 2-D and 3-D experiments as well as a quantitative performance analysis. In addition, we perform a comparison to several existent segmentation methods and demonstrate the improvements provided by our approach in terms of segmentation accuracy.     

Site‐Specific Placement of Au Nanoparticles on Chemical Nanopatterns Prepared by Molecular Transfer Printing Using Block‐Copolymer Films

Inexpensive, large area patterning of ex‐situ synthesized metallic nanoparticles (NPs) at the nanoscale may enable many technologies including plasmonics, nanowire growth, and catalysis. Here, site‐specific localization of Au NPs onto nanoscale chemical patterns of polymer brushes is investigated. In this approach, patterns of hydroxyl‐terminated poly(styrene) brushes are transferred from poly(styrene‐block‐methyl methacrylate) (PS‐b‐PMMA) block copolymer films onto a replica substrate via molecular transfer printing, and the remaining areas are filled with hydroxyl‐terminated poly(2‐vinyl pyridine) (P2VP‐OH) brushes. Citrate‐stabilized Au NPs (13 nm) selectively bind to P2VP‐OH functionalized regions and the quality of the resulting assemblies depends on high chemical contrast in the patterned brushes. Minimization of the interpenetration of P2VP‐OH chains into PS brushes during processing is the key for achieving high chemical contrast. Large area hexagonal arrays of single Au NPs with a placement accuracy of 3.4 nm were obtained on patterns (～20 nm spots, ～40 nm pitch) derived from self‐assembled cylinder‐forming PS‐b‐PMMA films. Linear arrays of Au NPs were generated on patterns (40 nm lines, 80nm pitch) derived from lamellae‐forming PS‐b‐PMMA that had been directed to assemble on lithographically defined masters.     

Automatic diagnosis of ureteral stone and degree of hydronephrosis with proposed convolutional neural network,RelieF, and gradient-weighted class activation mapping based deep hybrid model

Urinary system stone disease is a common disease group all over the world. Ureteral stones constitute 20% of all urinary system stones. Ureteral stones are important because they can cause hydronephrosis and related renal parenchymal damage in the kidneys. In the study, a hybrid model was developed to detect hydronephrosis and ureteral stones from kidney images. In the developed model, heat maps of the original images were obtained by using gradient-weighted class activation mapping (Grad-CAM) technology. Then, feature maps were extracted from both the original and heatmap datasets using the Efficientnetb0 architecture. Extracted feature maps were concatenated using a multimodal fusion technique. In this way, different features of an image are obtained. This has a positive effect on the performance of the model. The Relief dimension reduction technique was used to eliminate unnecessary features in the obtained feature map so that the proposed model can work faster and more effectively. Finally, the optimized feature map is classified in the support vector machine (SVM) classifier. To compare the performance of the proposed hybrid model, results were obtained with 8 state-of-the-art models accepted in the literature. Among these models, the highest accuracy value was achieved in the Efficientnetb0 architecture with 67.98%, whereas the accuracy of the proposed hybrid model was 91.1%. This value indicates that the proposed model can be used for HUN diagnosis.     

Synthesis of Fe–4.6?wt% B alloy via electro-deoxidation of mixed oxides

Fe–4.6 wt% B alloy was synthesized via electro-deoxidation of the mixed oxide precursor. The oxides, Fe₂O₃ and B₂O₃, mixed in suitable proportions were sintered at 900 °C yielding pellets with a two-phase structure; Fe₂O₃ and Fe₃BO₆. The sintered pellets, connected as cathode, were then electro-deoxidized in molten CaCl₂ or in CaCl₂–NaCl eutectic, against a graphite anode at 3.1 V. The electrolysis at 850 °C has successfully yielded a powder mixture of Fe and Fe₂B. Sequence of changes during the electrolysis was followed by interrupted experiments conducted at 850 °C. This has shown that iron is extracted quite early during the electrolysis through the depletion of oxygen from the starting oxide; Fe₂O₃, forming the other iron oxides in the process. Boron follows a more complicated route. Fe₃BO₆, the initial boron-bearing phase, was depleted in the early stages due to its reaction with molten salt. This gave rise to the formation of calcium borate. Boron was extracted from calcium borate in later stages of electrolysis, which appeared to have reacted in situ with the iron forming compound Fe₂B. An erratum to this article can be found at     

Controlling Nanoscale Thermal Expansion of Monolayer Transition Metal Dichalcogenides by Alloy Engineering

2D materials, such as transition metal dichalcogenides (TMDs), graphene, and boron nitride, are seen as promising materials for future high power/high frequency electronics. However, the large difference in the thermal expansion coefficient (TEC) between many of these 2D materials could impose a serious challenge for the design of monolayer‐material‐based nanodevices. To address this challenge, alloy engineering of TMDs is used to tailor their TECs. Here, in situ heating experiments in a scanning transmission electron microscope are combined with electron energy‐loss spectroscopy and first‐principles modeling of monolayer Mo_1?xW_xS₂ with different alloying concentrations to determine the TEC. Significant changes in the TEC are seen as a function of chemical composition in Mo_1?xW_xS₂, with the smallest TEC being reported for a configuration with the highest entropy. This study provides key insights into understanding the nanoscale phenomena that control TEC values of 2D materials.