Antibacterial Surface Coatings from Zinc Oxide Nanoparticles Embedded in Poly(N‐isopropylacrylamide) Hydrogel Surface Layers

Despite multiple research approaches to prevent bacterial colonization on surfaces, device‐associated infections are currently responsible for about 50% of nosocomial infections in Europe and significantly increase health care costs, which demands development of advanced antibacterial surface coatings. Here, novel antimicrobial composite materials incorporating zinc oxide nanoparticles (ZnO NP) into biocompatible poly(N‐isopropylacrylamide) (PNIPAAm) hydrogel layers are prepared by mixing the PNIPAAm prepolymer with ZnO NP, followed by spin‐coating and photocrosslinking. Scanning electron microscopy (SEM) characterization of the composite film morphology reveals a homogeneous distribution of the ZnO NP throughout the film for every applied NP/polymer ratio. The optical properties of the embedded NP are not affected by the matrix as confirmed by UV‐vis spectroscopy. The nanocomposite films exhibit bactericidal behavior towards Escherichia coli (E. coli) for a ZnO concentration as low as ≈0.74 μg cm^?2 (1.33 mmol cm^?3), which is determined by inductively coupled plasma optical emission spectrometry. In contrast, the coatings are found to be non‐cytotoxic towards a mammalian cell line (NIH/3T3) at bactericidal loadings of ZnO over an extended period of seven days. The differential toxicity of the ZnO/hydrogel nanocomposite thin films between bacterial and cellular species qualifies them as promising candidates for novel biomedical device coatings.     

Ester-functionalized poly(3-alkylthiophene) copolymers: Synthesis,physicochemical characterization and performance in bulk heterojunction organic solar cells

The introduction of functional moieties in the donor polymer (side chains) offers a potential pathway toward selective modification of the nanomorphology of conjugated polymer:fullerene active layer blends applied in bulk heterojunction organic photovoltaics, pursuing morphology control and solar cell stability. For this purpose, two types of poly(3-alkylthiophene) random copolymers, incorporating different amounts (10/30/50%) of ester-functionalized side chains, were efficiently synthesized using the Rieke method. The solar cell performance of the functionalized copolymers was evaluated and compared to the pristine P3HT:PCBM system. It was observed that the physicochemical and opto-electronic characteristics of the polythiophene donor material can be modified to a certain extent via copolymerization without (too much) jeopardizing the OPV efficiency, as far as the functionalized side chains are introduced in a moderate ratio (<30%) and that preference is given to side chains with a small molar volume. A range of complementary techniques – UV–Vis spectroscopy, (modulated temperature) differential scanning calorimetry, transmission electron microscopy and X-ray diffraction analysis – indicated that variations in polymer crystallinity, while maintaining a high level of regioregularity, are probably the main factor responsible for the observed differences.     

A new method for modeling preoperative diagnosis of ovarian tumors

In this paper, we present a sequential nonuniform procedure, an inference method which combines feature selection based on the Kullback information gain and a step-wise classification procedure to produce a reliable, interpretable, and robust model. We applied the model to an ovarian tumor data set to distinguish between malignant and benign tumors. The performance of the model was assessed using receiver operating characteristic (ROC) analysis and gave an overall accuracy over 85%, and area under the curve (AUC) of 0.887 which compares well with existing methods. The method presented here is significant because of its ability to handle missing values, and it only uses a small number of variables which are graded according to their discriminative relevance. This, together with the fact that the resulting model is interpretable and has good performance, is likely to lead to widespread clinical acceptance of the method. The method is also generic and can be readily adapted for other classifications problems in biomedicine.     

Using prior knowledge in SVD-based parameter estimation for magnetic resonance spectroscopy--the ATP example

We introduce the knowledge-based singular value decomposition (KNOB-SVD) method for exploiting prior knowledge in magnetic resonance (MR) spectroscopy based on the SVD of the data matrix. More specifically, we assume that the MR data are well modeled by the superposition of a given number of exponentially damped sinusoidal components and that the dampings alphakappa, frequencies omegakappa, and complex amplitudes rhokappa of some components satisfy the following relations: alphakappa = alpha (alpha = unknown), omegakappa = omega + (kappa- 1)delta (omega = unknown, delta = known), and rhokappa = Ckapparho (rho = unknown, ckappa = known real constants). The adenosine triphosphate (ATP) complex, which has one triple peak and two double peaks whose dampings, frequencies, and amplitudes may in some cases be known to satisfy the above type of relations, is used as a vehicle for describing our SVD-based method throughout the paper. By means of numerical examples, we show that our method provides more accurate parameter estimates than a commonly used general-purpose SVD-based method and a previously suggested prior knowledge-based SVD method.     

Effect of pressure on efficiency of UV curing of CVD-derived low-k material at different wavelengths

Low-k dielectrics prepared by CVD in the form of 200 nm thick layers on Si wafers were thermally treated at 410 °C and irradiated using UV lamps emitting photons of different wavelengths around 172 nm, 185 nm, and 222 nm. The treatment was performed in high vacuum and under a nitrogen atmosphere at various pressures ranging from 0.1 mbar up to 700 mbar. Subsequently, the samples were investigated using FTIR transmission spectroscopy, contact angle measurement, X-ray photoelectron spectrometry (XPS), time-of-flight secondary ion mass spectrometry (TOF-SIMS), X-ray reflectometry (XRR), surface acoustic wave spectrometry (SAW), and purged UV spectroscopic ellipsometry (PUVSE). It was found that for all UV wavelengths applied for curing the depth profiles of the chemical composition were homogeneous. For all properties evaluated, irradiation at wavelengths below 200 nm resulted in more pronounced changes than at longer wavelengths. Generally, a decrease in residual porogen content, conversion of the Si-O-Si bonds from cage to network/suboxide, degradation of Si-CH₃ bonds, formation of H-SiO bonds, increase in surface energy, changes of element concentrations and of density, increase in Young’s modulus, and changes in dielectric constant were observed. These findings were confirmed by quantum-chemical calculations. With increasing nitrogen pressure the effects were more considerable. An attempt was undertaken to explain the effect of nitrogen pressure in course of the role of nitrogen molecules as collision partners.     

Effect of Bismuth Nanotubes on the Thermoelectric Properties of BiSb Alloy Nanocomposites

Bismuth nanotubes have been synthesized and successfully included in Bi_1?x Sb _x nanoalloys to form composite structures. The nanotubes were synthesized by transformation of a β-BiI precursor with n-BuLi solution leading to tubular bismuth structures. The Bi_1?x Sb _x nanoalloys were produced by ball milling. Three series of composite structures were synthesized by including different fractions (0 wt.%, 3 wt.%, 5 wt.%) of nanotubes in nanoalloys of different composition x. Investigation of thermoelectric and structural properties revealed a decrease of the thermal conductivity of up to 40% for the composites in comparison with alloys without nanotube inclusions. This effect can be attributed to enhanced phonon scattering. Seebeck coefficients and electrical conductivities were both slightly enhanced in the composite series with 3 wt.% nanotube inclusions, leading to enhancement of $$ ZT \ \left(ZT=\frac {(S^2 \sigma)}{\kappa}\,{ {T}}\right) $$ throughout the series compared with the nanoalloy series without nanotube inclusions.     

Stability of Flip-Chip Interconnects Assembled with Al/Ni(V)/Cu-UBM and Eutectic Pb-Sn Solder During Exposure to High-Temperature Storage

The thermal stability of flip-chip solder joints made with trilayer Al/Ni(V)/Cu underbump metalization (UBM) and eutectic Pb-Sn solder connected to substrates with either electroless Ni(P)-immersion gold (ENIG) or Pb-Sn solder on Cu pad (Cu-SOP) surface finish was determined. The ENIG devices degraded more than 50 times faster than the Cu-SOP devices. Microstructural characterization of these joints using scanning and transmission electron microscopy and ion beam microscopy showed that electrical degradation of the ENIG devices was a direct result of the conversion of the as-deposited Ni(V) barrier UBM layer into a porous fine-grained V₃Sn-intermetallic compound (IMC). This conversion was driven by the Au layer in the ENIG surface finish. No such conversion was observed for the devices assembled on Cu-SOP surface finish substrates. A resistance degradation model is proposed. The model captures changes from a combination of phenomena including increased (1) intrinsic resistivity, (2) porosity, and (3) electron scattering at grain boundaries and surfaces. Finally, the results from this study were compared with results found in a number of published electromigration studies. This comparison indicates that degradation during current stressing in the Pb-Sn bump/ENIG system is in part due to current-crowding-induced Joule heating and the thermal gradients that result from localized Joule heating.     

How to improve intrinsic and extrinsic reliability of vias by process optimization

A systematic study of various processes and their impact on intrinsic reliability has been performed on Cu dual damascene interconnects. The most significant improvement for intrinsic reliability is the ‘break-through’ liner. A strong impact on stressmigration (SM) was revealed using a HDP based SiN deposition on top of Cu lines. Early failures in electromigration (EM) studies are present with insufficient cleaning processes. No reliability impact was detected with different plating and slurry chemistries and liner thickness increase. Extrinsic via reliability is assessed with a special test chip comprising 3E9 via/wafer. High ohmic vias are identified before and after thermal stress. As an example, the failure rates in Cu dual damascene levels with relaxed pitch before and after cleaning optimization are discussed.     

Application of kernel principal component analysis for single-lead-ECG-derived respiration

Recent studies show that principal component analysis (PCA) of heartbeats is a well-performing method to derive a respiratory signal from ECGs. In this study, an improved ECG-derived respiration (EDR) algorithm based on kernel PCA (kPCA) is presented. KPCA can be seen as a generalization of PCA where nonlinearities in the data are taken into account by nonlinear mapping of the data, using a kernel function, into a higher dimensional space in which PCA is carried out. The comparison of several kernels suggests that a radial basis function (RBF) kernel performs the best when deriving EDR signals. Further improvement is carried out by tuning the parameter σ(2) that represents the variance of the RBF kernel. The performance of kPCA is assessed by comparing the EDR signals to a reference respiratory signal, using the correlation and the magnitude squared coherence coefficients. When comparing the coefficients of the tuned EDR signals using kPCA to EDR signals obtained using PCA and the algorithm based on the R peak amplitude, statistically significant differences are found in the correlation and coherence coefficients (both p<0.0001), showing that kPCA outperforms PCA and R peak amplitude in the extraction of a respiratory signal from single-lead ECGs.