Optimization of microfluidization for the homogeneous distribution of cellulose nanocrystals (CNCs) in biopolymeric matrix

Microfluidization, which is a high-pressure homogenization technique, was used to develop highly dispersed cellulose nanocrystal (CNC) reinforced chitosan based nanocomposite films. A three factor central composite design with five levels was designed to systematically optimize the microfluidization process. The three factors were the CNC content, the microfluidization pressure and the number of microfluidization cycles. Response surface methodology was used to obtain relationship between the mechanical properties of the nanocomposite films and the factors. Polynomial equations were generated based on the regression analysis of the factors and the predicted properties of the nanocomposite films were in good agreement with the experimental results. Microfluidization effectively reduced the CNC–chitosan aggregates and improved the mechanical properties of the nanocomposite films. Microscopic analysis of the microfluidized nanocomposite films revealed a 10–15 times reduction in the size of the aggregates compared to the non-microfluidized CNC/chitosan films and an increase in the root mean square surface roughness (Rq).     

Oversampling Free Energy Perturbation Simulation in Determination of the Ligand-Binding Free Energy

Determination of the ligand-binding affinity is an extremely interesting problem. Normally, the free energy perturbation (FEP) method provides an appropriate result. However, it is of great interest to improve the accuracy and precision of this method. In this context, temperature replica exchange molecular dynamics implementation of the FEP computational approach, which we call replica exchange free energy perturbation (REP) was proposed. In particular, during REP simulations, the system can easily escape from being trapped in local minima by exchanging configurations with high temperatures, resulting in significant improvement in the accuracy and precision of protein–ligand binding affinity calculations. The distribution of the decoupling free energy was enlarged, and its mean values were decreased. This results in changes in the magnitude of the calculated binding free energies as well as in alteration in the binding mechanism. Moreover, the REP correlation coefficient with respect to experiment ( R^REP = 0.85 ± 0.15 ) is significantly boosted in comparison with the FEP one ( R^FEP = 0.64 ± 0.30 ). Furthermore, the root-mean-square error (RMSE) of REP is also smaller than FEP, RMSE^REP = 4.28 ± 0.69 versus RMSE^FEP = 5.80 ± 1.11 kcal/mol, respectively. © 2019 Wiley Periodicals, Inc.     

Effect of aspect ratio of vertically aligned copper nanowires in the presence of cellulose nanofibers on the thermal conductivity of epoxy composites

The composites comprising vertically aligned network of copper nanowires (CuNWs) in the presence of cellulose nanofibers were fabricated by using the freeze‐templating method and the effect of aspect ratio (A/R) of CuNWs on the thermal conductivity of epoxy composites was investigated. The thermal conductivity of epoxy composites increased to 0.79 W m^?1 K^?1 at 1.12 vol% of high A/R CuNWs loading, corresponding to the thermal conductivity enhancement of 365% as compared to the pure epoxy. The thermal conductivity of vertically aligned higher A/R CuNWs/epoxy, which is 38.5% and 51.9% higher than those of the lower A/R CuNWs and the randomly aligned CuNWs, respectively. The application of the epoxy composites in heat dissipation was demonstrated by the temperature changes of composites on a hot plate with the increase of heating time. These results indicate that the thermally conductive composites in this study could be applied for thermal dissipating materials in electronic devices.     

On Roussel–Rubio-type lemmas and their consequences

Roussel and Rubio proved a lemma which is essential in the proof of the Strong Perfect Graph Theorem. We give a new short proof of the main case of this lemma. In this note, we also give a short proof of Hayward’s decomposition theorem for weakly chordal graphs, relying on a Roussel–Rubio-type lemma. We recall how Roussel–Rubio-type lemmas yield very short proofs of the existence of even pairs in weakly chordal graphs and Meyniel graphs.     

Lattice dynamics of Eu<Subscript>1-x</Subscript>Y<Subscript>x</Subscript>MnO<Subscript>3</Subscript> (0 ≤ x ≤ 0.5)

A systematic and detailed study of Raman and infrared active lattice excitations in the orthorhombic multiferroic manganite Eu_1−xY_xMnO₃ (0 ≤ x ≤ 0.5) was carried out at room temperature. For the infrared active phonon modes the eigenfrequencies, damping constants and oscillator strengths were analyzed by Fourier-Transform Infrared Spectroscopy in the far infrared frequency range. For the Raman active phonons the same analysis for eigenfrequencies and damping constants was carried out using Raman spectroscopy in the range from 200 cm⁻¹ to 700 cm⁻¹. Y doping leads to mode-dependent phonon frequency shifts up to 8%. These are interpreted in terms of the interplay between the decrease of the reduced ion masses and the axis-dependent change of bond lengths. The latter leads to a bond softening along the a-axis and a strengthening along the c-axis, for which the highest phonon frequency increase is observed. The application of both Raman and Infrared Spectroscopy gives us sensitivity not only to symmetry properties via the selection rules but also to the involvement of different ion types within the unit cell. It is clearly shown that the disorder induced effects are of minor impact on the lattice properties and solely detected on the rare earth sites. The MnO₆ octahedra remain unaffected and show the same behavior as in the stochiometric RMnO₃ making Eu_1−xY_xMnO₃ an excellent model system for a quasi-continuous fine-tuning of the lattice parameters relevant for the appearance of multiferroicity.     

Tuning of nanotube mechanical resonances by electric field pulling

We show here that field emission (FE) can be used to directly observe the vibration resonances nu(R) of carbon nanotubes (CNTs) and that the tension created by the applied field allows the tuning of these resonances by up to a factor of 10. The resonances are observable by the changes they create in the FE pattern or the emitted FE current. The tuning is shown to be linear in voltage and to follow from the basic physics of stretched strings. The method allows one to study the mechanical properties of individual multiwall carbon nanotubes within an ensemble and follow their evolution as the CNTs are modified. The tuning and detection should be useful for nanometric resonant devices.     

Measurement of the spectral distribution of a multi-mode dye laser light by using speckle patterns

A simple method of measuring the wavelength γ₁ and the spectral line spacing Δγ of a multi-mode dye laser light by using the correlated speckle patterns produced at the far-field of a diffuser is proposed. Examples of the obtained values of γ₁ and Δγ are 6.0 × 10³ Å and 3.0 × 10¹ Å, respectively.     

Molality as a unit of measure for expressing 1H MRS brain metabolite concentrations in vivo

Absolute concentrations of cerebral metabolite in in vivo 1H magnetic resonance spectroscopy studies (1H-MRS) are widely reported in molar units as moles per liter of tissue, or in molal units as moles per kilogram of tissue. Such measurements require external referencing or assumptions as to local water content. To reduce the scan time, avoid assumptions that may be invalid under specific pathologies, and provide a universally accessible referencing procedure, we suggest that metabolite concentrations from 1H-MRS measurements in vivo be reported in molal units as moles per kilogram of tissue water. Using internal water referencing, a two-compartment water model, a simulated brain spectrum for peak identification, and a spectroscopic bi-exponential spin-spin relaxation segmentation technique, we measured the absolute concentrations for the four common 1H brain metabolites: choline (Cho), myo-inositol (mIno), phosphocreatine + creatine (Cr), and N-acetyl-aspartate (NAA), in the hippocampal region (n = 26) and along the Sylvian fissure (n = 61) of 35 healthy adults. A stimulated echo localization method (20 ms echo time, 10 ms mixing time, 4 s repetition time) yielded metabolite concentrations, uncorrected for metabolite relaxation or contributions from macromolecule resonances, that were expectantly higher than with molar literature values. Along the Sylvian fissure the average concentrations (coefficient of variation (CV)) in mmoles/kg of tissue water were 17.6 (12%) for NAA, 14.2 (9%) for Cr, 3.6 (13%) for Cho, and 13.2 (15%) for mIno. Respective values for the hippocampal region were 15.7 (20%), 14.7 (16%), 4.6 (19%), and 17.7 (26%). The concentrations of the two regions were significantly different (p 相似文献   

Eigenvalues of Random Power law Graphs

Many graphs arising in various information networks exhibit the "power law" behavior -the number of vertices of degree k is proportional to k^-# for some positive #. We show that if # > 2.5, the largest eigenvalue of a random power law graph is almost surely(1+ o(1))?m (1+ o(1))\sqrt{m} where m is the maximum degree. Moreover, the klargest eigenvalues of a random power law graph with exponent # have power law distribution with exponent 2# if the maximum degree is sufficiently large, where k is a function depending on #, mand d, the average degree. When 2<#< 2.5, the largest eigenvalue is heavily concentrated at cm^3-# for some constant c depending on # and the average degree. This result follows from a more general theorem which shows that the largest eigenvalue of a random graph with a given expected degree sequence is determined by m, the maximum degree, and [(d)\tilde] \tilde{d} , the weighted average of the squares of the expected degrees. We show that the k-th largest eigenvalue is almost surely (1+ o(1))?{m_k} (1+ o(1))\sqrt{m_k} where m_k is the k-th largest expected degree provided m_k is large enough. These results have implications on the usage of spectral techniques in many areas related to pattern detection and information retrieval.