Tuning of shear thickening behavior and elastic strength of polyvinylidene fluoride via doping of ZnO-graphene

ZnO rice like nonarchitects are grafted on the graphene carbon core via a rapid microwave synthesis route. The prepared grafted systems are characterized via XRD, SEM, RAMAN, and XPS to examined the structural and morphological parameters. Zinc oxide grafted graphene sheets (ZnO-G) are further doped in β-phase of polyvinylidene fluoride (PVDF) to prepare the polymer nanocomposites (PNCs) via mixed solvent approach (THF/DMF). β-phase confirmation of PVDF PNCs is done by FTIR studies. It is observed that ZnO-G filler enhances the β-phase content in the PNCs. Non-doped PVDF and PNCs are further studied for rheological behavior under the shear rate of 1–100 s⁻¹. Doping of ZnO-G dopant to the PVDF matrix changes its discontinuous shear thickening (DST) behavior to continues shear thickening behavior (CST). Hydrocluster formation and their interaction with the dopant could be the reason for this striking DST to CST behavioral change. Strain amplitude sweep (10⁻³% -10%) oscillatory test reveals that the PNCs shows extended linear viscoelastic region with high elastic modulus and lower viscous modulus. Effective shear thickening behavior and strong elastic strength of these PNCs present their candidature for various fields including mechanical and soft body armor applications.     

Large Area Self-Assembled Ultrathin Polyimine Nanofilms Formed at the Liquid–Liquid Interface Used for Molecular Separation

Separation membranes with higher molecular weight cut-offs are needed to separate ions and small molecules from a mixed feed. The molecular sieving phenomenon can be utilized to separate smaller species with well-defined dimensions from a mixture. Here, the formation of freestanding polyimine nanofilms with thicknesses down to ≈14 nm synthesized via self-assembly of pre-synthesized imine oligomers is reported. Nanofilms are fabricated at the water–xylene interface followed by reversible condensation of polymerization according to the Pieranski theory. Polyimine nanofilm composite membranes are made via transferring the freestanding nanofilm onto ultrafiltration supports. High water permeance of 49.5 L m^-2 h⁻¹ bar⁻¹ is achieved with a complete rejection of brilliant blue-R (BBR; molecular weight = 825 g mol⁻¹) and no more than 10% rejection of monovalent and divalent salts. However, for a mixed feed of BBR dye and monovalent salt, the salt rejection is increased to ≈18%. Membranes are also capable of separating small dyes (e.g., methyl orange; MO; molecular weight = 327 g mol⁻¹) from a mixed feed of BBR and MO. Considering a thickness of ≈14 nm and its separation efficiency, the present membrane has significance in separation processes.     

Synthesis and characterization of electrically conducting copolymer of aniline and o‐bromoaniline using methane sulfonic acid as dopant

Polyaniline (PAN), poly(o‐bromoaniline) (POBA), and poly(aniline‐co‐o‐bromoaniline) (PABA) were synthesized by oxidative coupling. These polymers are protonated by 10–20% methane sulfonic acid (MSA) and 1M HCl. The new polymer bases have greater solubility than that of PAN in common polar organic solvents; PAN–MSA was observed to be the most thermally stable of these polymers. POBA is associated with residual quinoid diimine units as illustrated in the IR and UV‐vis spectra, after reduction with hydrazine dihydrochloride. Both the doping agents cause a downward shift of the quinoid absorption in the IR spectra. MSA‐ and HCl‐doped PAN and PABA polymers exhibit a coil‐like conformation in DMSO, whereas only MSA‐doped PAN and PABA show an “expanded coil‐like” conformation in m‐cresol with a “free carrier tail” above 800 nm in their electronic spectra. XPS spectra indicated the presence of covalent bromine in the POBA and PABA polymers. Bromine retention was greater in the homopolymer as evidenced by the IR studies after aging at 350°C. Compared to HCl, MSA is found to be a more effective dopant, enhancing the conductivity of the copolymers by 10²–10³ times in magnitude. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 2662–2669, 2002     

Study of polyaniline polyacrylamide composites by positron annihilation technique

Polyaniline doped with nonoxidizing Bronsted acids is recognized as a conducting material, as its electrical conductivity changes with percentage of doping. In the present work, different percentages of doped polyaniline were blended with polyacrylamide and their electrical conductivities as well as the positron annihilation lifetimes were measured. Analysis of data yielded three lifetime components. It was observed that the value of the short lifetime component remained constant for doping concentration, whereas that of the intermediate component τ₂ decreased. The relative intensity pertaining to τ₂, however, increased with the increase in doped PANI concentration. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 930–933, 2003     

An International Collaborative Study on Trypsin Inhibitor Assay for Legumes,Cereals, and Related Products

For determining trypsin inhibitor activity (TIA) in soy products, the American Oil Chemists' Society (AOCS) Method Ba 12-75 has been used. It measures differences in absorbance at 410 nm of bovine trypsin activity toward a synthetic substrate (Nα-benzoyl-DL-arginine-p-nitroanilide) in the absence and presence of an inhibitor. Recently, a significantly improved method was developed (JAOCS, 2019, 96:635–645), featuring 5 mL of total assay volume, enzyme-last sequence, and single inhibitor level in duplicate. It is proposed as the AOCS Method Ba 12a-2020. As a part of the AOCS method approval process, a collaborative study involving 12 international laboratories was conducted to evaluate the performance of the proposed method. The study involved measuring TIA in 10 selected test samples plus a blind duplicate. They included soybeans, pulses, cereals, and their processed products (flours, concentrates, and isolates). After rigorous statistical treatment of the data, only three outliers were removed from the data of two samples. Repeatability relative standard deviations (RSDr) for the 11 samples ranged from 0.99% to 5.52%. Reproducibility RSD (RSD_R) ranged from 7.07% to 22.92%, with seven samples having RSD_R around 10% or less. The remaining four samples had very low TIA, and their RSD_R values ranged from 13.34% to 22.92%. The study has demonstrated reliable performance of the proposed AOCS method. Several collaborators carried out additional experiments addressing some aspects of the method, leading to further refinements. The proposed method is undergoing evaluation by the AOCS Uniform Methods Committee for adoption as an Official Method for measuring TIA in various legume and grain products.     

Topography of the flank wear surface

In many applications, topography represents the main external features of a surface. This paper describes the topography of the flank wear surface and also presents the relationship between the maximum flank wear and the topography parameters (roughness parameters) of the flank wear surface during the turning operation. A modern CNC lathe machine (Okuma LH35-N) was used for the machine turning operation. Three-dimensional surface roughness parameters of the flank wear surface were measured by a surface texture instrument (from Talysurf series) using surface topography software (Talymap). Based on the resulting experimental data, it is found that as the flank wear increases, the roughness parameters (sR_a, sR_q, and sR_t) on the flank surface increase significantly. The greater the roughness value of the flank wear surface, the higher the friction of the tool on the workpiece and the greater the heat generation that will occur, thus ultimately causing tool failure. On the other hand, positive skewness (sR_sk) indicates the presence of a small number of spikes on the flank surface of the cutting tool, which could quickly wear off during the machining process.     

A Two-Stage Approach for Network Monitoring

A goal of network tomography is to infer the status (e.g. delay) of congested links internal to a network, through end-to-end measurements at boundary nodes (end-hosts) via insertion of probe signals. Because (a) probing constitutes traffic overhead, and (b) in any typical scenario, the number of congested links is a small fraction of the total number in the network, a desirable design objective is to identify those (few) congested links using a minimum number of probes. In this paper, we make a contribution to solving this problem, by proposing a new two-stage approach for this problem. First, we develop a binary observation model linking end-to-end observations with individual link statuses and derive necessary and sufficient conditions for whether at least one link in the network is congested. Stage I of the proposed method shows that achieving 1-identifiability with a minimum number of probes is equivalent to the familiar minimum set covering problem that can be efficiently solved via a greedy heuristic. A sequential algorithm is described, leading to a significantly lowered computational complexity vis-a-vis a batch algorithm. Next, a binary splitting algorithm originally developed in group testing is used to identify the location of the congested links. The proposed scheme is evaluated by simulations in OPNET and experiments on the PlanetLab testbed to validate the advantages of our 2-stage approach vis-a-vis a conventional (batch) algorithm.     

Template-based program verification and program synthesis

Program verification is the task of automatically generating proofs for a program’s compliance with a given specification. Program synthesis is the task of automatically generating a program that meets a given specification. Both program verification and program synthesis can be viewed as search problems, for proofs and programs, respectively. For these search problems, we present approaches based on user-provided insights in the form of templates. Templates are hints about the syntactic forms of the invariants and programs, and help guide the search for solutions. We show how to reduce the template-based search problem to satisfiability solving, which permits the use of off-the-shelf solvers to efficiently explore the search space. Template-based approaches have allowed us to verify and synthesize programs outside the abilities of previous verifiers and synthesizers. Our approach can verify and synthesize difficult algorithmic textbook programs (e.g., sorting and dynamic programming-based algorithms) and difficult arithmetic programs.     

Language independent unsupervised learning of short message service dialect

Noise in textual data such as those introduced by multilinguality, misspellings, abbreviations, deletions, phonetic spellings, non-standard transliteration, etc. pose considerable problems for text-mining. Such corruptions are very common in instant messenger and short message service data and they adversely affect off-the-shelf text mining methods. Most techniques address this problem by supervised methods by making use of hand labeled corrections. But they require human generated labels and corrections that are very expensive and time consuming to obtain because of multilinguality and complexity of the corruptions. While we do not champion unsupervised methods over supervised when quality of results is the singular concern, we demonstrate that unsupervised methods can provide cost effective results without the need for expensive human intervention that is necessary to generate a parallel labeled corpora. A generative model based unsupervised technique is presented that maps non-standard words to their corresponding conventional frequent form. A hidden Markov model (HMM) over a “subsequencized” representation of words is used, where a word is represented as a bag of weighted subsequences. The approximate maximum likelihood inference algorithm used is such that the training phase involves clustering over vectors and not the customary and expensive dynamic programming (Baum–Welch algorithm) over sequences that is necessary for HMMs. A principled transformation of maximum likelihood based “central clustering” cost function of Baum–Welch into a “pairwise similarity” based clustering is proposed. This transformation makes it possible to apply “subsequence kernel” based methods that model delete and insert corruptions well. The novelty of this approach lies in that the expensive (Baum–Welch) iterations required for HMM, can be avoided through an approximation of the loglikelihood function and by establishing a connection between the loglikelihood and a pairwise distance. Anecdotal evidence of efficacy is provided on public and proprietary data.