Spectral narrowing and manipulation in an optical parametric oscillator using periodically poled lithium niobate electro-optic polarization-mode converters

We report a unique spectral narrowing and manipulation technique in an optical parametric oscillator (OPO) realized by an integrated periodically poled lithium niobate comprising an optical parametric gain medium sandwiched by two electro-optic polarization-mode converters (EO PMCs). We achieved a manipulation of the gain spectrum of the OPO via EO and/or temperature control of the EO PMCs, in which we obtained single to multiple signal spectral peaks from the OPO with a spectral width reduced by up to 10 times and peak intensity increased by up to 6 times in comparison with the original signal. Fast EO tuning of the narrowed signal spectral peak has also been demonstrated.     

Effects of post-annealing on the structural and nanomechanical properties of Ga-doped ZnO thin films deposited on glass substrate by rf-magnetron sputtering

In this study, the effects of post-annealing on the structure, surface morphology and nanomechanical properties of ZnO thin films doped with a nominal concentration of 3 at.% Ga (ZnO:Ga) are investigated using X-ray diffraction (XRD), atomic force microscopy (AFM) and scanning electron microscopy (SEM) and nanoindentation techniques. The ZnO:Ga thin films were deposited on the glass substrates at room temperature by radio frequency magnetron sputtering. Results revealed that the as-deposited ZnO:Ga thin films were polycrystalline albeit the low deposition temperature. Post-annealing carried out at 300, 400 and 500 °C, respectively, has resulted in progressive increase in both the average grain size and the surface roughness of the ZnO:Ga thin film, in addition to the improved thin films crystallinity. Moreover, the hardness and Young's modulus of ZnO:Ga thin films are measured by a Berkovich nanoindenter operated with the continuous contact stiffness measurements (CSM) option. The hardness and Young's modulus of ZnO:Ga thin films increased as the annealing temperature increased from 300 to 500 °C, with the best results being obtained at 500 °C.     

Magnetic properties of electroless-deposited Ni and Ni-NiO core-shell nano-arrays

Ni and Ni-NiO core-shell nano-arrays were fabricated by means of electroless deposition, where the latter was covered by a NiO shell of ∼10 nm by annealing the former at 350 °C for 30 min in an atmospheric condition. HRTEM showed that the NiO shell was developed at the expense of Ni at the array's surface. Ferromagnetic ordering of the Ni-NiO arrays was found to be suppressed compared with those of the less oxidized reference Ni arrays. This is attributed to the screening effect of the NiO shell, and weak ferromagnetism of inner Ni arrays resulted from the development of the NiO. X-ray absorption spectrum reveals that the reference Ni is partially oxidized. Also, X-ray magnetic circular dichroism suggests that the magnetic suppression of the Ni-NiO arrays is associated with a reduced spin moment.     

Rough set theory: a novel approach for extraction of robust decision rules based on incremental attributes

Rough set theory is a new data mining approach to manage vagueness. It is capable to discover important facts hidden in the data. Literature indicate the current rough set based approaches can’t guarantee that classification of a decision table is credible and it is not able to generate robust decision rules when new attributes are incrementally added in. In this study, an incremental attribute oriented rule-extraction algorithm is proposed to solve this deficiency commonly observed in the literature related to decision rule induction. The proposed approach considers incremental attributes based on the alternative rule extraction algorithm (AREA), which was presented for discovering preference-based rules according to the reducts with the maximum of strength index (SI), specifically the case that the desired reducts are not necessarily unique since several reducts could include the same value of SI. Using the AREA, an alternative rule can be defined as the rule which holds identical preference to the original decision rule and may be more attractive to a decision-maker than the original one. Through implementing the proposed approach, it can be effectively operating with new attributes to be added in the database/information systems. It is not required to re-compute the updated data set similar to the first step at the initial stage. The proposed algorithm also excludes these repetitive rules during the solution search stage since most of the rule induction approaches generate the repetitive rules. The proposed approach is capable to efficiently and effectively generate the complete, robust and non-repetitive decision rules. The rules derived from the data set provide an indication of how to effectively study this problem in further investigations.     

Maintenance outsourcing coordination with risk-averse contractors

Under a maintenance outsourcing contract, an external contractor receives a fixed payment from a manufacturer for periodically performing preventive maintenance and for performing minimal repairs whenever process failures occur. If the contractor’s maintenance policy results in a process uptime above a target level specified in the contract, the contractor receives a bonus payment based on the difference between the uptime and the target levels. We study the optimal designs of maintenance outsourcing contracts for achieving channel coordination when the contractor is risk averse towards uncertain repair costs caused by process failures. We find cases in which channel coordination cannot be achieved because of the contractor’s risk preference. Furthermore, the contractor’s risk preference may make channel coordination more difficult or easier, depending on the parameters considered in the model.     

Extracting informative variables in the validation of two-group causal relationship

The validation of causal relationship between two groups of multivariate time series data often requires the precedence knowledge of all variables. However, in practice one finds that some variables may be negligible in describing the underlying causal structure. In this article we provide an explicit definition of “non-informative variables” in a two-group causal relationship and introduce various automatic computer-search algorithms that can be utilized to extract informative variables based on a hypothesis testing procedure. The result allows us to represent a simplified causal relationship by using minimum possible information on two groups of variables.     

Hard nanocomposite comprising stereoregular syndiotactic polypropylene with chemically bonded gold nanoparticles

An effective method to synthesize directly a hard composite material containing uniformly dispersed nanogold particles chemically bonded with a stereospecific, crystalline polymer matrix has been developed. Syndiotactic polypropylene was synthesized and functionalized to have a hydroxyl terminal group (sPP_OH) via a metallocene catalysis with a selective chain transfer. Next, sPP_OH was activated to react with ethylene sulfide forming the thiol‐terminated polymer, sPP_SH. sPP_SH was then chemically bonded to gold nanoparticles (AuNPs) formed in situ via a reduction of HAuCl₄. The bonding between thiol and AuNP stabilized the AuNPs and led to the formation of sPP_AuNPs composite containing uniformly‐dispersed AuNPs of a 19–40 nm size without noticeable aggregation. Furthermore, the chemical bonding of AuNPs has afforded sPP_AuNPs a thermal degradation temperature (T_D) 49.4 °C higher than the pristine sPP or sPP_OH and 25.7 °C higher than sPP_SH without any adverse effect on the crystalline temperature and melting temperature. In addition, the characteristic UV‐Vis absorption wavelength of sPP_AuNPs remains the same at various temperatures, thus indicating the independence of optical property on temperature as well as the good thermal stability of the sPP_AuNPs composite. ¹H NMR, ¹³C NMR, FESEM, STEM, XPS, TGA and DSC were used to investigate the molecular structure, morphology and thermal properties of the resulting sPP_AuNPs nanocomposite. © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2010     

Copolyphenylenes with pendant benzimidazolyl and diethanolaminohexyloxy groups: Synthesis and electron‐transporting application in PLEDs

Two new electron‐transporting copolyphenylenes P1NH and P2NH possessing balanced charges crucial to emission efficiency of polymer light‐emitting diodes (PLEDs) have been synthesized and applied as an electron‐transporting layer (ETL). The main chain structure is all para‐linkage for P1NH and both para‐ and meta‐linkage for P2NH , with the same pendant electron‐withdrawing benzimidazolyl and polar diethanolaminohexyloxy groups. Both copolymers possess excellent thermal stability (T _d > 300 °C, T _g > 100 °C) due to their rigid backbones. In addition, the pendant groups effectively lower LUMO (～ ?2.70 eV) and HOMO (～ ?5.70 eV) levels, resulting in improved electron‐transporting and hole‐blocking capabilities. Multilayer yellow‐emitting PLEDs with a configuration of ITO/PEDOT:PSS/SY/ETL/LiF/Al were successfully fabricated by the spin‐coating process. The maximum luminance and maximum current efficiency of the P1NH ‐based device were 12,881 cd/m² and 10.94 cd/A, respectively, superior to the performance of P2NH ‐based device (4938 cd/m², 3.70 cd/A) and the device without ETL (8690 cd/m², 2.78 cd/A). Current results indicate that P1NH is highly effective in enhancing electron transport and device performance. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2017 , 55 , 2494–2505     

Surrogate-based modeling and dimension reduction techniques for multi-scale mechanics problems

Successful modeling and/or design of engineering systems often requires one to address the impact of multiple "design variables" on the prescribed outcome.There are often multiple,competing objectives based on which we assess the outcome of optimization.Since accurate,high fidelity models are typically time consuming and computationally expensive,comprehensive evaluations can be conducted only if an efficient framework is available.Furthermore,informed decisions of the model/hardware’s overall performance rely on an adequate understanding of the global,not local,sensitivity of the individual design variables on the objectives.The surrogate-based approach,which involves approximating the objectives as continuous functions of design variables from limited data,offers a rational framework to reduce the number of important input variables,i.e.,the dimension of a design or modeling space.In this paper,we review the fundamental issues that arise in surrogate-based analysis and optimization,highlighting concepts,methods,techniques,as well as modeling implications for mechanics problems.To aid the discussions of the issues involved,we summarize recent efforts in investigating cryogenic cavitating flows,active flow control based on dielectric barrier discharge concepts,and lithium(Li)-ion batteries.It is also stressed that many multi-scale mechanics problems can naturally benefit from the surrogate approach for "scale bridging."