Interaction of Small Molecules within Metal Organic Frameworks Studied by In Situ Vibrational Spectroscopy

Molecular-level characterization of interaction between small gases and metal organic frameworks (MOFs) is crucial to elucidate the adsorption mechanism and establish the relationship between the structure and chemical features of MOFs with observed adsorptive properties, which ultimately guide the new structure design and synthesis for enhanced functional performance. Among different techniques, vibrational spectroscopy (infrared and Raman), which provides fingerprint of chemical bonds by their vibrational spectra, is one of the most powerful tools to study adsorbate-adsorbent interaction and give rich detailed information for molecular behaviors inside MOFs pores. This chapter reviews a number of exemplary works utilizing vibrational spectroscopy to study the interaction of small molecules with metal organic frameworks

The Impact of Brand Image and Customer Commitment on Loyalty: An Empirical Study of Automobile Sector

Corporate brand image has been assessed as an important antecedent of customer commitment and loyalty. Corporate brands help companies achieving higher performance, such as sales. A poor brand image will lead to disaster, and lose customers. Marketing exists to deliver more value to satisfy customers as well as build a long-term and mutually profitability relationship with customers. If a firm’s products or services do not satisfy or meet the customer’s needs and wants, all the strategies are insufficient. With loyal customers, companies can have higher market share and reduce the operating cost. This initial study was from relevant literature, then set up research structure and hypotheses. Survey was employed, and respondents were collected from automobile sector in Taiwan. There were 170 usable questionnaires to analyze normality, convergent and discriminant validities, and SEM model by PASW 18 and AMOS 18.0. The research found that corporate brand image significantly affects customer commitment and loyalty, and customer commitment has strong impact on customer loyalty for the sample. Therefore, firms need to specifically focus on a long-term and mutually profitability relationship with a customer and create loyalty as competitive advantages in the markets

Graphene field effect transistors with ferroelectric gating

Recent experiments on ferroelectric gating have introduced a novel functionality, i.e. nonvolatility, in graphene field effect transistors. A comprehensive understanding in the non-linear, hysteretic ferroelectric gating and an effective way to control it are still absent. In this letter, we quantitatively characterize the hysteretic ferroelectric gating using the reference of an independent background doping (nBG) provided by normal dielectric gating. More importantly, we prove that nBG can be used to control the ferroelectric gating by unidirectionally shifting the hysteretic ferroelectric doping in graphene. Utilizing this electrostatic effect, we demonstrate symmetrical bit writing in graphene-ferroelectric FETs with resistance change over 500% and reproducible no-volatile switching over 10^5 cycles.Comment: 5 Pages; 4 figures; two column forma

Killing Two Birds with One Stone: Quantization Achieves Privacy in Distributed Learning

Communication efficiency and privacy protection are two critical issues in distributed machine learning. Existing methods tackle these two issues separately and may have a high implementation complexity that constrains their application in a resource-limited environment. We propose a comprehensive quantization-based solution that could simultaneously achieve communication efficiency and privacy protection, providing new insights into the correlated nature of communication and privacy. Specifically, we demonstrate the effectiveness of our proposed solutions in the distributed stochastic gradient descent (SGD) framework by adding binomial noise to the uniformly quantized gradients to reach the desired differential privacy level but with a minor sacrifice in communication efficiency. We theoretically capture the new trade-offs between communication, privacy, and learning performance