Lehigh University

About: Lehigh University is a education organization based out in Bethlehem, Pennsylvania, United States. It is known for research contribution in the topics: Catalysis & Fracture mechanics. The organization has 12684 authors who have published 26550 publications receiving 770061 citations.

Quantitative characterization of the acid-base properties of solvents, polymers, and inorganic surfaces

Abstract: The growing realization of the importance of intermolecular acid-base interactions in promoting the solubility, adsorption, and adhesion of polymers to other materials has caused a demand for the quantitative characterization of the acid-base properties of the commonly used solvents, polymers, and inorganic fillers and substrates. There have been several recent advances in the measurement techniques for such determinations, especially in the fields of inverse gas chromatography, microcalorimetry, ellipsometry, FTIR, NMR, and XPS spectroscopy, all leading to the capability of determining the Drago E and C constants or the Gutmann acceptor numbers (AN) or donor numbers (DN) for the acidic or basic sites of solvents, polymers, or inorganic surfaces. In the last year, new studies have also allowed the characterization of the specific acid-base cohesive interactions in solvents and polymers, and the determination, from contact angle measurements on polymers, of the surface concentration and strength of acidic ...

Strategies for the Synthesis of Supported Gold Palladium Nanoparticles with Controlled Morphology and Composition

Abstract: The discovery that supported gold nanoparticles are exceptionally effectivecatalysts for redox reactions has led to an explosion of interest in gold nanoparticles. In addition, incorporating a second metal as an alloy with gold can enhance the catalyst performance even more. The addition of small amounts of gold to palladium, in particular, and vice versa significantly enhances the activity of supported gold–palladium nanoparticles as redox catalysts through what researchers believe is an electronic effect.In this Account, we describe and discuss methodologies for the synthesisof supported gold–palladium nanoparticles and their use as heterogeneous catalysts. In general, three key challenges need to be addressed in the synthesis of bimetallic nanoparticles: (i) control of the particle morphology, (ii) control of the particle size distribution, and (iii) control of the nanoparticle composition. We describe three methodologies to address these challenges. First, we discuss the relatively simple method of co...

Learning with dynamic group sparsity

Abstract: This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivated by the observation that in some practical sparse data the nonzero coefficients are often not random but tend to be clustered. Intuitively, better results can be achieved in these cases by reasonably utilizing both clustering and sparsity priors. Motivated by this idea, we have developed a new greedy sparse recovery algorithm, which prunes data residues in the iterative process according to both sparsity and group clustering priors rather than only sparsity as in previous methods. The proposed algorithm can recover stably sparse data with clustering trends using far fewer measurements and computations than current state-of-the-art algorithms with provable guarantees. Moreover, our algorithm can adaptively learn the dynamic group structure and the sparsity number if they are not available in the practical applications. We have applied the algorithm to sparse recovery and background subtraction in videos. Numerous experiments with improved performance over previous methods further validate our theoretical proofs and the effectiveness of the proposed algorithm.

Theoretical Foundations for Enhancing Social Connectedness in Online Learning Environments

Abstract: Group social structure provides a comfortable and predictable context for interaction in learning environments. Students in face‐to‐face learning environments process social information about others in order to assess traits, predict behaviors, and determine qualifications for assuming particular responsibilities within a group. In online learning environments, however, negotiating social information and maintaining social connectedness can pose challenges for participants. Nonverbal strategies one typically uses for enhancing communication and overcoming ambiguity – such as an approving smile or a questioning brow – must be approached differently while learning online where fewer sensory communication channels are typically available. We present the theoretical foundation for how social information processing and group structure theories may be combined to assist instructional designers in further examining the social system perceived by the online learner. We propose a framework for thinking more system...

Experimental Behavior of High Strength Square Concrete-Filled Steel Tube Beam-Columns

Abstract: The flexural force-deformation behavior of high strength square concrete-filled steel tube (CFT) beam-columns was experimentally investigated. The parameters in the study included the width-to-thic...