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Introduction to Heterogeneous Catalysis in Organic Transformation
Published in Varun Rawat, Anirban Das, Chandra Mohan Srivastava, Heterogeneous Catalysis in Organic Transformations, 2022
Garima Sachdeva, Gyandshwar Kumar Rao, Varun Rawat, Ved Prakash Verma, Kaur Navjeet
The complex nature of heterogeneous catalysts prevents their analysis and characterization at a molecular level, making their development difficult through structure–reactivity relationships. Additionally, the traditional heterogeneous catalysts are less reactive and show poor selectivity in a chemical reaction. In order to overcome these issues, homogeneous catalysts are often embedded on solid surfaces to add heterogeneity in their nature. This approach brings features of both homogeneous (selectivity and reactivity) and heterogeneous (reproducibility) catalysts together in one catalyst, which greatly enhance the outcome of a reaction. Heterogeneity can be obtained by immobilizing catalysts on the solid surface via surface processes like physisorption or chemisorption [8].
Flow and Transport in Heterogeneous Formations: Single Realization Approach
Published in Amro M.M. Elfeki, Gerard J.M. Uffink, Frans B.J. Barends, Groundwater Contaminant Transport, 2017
Amro M.M. Elfeki, Gerard J.M. Uffink, Frans B.J. Barends
Most of the recently developed stochastic theories and applications do not take into account the geometrical architecture of the underground reservoir. More reliable predictions of transport in geological media require the integration of the effects from many different scales. The heterogeneity may be discrete (e.g. geometrical heterogeneity), continuous (e.g. parametric variability) or compound (geometrical and parametric variability).
A holistic approach to aligning geospatial data with multidimensional similarity measuring
Published in International Journal of Digital Earth, 2018
Li Yu, Peiyuan Qiu, Xiliang Liu, Feng Lu, Bo Wan
Abundant geospatial data are now available from a wealth of sources, such as volunteered geographic information (VGI; Geonames1, OpenStreetMap2), open digital gazetteers (ADL3, DIVA-GIS4) and a variety of authoritative geospatial databases (e.g. a topographic map, the national highway network). However, these geospatial data are generally heterogeneous for the following reasons. (1) Lexical heterogeneity. Different organizations publish their own geographical data in different terminologies (Janowicz et al. 2010). For example, the same concept or place name may be expressed with different vocabularies, or the same vocabulary has different meanings under different contexts (Du et al. 2013). (2) Structural heterogeneity. Geographical data are published under different standards and protocols, making the same domain being modeled with different storage formats, spatial granularities and taxonomic hierarchies (Yu and Liu 2015), and leading to various geospatial data structures. (3) Spatial heterogeneity. Geometric shapes of the same location from different data sources may be completely different. For example, a location may be represented as a polygon in a geospatial database, but may also be expressed as a point of interest in a navigation-oriented OpenStreetMap database (Delgado, Mercedes Martínez-González, and Finat 2013).
Interrelationships between influential factors and behavioral intention with regard to autonomous vehicles
Published in International Journal of Sustainable Transportation, 2019
Heterogeneity refers to whether a quality or state consists of dissimilar or diverse characteristics. Distinct population groups tend to show dissimilar intentions and/or behavior and, if necessary, should be treated differently. To identify heterogeneous groups, both observed and unobservable variables can be used.
Interrelationships between behaviour intention and its influential factors for consumers of motorcycle express cargo delivery service
Published in Transportmetrica A: Transport Science, 2019
Huey-Kuo Chen, Huey-Wen Chou, Sam-Chu Hung
Heterogeneity refers to the quality or state of consisting of dissimilar or diverse characteristics. Distinct population groups tend to show dissimilar intention or behaviour and, if needed, should be treated differently. To identify heterogeneous groups, both observed and unobserved variables can be used.