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物品 #:
246347252
Categorization and Simple Graph Theory of Golden Clusters
物品 #:
246347252
HKD 678
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現在訂購，約可在下列時間收貨： Sunday, 十月 18
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The application of skeletal numbers is quite easy, fast and precise.
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What Stands Out
Advanced Categorization
Utilizes innovative methods for categorizing golden clusters, enhancing data organization and analysis efficiency, making it easier for researchers to draw insights.
Graph Theory Application
Incorporates simple graph theory to visualize relationships among clusters, facilitating better understanding and communication of complex data structures.
User-Friendly Interface
Designed with an intuitive interface, allowing users of all backgrounds to navigate and utilize the system effectively, reducing learning time and increasing productivity.
產品詳情
- The book introduces the analysis and categorization of golden clusters using the 14N/4N method and its skeletal numbers for the first time. The application of skeletal numbers is quite easy, fast and precise. Initially the method which has been found to be very successful in categorizing clusters of other skeletal elements is well demonstrated using the osmium fragments and clusters. It is then applied to clusters of gold with some elements from the p-block elements. The analysis of the golden clusters with the series method reveals that the clusters obey the 4N series principle and are highly capped with nuclei comprising mainly of one or two elements in the nuclei. A small number of clusters indicate the absence of skeletal elements in the nucleus. A cluster with such a nucleus has been referred to as having a black-hole. With more understanding of the 4N series method a simple graph theory concept has been introduced to sketch isomeric graphical structures of the clusters as well as being utilized to hypothetically distribute the ligands around the skeletal elements.
| Publisher | LAP LAMBERT Academic Publishing |
| Publication date | 3 Sept. 2018 |
| Language | English |
| Print length | 120 pages |
| ISBN-10 | 3659753254 |
| ISBN-13 | 978-3659753251 |
| Dimensions | 15.01 x 0.71 x 22 cm |
| Item Weight | 1 lbs (450 grams) |
Who Should Buy?
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Academic Researchers
Ideal for researchers focusing on graph theory applications and its implications in categorization tasks across various domains.
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Data Analysts
Data analysts can leverage the principles in this product to enhance their data modeling and visualization techniques.
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Students
Students studying mathematics or computer science can benefit greatly from simplified concepts and applications of graph theory.
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Casual Learners
Not ideal for casual learners seeking light reading or basic overviews without in-depth mathematical understanding.
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Chemistry Editorial Review
Categorization And Simple Graph Theory Of Golden Clusters is an academic publication by LAP LAMBERT Academic Publishing that delves into graph theory with a focus on categorization. This resourceful book, published on 3 Sept. 2018, spans 120 pages, offering comprehensive insights for both students and professionals in mathematics and related fields. Its dimensions of 15.01 x 0.71 x 22 cm make it a compact academic resource, and its ISBNs provide easy identification for libraries and bookstores. The English language text is designed to enhance understanding of complex graph theory concepts, making it a valuable addition to any mathematical library.
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優點
- Well-researched content about graph theory concepts
- 120 pages of in-depth academic information
- Compact size for easy handling and storage
- Published by a reputable academic publisher
- ISBNs for easy reference and cataloging
缺點
- Limited availability of user reviews for insights
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HKD 678
現在訂購，約可在下列時間收貨： Sunday, 十月 18
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特色和優勢
- Innovative analysis method for categorizing golden clusters.
- Introduces the 14N/4N method and skeletal numbers for accurate results.
- Successfully demonstrates categorization using osmium fragments.
- Applies findings to gold clusters alongside p-block elements.
- Shows clusters follow the 4N series principle with simplified graph theory.
- Visualizes isomeric structures and ligand distribution effectively.
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