Property hierarchy

Property Data fretworks. These include the Materials Property Data Network, Inc. (MPD) (57) and Chemical Property Data Network (CPDN) and are available on STN. These networks provide menu access to numeric data on the performance of different materials and chemicals. Tables 5 and 6 summarize using the numeric files available on STN. NUMERIGUIDE is a data directory and property hierarchy support file produced by STN it contains information on all properties available in the numeric files on STN. 

Fi(i. 7. Property hierarchy and common difference-elimination methods. 

A number of experimental chemical process synthesis procedures have been developed with a hierarchical architecture based on both the hierarchical structure of the chemical innovation process and the physical property hierarchy. Examples include PIP (Kirkwood et al, 1988) and BALTAZAR (Mahalec and Motard, 1977). This hierarchical approach is also evident in the Pinch Technology Onion Diagram (Linnhoff and Ahmad, 1983). The hierarchical approach is also the foundation for the two early textbooks on process synthesis methodology (Rudd et al, 1973 Douglas, 1988). 

Schema (RDFS). RDF(S) provides language constructs to formulate simple graphs containing class and property hierarchies as well as property restrictions. With its formal semantics, RDF(S) leaves no room for interpretation of what conclusions can be drawn from a given graph, thereby providing standard inference mechanisms for any RDF(S)-compliant graph. RDF(S) can, hence, be used as a language to model simple ontologies, but provides limited expressive means and is not suitable to formulate more complex knowledge (Hitzler et al. 2010). Examples for knowledge that cannot be formulated in RDF(S) are the phrases Each Module consists of at least one component and Components are either actuators or sensors.

Table 5 Upper-level Property Hierarchy of CrossFire Chemical Data...

At deeper levels, the database fields become more and more specific, and run into several hundreds. As an example, the upper levels of the property hierarchy are shown in Table 5. 

Another type of information is represented by the descriptors in the fields Field Availability (FA), Property Hierarchy (PH), Preferred Property Names (PPN), and Controlled Terms (CT and CTM). All these fields contain information on the availability of properties in the form of bound phrases. If data are available for a certain field of a given substance the field name and the corresponding field qualifier (search field code) are indexed in FA. 

The main qualifier LDEN is also used to display the data for the property liquid density. In addition to the physical parameters there are two other columns which contain literature references and notes. For the display of the factual information one may use one of the following formats QRD (default), (PROP) = main qualifier, ALL, or one of the display format, which contain the property in question (see property hierarchy in Figure 7). The design of reaction information follows the same rules as the design for physical properties. Here, there is no main entity but rather a set of parameters such as the starting materials, the products, and the various reaction conditions. 

When investigating, whether certain data are available related to a certain substance or a substance class, the field Property Hierarchy (PH) can help to provide all relevant names and field acronyms. The easiest way to find out is an EXPAND command (Fig. 152) ... 

Numerical properties may all be searched for using numerical operators (<, <=, >, >=, =). Every field has a singular unit, retrievable in the manual The Beilstein File - Database Description. As a supplement to the field Property Hierarchy (PH), the subfield Keywords (XYZ.KW) is usable. It gives out descriptions of given numeric data. The following keywords are used ... 

If a Pfaff differential expression DF = Xdx + Tdy+Zdz has the property that every arbitrary neighbourhood of a point P(x, y, z) contains points that are inaccessible along a path corresponding to a solution of the equation DF = 0, then an integrating denominator exists. Physically this means that there are two mutually exclusive possibilities either a) a hierarchy of non-intersecting surfaces (x,y, z) = C, each with a different value of the constant C, represents the solutions DF = 0, in which case a point on one surface is inaccessible... 

The representation of molecular surfaces, including the display of molecular surface properties, can be regarded as the next level of this hierarchy, but will be addressed in Sections 2,10 and 2,11 in this volume. 

In fact, there is a hierarchy in calculating molecular properties by additivity of atomic, bond, or group properties, as was pointed out some time ago by Benson [1, 2]. The larger the substructures that have to be considered, the larger the number of inaements that can be derived and the higher the accuracy in the values obtained for a molecular property. 

As is well recognized, various macroscopic properties such as mechanical properties are controlled by microstructure, and the stability of a phase which consists of each microstructure is essentially the subject of electronic structure calculation and statistical mechanics of atomic configuration. The main subject focused in this article is configurational thermodynamics and kinetics in the atomic level, but we start with a brief review of the stability of microstructure, which also poses the configurational problem in the different hierarchy of scale. 

In the case of liquid crystals in particular, vibrational properties reflect very directly the complex hierarchy of the structure and bonding problem in these materials. For example, in a single mesogenic molecule vibrational frequencies range from about 10 cm to over 3000 cm which arise from the very wide range of force constants present [79]. 

A typical feature of expert systems that support frames is inheritance. Frames can be organized in a hierarchical structure. They can inherit properties (attributes) from frames that are higher in the hierarchy. The latter are therefore called parent frame and the former child frame. There are many varieties of the inheritance principle. Frames can have only one parent frame (simple inheritance) or may have multiple parent frames (multiple inheritance). All attributes can be inherited (full inheritance) or only a few, selected by the knowledge engineer, may be inherited (partial inheritance) by the child frames. An example of a simple inheritance organization of frames is shown in Table 43.1. The frame Organic Compound is the parent frame. The frames Ester and Acids are child frames of Organic Compound . A typical example of inheritance is instantiation. The frame Acetic acid is a child of Acids and, since no extra attributes are added, it is also an instantiation. 

As we saw in the previous sections, inclusion compounds have many structural properties which relate them to other systems based on the hierarchy of non-bound interactions, like enzymes or enzyme-substrate complexes. As a matter of fact, most of the so-called artificial enzymes are based on well-known host molecules (e.g. P-cyclodextrin) and are designed to act partly on such bases 108>109). Most of these models, however, take advantage of the inclusion (intra-host encapsulation) phenomena. Construction of proper covalently bound model molecules is a formidable task for the synthetic chemistuo>. Therefore, any kind of advance towards such a goal is welcomed. 

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