Dynamic capabilities approach

Chapter 19 Supply Chain Security A Dynamic Capabilities Approach... 

One interesting new field in the area of optical spectroscopy is near-field scaiming optical microscopy, a teclmique that allows for the imaging of surfaces down to sub-micron resolution and for the detection and characterization of single molecules [, M]- Wlien applied to the study of surfaces, this approach is capable of identifying individual adsorbates, as in the case of oxazine molecules dispersed on a polymer film, illustrated in figure Bl.22,11 [82], Absorption and emission spectra of individual molecules can be obtamed with this teclmique as well, and time-dependent measurements can be used to follow the dynamics of surface processes. 

Feedforward control can also be applied by multiplying the liquid flow measurement—after dynamic compensation—by the output of the temperature controller, the result used to set steam flow in cascade. Feedforward is capable of a reduction in integrated error as much as a hundredfold but requires the use of a steam-flow loop and dynamic compensator to approach this. 

Depth-sensing nanoindentation is one of the primary tools for nanomechanical mechanical properties measurements. Major advantages to this technique over AFM include (1) simultaneous measurement of force and displacement (2) perpendicular tip-sample approach and (3) well-modeled mechanics for dynamic measurements. Also, the ability to quantitatively infer contact area during force-displacement measurements provides a very useful approach to explore adhesion mechanics and models. Disadvantages relative to AFM include lower force resolution, as well as far lower spatial resolution, both from the larger tip radii employed and a lack of sample positioning and imaging capabilities provided by piezoelectric scanners. 

Dynamic simulation with discrete-time events and constraints. In an effort to go beyond the integer (logical) states of process variables and include quantitative descriptions of temporal profiles of process variables one must develop robust numerical algorithms for the simulation of dynamic systems in the presence of discrete-time events. Research in this area is presently in full bloom and the results would significantly expand the capabilities of the approaches, discussed in this chapter. 

Experimental probes of Born-Oppenheimer breakdown under conditions where large amplitude vibrational motion can occur are now becoming available. One approach to this problem is to compare theoretical predictions and experimental observations for reactive properties that are sensitive to the Born-Oppenheimer potential energy surface. Particularly useful for this endeavor are recombinative desorption and Eley-Rideal reactions. In both cases, gas-phase reaction products may be probed by modern state-specific detection methods, providing detailed characterization of the product reaction dynamics. Theoretical predictions based on Born-Oppenheimer potential energy surfaces should be capable of reproducing experiment. Observed deviations between experiment and theory may be attributed to Born-Oppenheimer breakdown. 

FUN tool is a new integrated software based on a multimedia model, physiologically based pharmacokinetic (PBPK) models and associated databases. The tool is a dynamic integrated model and is capable of assessing the human exposure to chemical substances via multiple exposure pathways and the potential health risks (Fig. 9) [70]. 2-FUN tool has been developed in the framework of the European project called 2-FUN (Full-chain and UNcertainty Approaches for Assessing Health Risks in FUture ENvironmental Scenarios www.2-fun.org). 

Advances in computational capability have raised our ability to model and simulate materials structure and properties to the level at which computer experiments can sometimes offer significant guidance to experimentation, or at least provide significant insights into experimental design and interpretation. For self-assembled macromolecular structures, these simulations can be approached from the atomic-molecular scale through the use of molecular dynamics or finite element analysis. Chapter 6 discusses opportunities in computational chemical science and computational materials science. 

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