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This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems.

A selected survey of aerodynamic drag reduction at high speed is presented. The dimensionless governing parameters are described for energy deposition in an ideal gas. The types of energy deposition are divided into two categories. First, energy deposition in a uniform supersonic flow is discussed. Second, energy deposition upstream of a simple aerodynamic body is examined. Both steady and unsteady (pulsed) energy deposition are examined for both categories, as well as the conditions for the formation of shock waves and recirculation regions. The capability of energy deposition to reduce drag is demonstrated experimentally. Areas for future research are briefly discussed. Nomenclature A = cross-sectional area C D = drag coefficient c p = specific heat at constant pressure D = diameter of body d = diameter of filament G,G = spatial distribution functions for energy deposition I = impulse L = streamwise length ' = characteristic length M = freestream Mach number _ m = mass flow rate P = power p = pressure Q = energy added per unit volume per time Q o = magnitude of energy deposition (energy per unit volume per time) Q T = energy deposited in V in time interval e q = energy added per unit mass per time q o = magnitude of energy deposition (energy per unit mass per time) q T = energy per mass deposited in V in time interval e R = gas constant for air T = temperature T = temporal distribution function for energy deposition U = freestream velocity V = volume v = velocity = f = 1 = ratio of specific heats E f = energy added e , i , L = dimensionless time scales ", " 0 = energy deposition parameters = efficiency of energy deposition = density $ = ratio of energy added to energy required to choke the flow = dimensionless time parameter e = duration of energy pulse Subscripts f = filament 1 = freestream I. Overview I N RECENT years, there has been intense activity in developing a fundamental understanding and practical applications of flow control at high speed using energy deposition. This interest is reflected in numerous conferences and workshops, including the Weakly Ionized Gas Workshops [1-8], the St. Petersburg Workshops [9-12], and the Institute for High Temperatures Workshops [13][14][15][16][17][18][19]. The scope of this research is broad. It encompasses a wide variety of energy deposition techniques (e.g., plasma arcs, laser pulse, microwave, electron beam, glow discharge, etc.) and a wide range of applications (e.g., drag reduction, lift and moment enhancement, improved combustion and mixing, modification of shock structure, etc.).The objective of this paper is to provide a selective survey of research on aerodynamic drag reduction at high speed using energy deposition. The research is reviewed principally from the viewpoint of ideal gas dynamics to elucidate the thermal effects of energy deposition on supersonic flow. In general, nonideal gas effects are not considered (except insofar as they naturally occur in the experiments cited herein) and are the topic of a future survey.The remainder of this paper is d...

Summary: The advent of high‐throughput combinatorial synthesis techniques in drug discovery has stimulated efforts to apply these techniques to the discovery of biomaterials. To be of practical utility, combinatorial approaches to biomaterials design require (i) the availability of parallel synthesis techniques to generate libraries of polymers, (ii) efficient assays for the rapid characterization of biorelevant material properties, and (iii) computational methods to efficiently model different biological responses in the presence of polymers. Here we report the integration of these methodologies and illustrate the potential of this approach to accelerate the development of new biomaterials. The parallel synthesis of a library of 112 biodegradable polyarylates has been reported previously. This library was used to develop efficient screening techniques to determine biorelevant polymer properties (fibrinogen adsorption, gene expression in macrophages, growth of fetal rat lung fibroblasts (RLFs)). A Surrogate (semiempirical) Model was developed (i) to determine molecular‐scale polymer properties that correlate to various biological responses, and (ii) to predict fibrinogen adsorption and RLF growth on polymeric surfaces. For 38 out of 45 polymers, the model predicted the amount of fibrinogen adsorbed correctly within the error of the experimental measurements. The growth of rat lung fibroblasts was correctly predicted by the model for 41 out of 48 polymers. The correlation factor between the model's predicted values and the experimentally determined data was 0.54 ± 0.09 and 0.69 ± 0.12 for fibrinogen adsorption and RLF growth, respectively. The results presented here demonstrate the utility of combinatorial and computational approaches for the rational design of polymers for biomedical applications.Design of the library of polyarylates, which are copolymers of a diacid and a diphenol. Chemical diversity was created by variations in the structure of the diacid (marked as “Y”) and the pendent chain (marked as “R”).magnified imageDesign of the library of polyarylates, which are copolymers of a diacid and a diphenol. Chemical diversity was created by variations in the structure of the diacid (marked as “Y”) and the pendent chain (marked as “R”).

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