Sampling, materials discovery

While producing samples more efficiently is one aspect which can lead to more efficient materials discovery efforts, efficient characterization is also needed. In his 1970 paper, [1] Hanak spoke to the issue of materials testing and evaluation. He discussed advances in the measurement of a number of chemical, physical and mechanical properties, measurements which must be tailored to the specific materials problem under investigation. Ultimately it was difficulties in characterization that limited the impact of these approaches. Computers were not yet commonly available, and automated sample evaluation methods remained to be developed. 

While these more efficient materials synthesis approaches were exploited in some laboratories, traditional one-sample-at-a-time methods have persisted generally. Often this is appropriate because the intense testing regimens that the samples are being subjected to take much longer than the synthetic step. Improving the speed of the synthetic step alone would have little effect on the overall progress of materials discovery. 

Microarrays have become robust, reliable research tools that enable researchers to screen for a multitude of parameters using minimal amounts of sample material. The acceptance of protein microarrays is growing constantly they have already been demonstrated to be useful tools in disease-related biomarker discovery. In addition, protein microarrays have been introduced into clinical trials in order to investigate the potential adverse effects of drug candidates. Depending on the number of validated disease-specific biomarkers, as well as on their therapeutic relevance, such assays are performed either on a protein microarray or a bead-based platform. 

Combinatorial chemistry differs from usual Monte Carlo simulations in that several simultaneous searches of the variable space are carried out. That is, in a typical combinatorial chemistry experiment, several samples, e.g., 10,000, are synthesized and screened for figure of merit at one time. With the results of this first round, a new set of samples can be synthesized and screened. This procedure can be repeated for several rounds, although current materials discovery experiments have not systematically exploited this feature. 

The technology for materials discovery is still in the developmental stage, and future progress can still be influenced by theoretical considerations. In this spirit, I assume that the composition and noncomposition variables of each sample can be changed independently, as in spatially addressable libraries (Akporiaye et al., 1998 Pirrung, 1997). This is significant, because it allows great flexibility in how the space can be searched with a limited number of experimental samples. 

Current experiments uniformly tend to perform a grid search on the composition and noncomposition variables. It is preferable, however, to choose the variables statistically from the allowed values. It is also possible to consider choosing the variables in a fashion that attempts to maximize the amount of information gained from the limited number of samples screened, via a quasi-random, low-discrepancy sequence (Niederreiter, 1992 Bratley et al., 1994). Such sequences attempt to eliminate the redundancy that naturally occurs when a space is searched statistically, and they have several favorable theoretical properties. An illustration of these three approaches to materials discovery library design is shown in Fig. 1. 

The points to be sampled in materials discovery are the allowed values of the composition and noncomposition variables. Typically, the composition variables are specified by the mole fractions. Since the mole fractions sum to one, sampling on these variables requires special care. 

The space of composition and noncomposition variables to search in materials discovery experiments can be forbiddingly large. Yet, by using Monte Carlo methods, one can achieve an effective search with a limited number of experimental samples. 

Gr. technetos, artificial) Element 43 was predicted on the basis of the periodic table, and was erroneously reported as having been discovered in 1925, at which time it was named masurium. The element was actually discovered by Perrier and Segre in Italy in 1937. It was found in a sample of molybdenum, which was bombarded by deuterons in the Berkeley cyclotron, and which E. Eawrence sent to these investigators. Technetium was the first element to be produced artificially. Since its discovery, searches for the element in terrestrial material have been made. Finally in 1962, technetium-99 was isolated and identified in African pitchblende (a uranium rich ore) in extremely minute quantities as a spontaneous fission product of uranium-238 by B.T. Kenna and P.K. Kuroda. If it does exist, the concentration must be very small. Technetium has been found in the spectrum of S-, M-, and N-type stars, and its presence in stellar matter is leading to new theories of the production of heavy elements in the stars. 

Were all of these newly discovered substances also new elements This question would not be answered for some years but there was a flurry of other major discoveries to keep the protagonists occupied. Pierre Curie discovered that radioactivity released large quantities of heat (Curie and Laborde 1903) which appeared mysterious—as if the heat was coming from nowhere. This discovery provided an extra heat source for the Earth and reconciled the estimates of a very old Earth, based on geological estimates, with the young age calculated by Lord Kelvin from cooling rates. The year 1903 also witnessed the first demonstration that a-decay released He (Ramsay and Soddy 1903). The build up of He was soon put to use to date geological materials, initially by Rutherford in 1905 who calculated the first ever radiometric age of 500 Myr for a pitchblende sample, and then by Strutt who examined a wide variety of minerals (Strutt... 

The discovery of the average metal-rich nature of planet-harbouring stars with regard to disc stars (i.e. [1],[2], [3]) has revealed the key role that metallicity plays in the formation and evolution of planetary systems. If the accretion processes were the main responsible for the iron excess found in planet host stars, volatile abundances should show clear differences in stars with and without planets, since volatiles (with low Tc) are expected to be deficient in accreted materials [4]. Previous studies of the abundance trends of the volatiles N, C, S and Zn [5, 6] have obtained no anomalies for a large sample of planet host stars. 

Experiments using the DCC approach aimed at the discovery of improved phosphor materials have also been described. [9] In this case, samples are evaluated optically, an approach well suited to direct comparisons of large numbers of samples, although it is somewhat difficult to compare the results to the optical properties of bulk materials. Further spectroscopic evaluations of individual elements of the sample array are also easily accomplished by a variety of approaches including scanning fiber techniques. One concern in studies of phosphors is the sensitivity of the optical behavior including fluorescence intensity to processing effects such as details of the microstructure or surface preparation. 

It should be noted that the ytterbium listed above was a mixture discovered in the mineral erbia by de Marignac in 1878 and not the neoytterbium/aldebaranium element renamed ytterbium that was foimd in the mineral ytterbia. The columbium was a mixture found in the mineral samarskite and was not the present day columbium/niobium. The ionium listed above was a mixture of terbium and gadolinium that was found in the mineral yttria and does not refer to °Th. Finally, the neptunium refers to material fovmd in niobium/tantalum minerals and does not refer to the 1940 discovery of the trans-uranium element produced via a neutron capture reaction on a uranium sample. 

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