Frontispiece: Cationic Tetrylene-Iron(0) Complexes: Access Points for Cooperative,Reversible Bond Activation and Open-Shell Iron(−I) Ferrato-Tetrylenes

The open-shell cationic stannylene-iron(0) complex 4 ( 4 =[^PhiPDippSn⋅Fe⋅IPr]⁺; ^PhiPDipp={[Ph₂PCH₂Si(ⁱPr)₂](Dipp)N}; Dipp=2,6-ⁱPr₂C₆H₃; IPr=[(Dipp)NC(H)]₂C:) cooperatively and reversibly cleaves dihydrogen at the Sn−Fe interface under mild conditions (1.5 bar, 298 K), in forming bridging hydrido-complex 6 . The One-electron oreduction of the related Ge^II−Fe⁰ complex 3 leads to oxidative addition of one C−P linkage of the ^PhiPDipp ligand in an intermediary Fe^−I complex, leading to Fe^I phosphide species 7 . One-electron reduction reaction of 4 gives access to the iron(−I) ferrato-stannylene, 8 , giving evidence for the transient formation of such a species in the reduction of 3 . The covalently bound tin(II)-iron(−I) compound 8 has been characterised through EPR spectroscopy, SQUID magnetometry, and supporting computational analysis, which strongly indicate a high localization of electron spin density at Fe^−I in this unique d⁹-iron complex.     

Simultaneous correction of the influence of skin color and fat on tissue spectroscopy by use of a two-distance fiber-optic probe and orthogonalization technique

We have demonstrated simultaneous correction for the optical interference of skin and fat in tissue spectra by using a two-distance fiber-optic probe. We obtained the correction by orthogonalizing the spectra collected at a long source-detector distance (SD) to the spectra collected at a short SD and mapped to the long SD space. The method was validated in tissuelike three-layer phantoms as well as preliminarily in human tissue. After the correction, a partial-least-squares model of the phantoms showed enhanced prediction performance.     

Spectral tolerance determination for multivariate optical element design

Recent reports from our laboratory have described a method for all-optical multivariate chemometric prediction from optical spectroscopy. The concept behind this optical approach is that a spectral pattern (a regression vector) can be encoded into the spectrum of an optical filter. The key element of these measurement schemes is the multivariate optical element (MOE), a multiwavelength interference-based spectral discriminator that is tied to the regression vector of a particular measurement. The fabrication of these MOEs is a complex operation that requires precise techniques. However, to date, no quantitative means of determining the allowable design/ manufacturing errors for MOEs has existed. The purpose of the present report is to show how the spectroscopy of a sample is used to define the accuracy with which MOEs must be designed and manufactured. We conclude this report with a general treatment of spectral tolerance and a worked example. The worked example is based on actual experimental measurements. We show how the spectral bandpass is defined operationally in a real problem, and how the statistics of the theoretical regression vector influence both the bandpass and the minimum tolerances. In the experimental example, we demonstrate that tolerances range continuously between 1 (totally tolerant) to approximately 10^–3 (0.1% T) in this problem. Received: 21 August 2000 / Revised: 30 October 2000 / Accepted: 4 November 2000     

Spectral tolerance determination for multivariate optical element design

Recent reports from our laboratory have described a method for all-optical multivariate chemometric prediction from optical spectroscopy. The concept behind this optical approach is that a spectral pattern (a regression vector) can be encoded into the spectrum of an optical filter. The key element of these measurement schemes is the multivariate optical element (MOE), a multiwavelength interference-based spectral discriminator that is tied to the regression vector of a particular measurement. The fabrication of these MOEs is a complex operation that requires precise techniques. However, to date, no quantitative means of determining the allowable design/ manufacturing errors for MOEs has existed. The purpose of the present report is to show how the spectroscopy of a sample is used to define the accuracy with which MOEs must be designed and manufactured. We conclude this report with a general treatment of spectral tolerance and a worked example. The worked example is based on actual experimental measurements. We show how the spectral bandpass is defined operationally in a real problem, and how the statistics of the theoretical regression vector influence both the bandpass and the minimum tolerances. In the experimental example, we demonstrate that tolerances range continuously between 1 (totally tolerant) to approximately 10(-3) (0.1% T) in this problem.     

Multivariate analysis of near-infrared spectra using the G-programming language

"Real-time" chemometrics as envisioned by the union of instrument control, data acquisition, and chemometric analysis with a single software platform can provide substantial benefits to manufacturing concerns that require process control. Some of these benefits include faster generation of information and improved quality control. This paper describes a series of chemometric routines written in LabVIEW and demonstrates their use in predicting six properties of diesel fuel. In particular, near-infrared spectral data were used to predict the boiling point at 50% recovery, cetane number, density, freezing temperature, total aromatics, and viscosity for a series of diesel fuels.     

Spectroelectrochemical study of the oxidative doping of polydialkylphenyleneethynylene using iterative target transformation factor analysis

Iterative target transformation factor analysis (ITTFA) was used to determine the spectra of the individual species generated during the oxidative p-doping of films of poly(para-phenyleneethynylene) (PPE). UV-visible spectra of PPE films on transparent electrodes were obtained in-situ during an anodic sweep. ITTFA identified 4 species present during the oxidation, which we assign as neutral polymer, polaron species, bipolaron species, and a species formed by further bipolaron reaction. The region of electrochemical stability for each of these species was identified and their potential-dependent profiles were obtained. This work is the first deconvolution of conjugated polymer spectroelectrochemistry.