A search for the best and most complete description of line-edge roughness (LER) is presented. The root mean square (rms) value of the edge (sigma value) does not provide a complete characterization of LER since it cannot give information about its spatial complexity. In order to get this missing information, we analyze the detected line edges as found from scanning electron microscope (SEM) image analysis [see Paper I: G. P. Patsis et al., J. Vac. Sci. Technol. B 21, 1008 (2003)] using scaling and fractal concepts. It is shown that the majority of analyzed experimental edges exhibit a self-affine character and thus the suggested parameters for the description of their roughness should be: (1) the sigma value, (2) the correlation length ξ, and (3) the roughness exponent α. The dependencies of ξ and α on various image recording and analysis parameters (magnification, resolution, threshold value, etc.) are thoroughly examined as well as their implications on the calculation of sigma when it is carried out by averaging over the sigmas of a number of segments of the edge. In particular, ξ is shown to be connected to the minimum segment size for which the average sigma becomes independent of the segment size, whereas α seems to be related to the relative contribution of high frequency fluctuations to LER.

Line edge (or width) roughness (LER or LWR) of photoresists lines constitutes a serious issue in shrinking the critical dimensions (CD) of the gates to dimensions of a few tens of nanometers. In this article, we address the problem of the reliable LER characterization as well as the association of LWR with the CD variations. The complete LER characterization requires more parameters than the rms value σ since the latter neglects the spatial aspects of LER and does not predict the dependence on the length of the measured line. The further spatial LER descriptors may be the correlation length ξ and the roughness exponent α, which can be estimated through various methods. One aim of the present work is to perform a systematic comparative study of these methods using model edges generated by a roughness algorithm, in order to show their advantages and disadvantages for a reliable and accurate determination of the spatial LER parameters. In particular, we compare the results from (a) the study of the height–height correlation function (HHCF), (b) the Fourier [or power spectrum (PS)] analysis, and (c) the variation of rms value σ with measured line edge L [σ(L) curve]. It is found that the HHCF can be considered approximately a rescaled version of σ(L) and that the value of σ becomes almost independent of the measured edge length for lengths larger than ten times the correlation length. As regards the PS, it is shown that the finite length of the edge may harmfully affect the reliable estimation of α and ξ. Finally, we confirm theoretically and generalize an experimental observation [Leunissen et al., Microelectron. Eng. (to be published)] regarding the relationship between LWR and the σ of the CD variations within a die of a wafer. It is shown that they behave in a complimentary way as line length increases so that the sum of their squares remains constant and equal to the square of the LWR σ of the infinite line.

The synthesis and biological evaluation of new M(I)(CO)3(NNO) (M = Re, 99mTc) complexes attached to the antitumor agent 2-(4-aminophenyl)benzothiazole are reported. The fluorescent rhenium complex enters MCF-7 breast cancer cells but does not enter normal HFFF-2 and MRC-5 cells. The analogous radioactive 99mTc complex produces fast blood and soft tissue clearance when administered to healthy mice. These complexes are promising candidates for developing radiopharmaceuticals for imaging (99mTc) and targeted radiotherapy (186Re, 188Re) of breast cancer.

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An off-line image analysis algorithm and software is developed for the calculation of line-edge roughness (LER) of resist lines, and is successfully compared with the on-line LER measurements. The effect of several image-processing parameters affecting the fidelity of the off-line LER measurement is examined. The parameters studied include the scanning electron microscopy magnification, the image pixel size dimension, the Gaussian noise-smoothing filter parameters, and the line-edge determination algorithm. The issues of adequate statistics and appropriate sampling frequency are also investigated. The advantages of off-line LER quantification and recommendations for the on-line measurement are discussed. Having introduced a robust algorithm for edge-detection in Paper I, Paper II [V. Constantoudis et al., J. Vac. Sci. Technol. B 21, 1019 (2003)] of this series introduces the appropriate parameters to fully quantify LER.