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College of Arts and Sciences


Faculty and Staff

Stephen L. Morgan

Title: Professor / Analytical
Bioanalytical / Environmental / Forensics / Polymer / Spectroscopy/ Theoretical/Computational
Department: Chemistry and Biochemistry
College of Arts and Sciences
E-mail: morgansl@mailbox.sc.edu
Phone: 803-777-2461
Fax: 803-777-9521
Office: Office: GSRC 208
Lab: GSRC 211, 803-777-0272
Lab 2: GSRC 212, 803-777-1176
Resources: CV [pdf]
All Publications 
Department of Chemistry and Biochemistry
Stephen Morgan

Education

B.S., 1971, Duke University
M.S., 1974, Emory University
Ph.D., 1975, Emory University

Honors and Awards

American Association for the Advancement of Science Fellow, 2016; American Chemical Society, South Carolina Section, Outstanding Chemist Award, 2011; Distinguished Undergraduate Research Mentor, University of South Carolina, 2007.

Research Interests

Analytical chemistry; Forensic analytical chemistry; rapid spectroscopic imaging of biological stains; noninvasive spectroscopic detection of magnetic tape degradation; chemometrics; sample preparation and rapid analysis for diverse forensic, biological, and environmental samples.

Recent research has involved spectroscopy, liquid chromatography, and mass spectrometry for forensic fiber analysis and analytical toxicology, thermal reflectance imaging for biological stains at crime scenes, and noninvasive methods for detection of degraded audio tapes using infrared spectroscopy. These projects are guided by experimental design, optimization, and multivariate pattern recognition and machine learning approaches. Modern statistical problems involving large data sets have benefited from the development of large-scale methods for inference that outperform conventional frequentist-based methods by taking advantage of empirical Bayes strategies that employ elements of both “Frequentism” and “Bayesianism”. Forensic imaging in the infrared. Identification of biological fluids on materials of evidentiary value (e.g., clothing from a crime scene) is driven by the fact that even minute traces can have probative value because of trace DNA profiling. Luminol spraying is a sensitive, but risks diluting and damaging DNA, while alternative light sources are not particularly sensitive. In collaboration with the Myrick group, we are designing and validating imaging techniques for rapid visualization of biological residues. Detection is based on filtered and processed reflectance measurements of absorption from surface stains. Current results extend detection limits to more than 1000×diluted stains. This effort is being extended to identification of other materials at crime scenes including other biological fluids, illicit drugs, and other trace evidence. Noninvasive detection of audio tape 'sticky shed' syndrome. Methods for identifying degraded tape at museums and archives depend on visual inspection followed by playing, which can irreversibly damage a tape by removing data-containing magnetic particles. IR spectroscopy enables non-invasive identification of tape degradation products and use of multivariate statistics and machine learning approaches for classification of the degradation status of tapes. A total of 133 quarter-inch audio tapes were analyzed by infrared spectroscopy with classification of tape playability accomplished using principal component analysis (PCA) followed by quadratic discriminant analysis (QDA). Classification accuracies of 92.58% and 85.53% were achieved for the 95 tape calibration model and 38 tape test set. Development of a reliable, non-destructive approach for identification of tape degradation prevents data loss and increases efficiency for facilitates prioritizing degraded tapes for restoration. Trace profiling of dyes extracted from textile fibers. Forensic examinations of trace fibers found at a crime scene involve a series of comparisons of one or more fibers of unknown origin, with fibers associated with the circumstances of the crime but whose origin is known. If the null hypothesis of common origin for the two fibers cannot be rejected, the two fibers may have originated from a common source and the evidence may support an association between a victim and a suspect, or between a suspect and the crime scene. Judging statistical or practical significance of a possible 'match' between two fibers is the most challenging issue in forensic fiber analysis because fibers are 'class evidence', for which many similar manufactured items exist. However, the significance of fiber evidence and discrimination are expanded by combinatorial possibilities of fiber types and dyes. Microextraction techniques coupled with UPLC/UV-visible and mass spectrometric methods enable dye profiling from single fibers as small as 0.5 mm in length.

Publications

Eric J. Reichard, Edward G. Bartick, Stephen L. Morgan, John V. Goodpaster, “Microspectrophotometric Analysis of yellow polyester fiber dye loadings with chemometric techniques,” Forensic Chemistry, 2017, 3, 21-27.
DOI: 10.1016/j.forc.2016.11.001.

Raymond G. Belliveau, Stephanie A. DeJong, Brianna M. Cassidy, Zhenyu Lu, Stephen L. Morgan, Michael L. Myrick, “Ridge patterns of Blood-Transferred Simulated Fingerprints Observed on Fabrics via Steam Thermography,” Forensic Chemistry, 2016, 1(8), 74-77. DOI: 10.1016/j.forc.2016.07.005.

Zhenyu Lu, Brianna M. Cassidy, Stephanie. A. DeJong, Raymond. G. Belliveau, Michael. L. Myrick, and Stephen. L. Morgan, “Attenuated Total Reflectance Sampling in Infrared Spectroscopy of Heterogeneous Materials Requires Reproducible Pressure Control,” Applied Spectroscopy 2017, 71(1) 97–104.
DOI: 10.1177/0003702816654150.

Mastrianni, K. R.; Lee, L. A.; Brewer, W. E.; Dongari, N.; Barna, M.; Morgan, S. L. “Variations in enzymatic hydrolysis efficiencies for amitriptyline and cyclobenzaprine in urine,” J. Analytical Toxicology, 2016, 40(9), 732-737.
DOI: 10.1093/jat/bkw062.

Cassidy, B. M.; Lu, Z.; Fuenffinger, N. C.; Skelton, S.; Bringley, E. J.; Nguyen, L.; Breitung, E. M.; Myrick, M. L.; Morgan, S. L. “Rapid and Non-destructive Identification of Degraded Polyester-urethane Magnetic Tape using ATR FT-IR Spectroscopy and Multivariate Statistics,” Analytical Chemistry, 2015, 87(18), 9265-9272. DOI: 10.1021/acs.analchem.5b01810.