We investigate the influence of the hole injection layer (HIL) on the performance of vapor-deposited tris-(8-hydroxyquinoline) aluminum-based organic light-emitting diodes. Four different HIL materials were used: 4,4′, 4″-tris{N,(3-methylphenyl)-N-phenylamino}-triphenylamine) (m-MTDATA), 4,4′, 4″-tris{N,-(2-naphthyl)-N-phenylamino}-triphenylamine, copper phthalocyanine, and oxotitanium phthalocyanine. In all cases, Alq3 acts as the emitting layer as well as electron-transporting layers. Evidence showed that m-MTDATA exhibits a dense film structure and fine surface morphology, leading to easier hole migration at the indium tin oxide/m-MTDATA and m-MTDATA/hole-transport layer junctions. It also possesses a shallow bulk trap level, providing more detrapping holes from the bulk trap states to highest occupied molecular orbital states for transporting in m-MTDATA. We suggest that these are the main contributing factors to the superior current density–voltage and luminance-voltage performance of this device.

PLSR models were developed based on FT-NIR spectra coupled with multivariate data analysis to provide a quick and low-cost estimate of specific sugar contents in grain sorghum stalks. This sugar information helps decision making for sorghum-based biomass processing and storage strategies.

A rapid quantification method was developed and validated for non-destructive measurement of starch content, theoretical ethanol yield and actual ethanol yield of 48 cultivars of sorghum grain using Fourier transform near infrared (FT-NIR) spectroscopy in diffuse reflectance mode. Multiplicative scatter correction, Savitzky-Golay derivative smoothing and mean centring were used for processing the spectra of ground sorghum grain. The processed spectra were correlated with starch content, theoretical ethanol yield and ethanol produced through simultaneous saccharification and fermentation using partial least-squares regression (PLSR). The spectral range and number of factors were optimised for the low number of factors, high coefficients of determination for calibration (R 2 ) and validation (r 2 ), low root mean square error of prediction (RMSEP), high ratio of performance to deviation (RPD) and high ratio of the standard error of prediction to the range (RER). The best PLSR model for starch content utilised the 4000-6000 cm -1 wavebands and had the following values: R 2 = r 2 = 0.97, RMSEP = 5.5 g kg -1 grain, RPD = 5.9 and RER = 15. Likewise, the model for theoretical ethanol yield utilised the 4000-8000 cm -1 wavebands and had R 2 and r 2 values of >0.90, RMSEP = 4.9 g kg -1 grain, RPD = 4.47 and RER = 12.8. It was more difficult to predict actual ethanol yield using FT-NIR spectroscopy given the small data set, and spectra were collected prior to the fermentation step. Resulting PLSR models had R 2 and r 2 values of <0.60, RMSEP = 11.2-21.4 g kg -1 , RPD < 3 and RER < 6. These results demonstrated that FT-NIR spectroscopy may be a practical method for rough screening of sorghum cultivars for desirable starch content and theoretical ethanol yield. The models may be improved by including more cultivars in the model and additional compositional information, such as tannin and free amino nitrogen contents, in the chemometric analysis and using FT-NIR scans of the fermentation products to predict actual ethanol yields.