A deep machine-learning technique based on a convolutional neural network (CNN) is introduced. It has been used for the classification of powder X-ray diffraction (XRD) patterns in terms of crystal system, extinction group and space group. About 150 000 powder XRD patterns were collected and used as input for the CNN with no handcrafted engineering involved, and thereby an appropriate CNN archi...

The legacy of planetary X-ray Diffraction (XRD) and X-ray Fluorescence (XRF) began in 1960 when W. Parish proposed an XRD instrument for deployment on the moon. The instrument was built and flight qualified, but the Lunar XRD program was cancelled shortly before the first human landing in 1969. XRF chemical data have been collected in situ by surface landers on Mars (Viking 1 & 2, Pathfinder) a...

The optimum conditions for the fabrication of zein/Ag composite nanoparticles from ethanol/H₂O cosolvents using electrospinning and the properties of the composite were investigated. The zein/Ag nanoparticles were characterized using field-emission scanning electron microscopy, transmission electron microscopy (TEM), X-ray diffraction (XRD), and thermogravimetric analysis. The antibacterial act...

The spectroscopic studies of transition metal complexes of iron. metal complexes, are characterized by XRD, FTIR, H NMR, Mössbauer and VSM (vibrating sample magnetometer) measurements, are reported in the present paper. The XRD analysis reveals the crystalline nature of all the compounds. Mössbauer study interprets paramagnetic nature of complexes at room temperature. VSM measurements also reve...

Monoenergetic x-ray diffraction (XRD) analysis is an established standard for the assessment of urinary stone composition. The inherent low energy of x-rays used (8 keV), however, restricts penetration depth and imposes a requirement for small powdered samples. A technique capable of producing detailed information regarding component structural arrangements in calculi non-destructively would pr...