The research on properties of asphaltene stationary phase to separate mixtures of optically active compounds with the use of gas chromatography technique

W pracy przedstawiono wyniki badań nad możliwością zastosowania asfaltenów jako chiralnej fazy stacjonarnej do chromatografii gazowej. Wyniki uzyskane dla fazy asfaltenowej porównano z wynikami uzyskanymi poprzez zastosowanie komercyjnie dostępnej chiralnej fazy stacjonarnej. Badania wykazały, że frakcja asfaltenowa posiada właściwości umożliwiające uzyskanie rozdzielenia mieszanin związków optycznie czynnych.The paper presents a results of research on the possibility of application of asphaltenes as a chiral stationary phase for gas chromatography. The results obtained for asphaltene stationary phase were compared with results obtained using a commercially available chiral stationary phase. The research showed that asphaltene fraction has properties allowing to separate mixtures of optically active compounds

Leaky integrate-and-fire model and short-term synaptic plasticity emulated in a novel bismuth-based diffusive memristor

Memristors, being prospective work-horses of future electronics offer various types of memory (volatile and nonvolatile) along with specific computational functionalities. Further development of memristive technologies depends on the availability of suitable materials. These materials should be easily available, stable, and preferably of low toxicity. Commonly used materials are lead halide perovskites, however, they are highly toxic and unstable under ambient conditions. Therefore a novel material is developed on the basis of bismuth iodide. In reaction with butylammonium iodide, it yields a novel compound, butylammonium iodobismuthate (BABI). Here, a diffusive memristor is introduced based on this compound and evaluates its memristive and neuromorphic properties. In contrast to nonvolatile memristors, the BABI memristors exhibit diffusive dynamics, which enable them to store the information only for short periods of time. This property is utilized to mimic the short-term synaptic plasticity described by the leaky integrate-and-fire model of a biological neuron. Combined with high switching uniformity and self-rectifying behavior, these devices show high classification accuracy for MNIST handwritten datasets, paving the way for their application in neuromorphic computing systems.</p