A study of TiO₂ nanocrystal growth and environmental remediation capability of TiO₂/CNC nanocomposites

Abstract

Green and sustainable cellulose nanocrystals-TiO2 nanocomposite was prepared for environmental applications using a facile method comprised of thermal degradation of aqueous titanium precursors.

Artificial intelligence to deep learning: machine intelligence approach for drug discovery

“…https://github.com/sysu-yanglab/DLIGAND2 Distance-scaled Best performance as a parameter-free statistical potential and among the best in all performance measures [ 228 ] StackCBPred A stacking-based prediction of protein-carbohydrate binding sites from the sequence. https://bmll.cs.uno.edu/ Machine learning Predicted structural properties of amino acids to effectively train a Stacking-based machine learning method for the accurate prediction of protein-carbohydrate binding sites [ 229 ] LSA A local-weighted structural alignment tool for virtual pharmaceutical screening Conventional similarity algorithms Computes the similarity of two molecular structures by considering the contributions of both overall similarity and local substructure match [ 230 ] ProPose Steered Virtual Screening by Simultaneous Protein−Ligand Docking and Ligand−Ligand Alignment Machine learning The combination of ligand- and receptor-based methods steers the virtual screening by ranking molecules according to the similarity of their interaction pattern with known ligands [ 231 ] TrixX Structure-based molecule indexing for large-scale virtual screening in sublinear time Machine learning TrixX counts among the fastest virtual screening tools currently available and is nearly two orders of magnitude faster than standard FlexX [ 232 ] DrugFinder In silico virtual screening service Machine learning It intended as a validation of the screening platform and its methods, and to promote confidence in its software components to produce valuable results [ 233 ] DEEPScreen High-performance drug-target interaction prediction. https://github.com/cansyl/DEEPscreen Convolutional neural networks ...…”

Nanocellulose/Fullerene Hybrid Films Assembled at the Air/Water Interface as Promising Functional Materials for Photo-electrocatalysis

“…In this context, nanocellulose-based materials show great potential for industry [ 35 ], as the principles of green and blue economies demand new sources of sustainable materials in substitution of oil-derivatives, for high volume applications in sectors, such as water treatment [ 36 ], paint and coating industry, building, hygiene, and paper industry [ 37 ]. Besides, new intriguing and emerging applications concern the use of nanocellulose in hydrogels and aerogels [ 38 , 39 ], emulsion stabilizers [ 40 ], biocatalyst immobilizers [ 41 ], biosensors [ 42 ], drug delivery systems [ 43 ], adsorbents for contaminants [ 44 , 45 ], nanocomposites for environmental remediation [ 46 ], photonic films and transparent substrates for optoelectronic devices, as well as new nanostructured electroactive materials [ 47 , 48 , 49 ]. Indeed, nanocellulose can expose a large active area, is transparent, and it is harmless for human health and the environment [ 50 , 51 ].…”

Separation of Boron from Geothermal Waters with Membrane System

“…Many useful methods are used for boron removal. The most used of these methods (in order) are: adsorption, chemical precipitation, ion exchange, reverse osmosis (RO), electrodialysis (ED), electro-coagulation, Donnan dialysis, capacitive deionization, microwave hydrothermal, extraction by ionic liquids, thermal desalination processes, and direct contact membrane distillation methods [8][9][10]. Among these methods, however, no standards are provided due to restrictions on boron removal.…”