Synthesis And Characterization Of Combinatorial Au-Pd Alloy Nanoparticle Library And Their Cellular Effects

In recent years,one of the reasons for more and more serious environmental pollution is a large number of new pollutants into the environment,nano material is such a new type of pollutants.Due to their special structure and excellent properties,nanomaterials have been widely used in industry and daily life,but also caused environmental pollution.At present,a large number of nanomaterials have been detected in the environment,and more and more attention has been paid to their potential threat to human health.When nanomaterials enter the human body,they will produce toxicity to the human body at the cellular and subcellular levels,and the toxicity is related to the cell type,the physical and chemical properties of nanomaterials(such as morphology,size,core composition,surface potential and surface chemical modification,etc.)and the biological microenvironment.Artificial intelligence has become an increasingly important research field with the development of computer technology in recent years.Big data computing and machine learning,especially deep learning,can be used for analysis,modeling and prediction.Artificial intelligence has been successfully used in biomedicine and many other fields.Therefore,toxicity big data and artificial intelligence also have a very broad development prospect in the field of environmental toxicology.However,the current dilemma of nanomaterial-cell effect research is the lack of systematic data,which cannot be applied to artificial intelligence research.Many published data of nanomaterial-cell effect are for the one-at-a-time research of very few nanomaterials,and there is a lack of systematic material synthesis standards,systematic characterization and cell effect.In addition,there is no unified standard among different laboratories,and sometimes there are even contradictory data.There is a lack of detailed characterization information in many nano-materials literature.As a result,we are currently unable to effectively convert data into information,and in particular,it is difficult to effectively use artificial intelligence to make breakthroughs.Therefore,we are committed to the synthesis of composite chemical nanoparticle library,through the systematic study of biological effects,to establish a large database of nanomaterial cell effects with different physical and chemical properties,in order to carry out deep learning and modeling prediction of these big data,and achieve the purpose of cross-material prediction of nanomaterial properties and cell effects.In this study,we successfully constructed the first combinatorial chemical nanoparticle library containing 84 kinds of nanomaterials with different sizes,varying proportions of Au and Pd alloys and diverse surface chemistry.Experimental results show that the nanoparticles,uniform distribution and the gradient alloy elements,surface chemical diversity change,and the success of the regulation of the physical and chemical and biological properties of nanoparticles,the preliminary research results show that the cell toxicity and cells of gold palladium alloy intake and cell type of nanomaterials and nano particle size and surface chemical properties.This study establishes a method system for synthesis,characterization and high-throughput cell research of composite chemical alloy nanoparticle libraries,which lays a solid foundation for further construction of large databases and artificial intelligence computing.