The ability to tune the magnetic properties of magnetic nanoparticles by manipulating the composition or surface properties of the nanoparticles is important for exploiting the application of the nanomaterials. This report describes preliminary findings of an investigation of the viability of synthesizing MnZn ferrite and core @ shell MnZn ferrite @ Au nanoparticles as potentially magnetization-tunable nanomaterials. The synthesis of the core-shell magnetic nanoparticles involved a simple combination of seed formation of the MnZn ferrite magnetic nanoparticles and surface coating of the seeds with gold shells. Water-soluble MnZn ferrite nanoparticles of 20-40 nm diameters and MnZn ferrite @ Au nanoparticles of 30-60 nm have been obtained. The MnZn ferrite @ Au nanoparticles have been demonstrated to be viable in magnetic separation of nanoparticles via interparticle antibody-specific binding reactivity between antibodies on the gold shells of the core-shell magnetic particles and proteins on gold nanoparticles. These findings have significant implications to the design of the core @ shell magnetic nanomaterials with core composition tuned magnetization for bioassay application.

SummarySentiment analysis, as a branch of unstructured data mining, has interested people greatly. Sentiment analysis based on machine learning method usually considers less sentimental feature extraction. This article presents a method based on machine learning combining with pattern matching for sentiment analysis. We conduct basic sub‐word first, and then designed the keyword extraction strategy. We designed some emotional expression patterns. After the success matching to those patterns, we get emotional features, which are in the form of sequence. For each feature pattern, we calculated the value of emotional tendency, and finally to obtain the emotional tendency of the web comment based on machine‐learning method. The experiment result shows the method can improve the classification performances compared to using regular machine‐learning method.

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