What is he best known for?
The fields of study he is best known for:
- Organic chemistry
- Polymer
- Enzyme
Xuesi Chen mainly investigates Polymer chemistry, Drug delivery, Copolymer, Ethylene glycol and Polymer.
His work carried out in the field of Polymer chemistry brings together such families of science as Biocompatibility, Chemical engineering and Lactide, Polymerization.
His studies deal with areas such as Doxorubicin Hydrochloride, Doxorubicin, Biochemistry and In vivo as well as Drug delivery.
His Copolymer research includes elements of Cationic polymerization, Gel permeation chromatography and Click chemistry.
Xuesi Chen combines subjects such as Conjugate, Micelle and Nuclear chemistry with his study of Ethylene glycol.
His Polymer research is multidisciplinary, relying on both Polyester, Biodegradation and Drug.
His most cited work include:
- Biodegradable synthetic polymers: Preparation, functionalization and biomedical application (793 citations)
- Biodegradable electrospun fibers for drug delivery (692 citations)
- Nano-composite of poly(L-lactide) and surface grafted hydroxyapatite: mechanical properties and biocompatibility. (363 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Polymer chemistry, Copolymer, Drug delivery, Ethylene glycol and Polymerization.
His Polymer chemistry study deals with Chemical engineering intersecting with Electrospinning.
His Copolymer study incorporates themes from Micelle and Aqueous solution.
His study in Drug delivery is interdisciplinary in nature, drawing from both Biophysics, In vivo and Doxorubicin.
His Doxorubicin study integrates concerns from other disciplines, such as Cancer research and Pharmacology.
His biological study spans a wide range of topics, including Schiff base, Cationic polymerization and Catalysis.
He most often published in these fields:
- Polymer chemistry (32.52%)
- Copolymer (21.19%)
- Drug delivery (16.50%)
What were the highlights of his more recent work (between 2018-2021)?
- Cancer research (14.36%)
- Drug delivery (16.50%)
- Tumor microenvironment (4.79%)
In recent papers he was focusing on the following fields of study:
Xuesi Chen mostly deals with Cancer research, Drug delivery, Tumor microenvironment, In vivo and Immune system.
His research in Cancer research intersects with topics in Immune checkpoint, Cancer immunotherapy, Immunotherapy, Doxorubicin and Nanomedicine.
The study incorporates disciplines such as Phenylboronic acid, Ethylene glycol and Click chemistry in addition to Drug delivery.
His study looks at the relationship between Ethylene glycol and topics such as Self-healing hydrogels, which overlap with Chondrogenesis and Tissue engineering.
He has included themes like In vitro, Biophysics, Receptor, Nanogel and Pharmacology in his In vivo study.
His work carried out in the field of Copolymer brings together such families of science as Combinatorial chemistry and Chemical engineering.
Between 2018 and 2021, his most popular works were:
- Electrospun polymer biomaterials (176 citations)
- Engineered nanomedicines with enhanced tumor penetration (99 citations)
- Electrospun polymer micro/nanofibers as pharmaceutical repositories for healthcare. (97 citations)
In his most recent research, the most cited papers focused on:
- Organic chemistry
- Polymer
- Enzyme
Xuesi Chen mainly investigates Cancer research, Tumor microenvironment, Drug delivery, Photothermal therapy and Nanotechnology.
His research in Drug delivery intersects with topics in Doxorubicin, Rodent model, Targeted therapy, Genetically engineered and Poor prognosis.
His studies in Photothermal therapy integrate themes in fields like Nanoparticle and Tumor therapy.
His study in Nanotechnology is interdisciplinary in nature, drawing from both Covalent bond and Electrospinning, Polymer.
His studies examine the connections between Polymer and genetics, as well as such issues in Fiber, with regards to Biomedical engineering.
The Adhesion study combines topics in areas such as Ethylene glycol and Regeneration.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
