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“Phase transformation of superparamagnetic iron oxide nanoparticles via thermal annealing : implications for hyperthermia applications”. Crippa F, Rodriguez-Lorenzo L, Hua X, Goris B, Bals S, Garitaonandia JS, Balog S, Burnand D, Hirt AM, Haeni L, Lattuada M, Rothen-Rutishauser B, Petri-Fink A, ACS applied nano materials 2, 4462 (2019). http://doi.org/10.1021/ACSANM.9B00823
Abstract: Magnetic hyperthermia has the potential to play an important role in cancer therapy and its efficacy relies on the nanomaterials selected. Superparamagnetic iron oxide nanoparticles (SPIONs) are excellent candidates due to the ability of producing enough heat to kill tumor cells by thermal ablation. However, their heating properties depend strongly on crystalline structure and size, which may not be controlled and tuned during the synthetic process; therefore, a postprocessing is needed. We show how thermal annealing can be simultaneously coupled with ligand exchange to stabilize the SPIONs in polar solvents and to modify their crystal structure, which improves hyperthermia behavior. Using high-resolution transmission electron microscopy, X-ray diffraction, Mossbauer spectroscopy, vibrating sample magnetometry, and lock-in thermography, we systematically investigate the impact of size and ligand exchange procedure on crystallinity, their magnetism, and heating ability. We describe a valid and simple approach to optimize SPIONs for hyperthermia by carefully controlling the size, colloidal stability, and crystallinity.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Times cited: 18
DOI: 10.1021/ACSANM.9B00823
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“Assessing the success of electricity demand response programs : a meta-analysis”. Srivastava A, Van Passel S, Laes E, Energy Research and Social Science 40, 110 (2018). http://doi.org/10.1016/J.ERSS.2017.12.005
Abstract: This paper conducts a meta-analysis of 32 electricity demand response programs in the residential sector to understand whether their success is dependent on specific characteristics. The paper analyses several regression models using various combinations of variables that capture the designs of the programs and the socio-economic conditions in which the programs are implemented. The analysis reveals that demand response programs are more likely to succeed in highly urbanized areas, in areas where economic growth rates are high, and in areas where the renewable energy policy is favorable. These findings provide useful guidance in determining where and how to implement future demand response programs.
Keywords: A1 Journal article; Economics; Engineering Management (ENM)
Times cited: 18
DOI: 10.1016/J.ERSS.2017.12.005
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