Haiying Zhou

Dr. Haiying Zhou

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 February 2025 in Catalysts
Verified
Journal Article
Open access
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HZHaiying Zhou
Haiying Zhou
WXWen Xiong
Wen Xiong
ASAbolfazl Shakouri
Abolfazl Shakouri
LLLu Lu
Lu Lu
John RegalbutoJohn Regalbuto
John Regalbuto
JTJohn Meynard Tengco
John Meynard Tengco
Well-defined supported metal nanoparticle catalysts, with high uniformity in particle sizes of the dispersed metal, are crucial for studying their catalyzed reactions that exhibit structure sensitivity. For such catalysts, conventional methods of preparation may prove unsuitable in controlling the nanoparticle size and distribution. In this work, the systematic growth of supported Pd and Pt particles was achieved through the method of electroless deposition (ED), in which additional metal was deposited on preexisting particles of the same metal. The ED process was investigated by varying the pump time, pump speed, and molar ratios of the reagents during the continuous addition of the metal precursor, as well as the reducing agent and stabilizer, which were hydrazine and ethylenediamine, respectively. This allowed for the precise control of deposition rates, thus regulating the supported metal particle size, size distribution, and particle density. A slower deposition rate was achieved by increasing the amount of the ethylenediamine stabilizer and lowering the pumping speed. Slower rates of deposition resulted in smaller particle sizes and tighter size distributions compared to other preparations with the same metal weight loading, as characterized via X-ray diffraction (XRD), chemisorption, and scanning-transmission electron microscopy (STEM) methods.

5 October 2022 in Frontiers in Oncology
Verified
Journal Article
Open access
ZYZi-Yi Yu
Zi-Yi Yu
DGDan Gao
Dan Gao
ZTZhao Tang
Zhao Tang
HZHaiying Zhou
Haiying Zhou
JOJing Ou
Jing Ou
TCTian-wu Chen
Tian-wu Chen
Purpose: To develop and validate a quantitative model based on gross tumor volume (GTV) of gastric adenocarcinoma (GA) corresponding to N-stage measured at multidetector computed tomography (CT) for preoperative determination of resectabilityMaterials and methods: 493 consecutive patients with confirmed GA undergoing contrast-enhanced CT two weeks before treatments were randomly enrolled into the training cohort (TC, n = 271), internal validation cohort (IVC, n = 107) and external validation cohort (EVC, n = 115). GTV was measured on CT by multiplying sums of all tumor areas by section thickness. In TC, univariate and multivariate analyses were performed to select factors associated with resectability. Receiver operating characteristic (ROC) analysis was to determine if N-stage based GTV could identify resectability. In IVC and EVC, unweighted Cohen’s Kappa tests were to evaluate performances of the ROC models.Results: According to univariate analysis, age, cT stage, cN stage and GTV were related to resectability in TC (all P-values < 0.05), and multivariate analysis suggested that cN stage and GTV were independent risk factors with odds ratios of 1.594 (95% confidence interval [CI]: 1.105–2.301) and 1.055 (95%CI: 1.035–1.076), respectively. ROC analysis in TC revealed the cutoffs of 21.81, 21.70 and 36.93 cm3 to differentiate between resectable and unresectable cancers in stages cN0-3, cN2 and cN3 with areas under the curves of more than 0.8, respectively, which was validated in IVC and EVC with average Cohen k-values of more than 0.72.Conclusions: GTV and cN stage can be independent risk factors of unresectable GA, and N-stage based GTV can help determine resectability.