Additional file 1: of Localized Surface Plasmon Resonance of Silver Nanotriangles Synthesized by a Versatile Solution Reaction

The size and the shape distribution histogram of the as-prepared silver nanoparticles. Figure S1. TEM images (a, b, c), the different nanoparticles shapes distributions histogram (d, e, f) and the corresponding edge length distributions histogram (g, h, i) of as-prepared silver nanotriangles with different dosages of seeds solution. (a), (d), and (g) for 0.01 mL; (b), (e), and (h) for 0.1 mL; (c), (f), and (i) for 1 mL. In (d), (e), and (f) the T-N, Q-N, T-T, and R-N are the abbreviations for triangular nanoparticles, quasi-spherical nanoparticles, truncated triangles, and rounded nanoplates. Figure S2. TEM images (a, b, c), the different nanoparticles shapes distributions histogram (d, e, f), and the corresponding edge length distributions histogram (g, h, i) of as-prepared silver nanotriangles with different molar ratio of PVP to AgNO3. (a), (d), and (g) for 1. (b), (e), and (h) for 2. (c), (f), and (i) for 4. In (d), (e), and (f) the T-N, Q-N, T-T and R-N are the abbreviations for triangular nanoparticles, quasi-spherical nanoparticles, truncated triangles, and rounded nanoplates. Figure S3. Absorption spectra of products obtained with the seeds solution dosage as 0.01, 0.1, and 1 mL. Figure S4. Absorption spectra of products obtained when the molar ratio between PVP and AgNO3 as 1, 2 and 4

Efficient Photochemical, Thermal, and Electrochemical Water Oxidation Catalyzed by a Porous Iron-Based Oxide Derived Metal–Organic Framework

Iron-based catalysts are of particular interest for water oxidation because of their high abundance, low toxicity, and rich redox properties. Herein, we report low cost porous iron-based oxides derived from calcining precursors of Prussian blue analogue (PBA) M_<i>x</i>[Fe­(CN)₆]_<i>y</i> (M = Fe, Co, Ni). This synthesis approach involves a simple self-assembly technology and a low-temperature annealing procedure. These catalysts were investigated for photocatalytic, cerium­(IV)-driven, and electrochemical water oxidation, and they exhibited superior activity. It is noteworthy that this photocatalytic water oxidation was conducted under neutral conditions that are similar to the natural photosystem II. The high initial turnover frequency (TOF) of ∼5.4 × 10^–4 s^–1 per transition metal atom at the first 60 s is obtained under neutral pH using porous Co_<i>x</i>Fe_3–<i>x</i>O₄ in photocatalytic water oxidation reaction, which is comparable with those published iron-based catalysts. Under cerium­(IV)-driven water oxidation conditions, the TOF of porous Co_<i>x</i>Fe_3–<i>x</i>O₄ is 5.2 × 10^–4 s^–1 per transition metal atom, which is the highest value among all the documented iron oxides. In the electrochemical water oxidation, the porous Ni_<i>x</i>Fe_3–<i>x</i>O₄ catalyst exhibits a low overpotential of 402 mV at 10 mA cm^–2. Meanwhile, the porous iron-based oxides possess beneficial ferromagnetic properties and excellent stability so that they were used repeatedly without loss in activity

Table1_Current trends and emerging patterns in the application of nanomaterials for ovarian cancer research: a bibliometric analysis.DOCX

Introduction: Ovarian cancer remains to be a significant cause of global cancer-related mortality. In recent years, there has been a surge of studies in investigating the application of nanomaterials in the diagnosis and treatment of ovarian cancer. This study aims to conduct a comprehensive bibliometric analysis regarding nanomaterial-based researches on ovarian cancer to evaluate the current state and emerging patterns in this field.Methods: A thorough literature search on the Web of Science Core Collection database was conducted to identify articles focused on nanomaterial-based ovarian cancer researches. The studies that met the inclusion criteria were selected for further analysis. VOSviewer and CiteSpace were applied for the bibliometric and visual analyses of the selected publications.Results: A total of 2,426 studies were included in this study. The number of annual publications showed a consistent upward trend from 2003 to 2023. Notably, China, the United States, and India have emerged as the leading contributors in this field, accounting for 37.39%, 34.04%, and 5.69% of the publications, respectively. The Chinese Academy of Sciences and Anil K. Sood were identified as the most influential institution and author, respectively. Furthermore, the International Journal of Nanomedicine was the most frequently cited journal. In terms of the research focus, significant attention has been directed towards nanomaterial-related drug delivery, while the exploration of immunogenic cell death and metal-organic frameworks represented recent areas of interest.Conclusion: Through comprehensive analyses, an overview of current research trends and emerging areas of interest regarding the application of nanomaterials in ovarian cancer was illustrated. These findings offered valuable insights into the status and future directions of this dynamic field.</p

The difference in soil C/N ratios among sites (a) and depths (b).

<p>SF-1 and SF-2 are sites of secondary forest while RG-1 and RG-2 are sites of restored grassland. Error bars are standard error (plot to plot and depth to depth, N = 6).</p

The difference in bulk density at secondary forest (SF-1, SF-2) and restored grassland (RG-1, RG-2).

<p>Error bars are standard error (plot to plot and depth to depth, N = 6).</p

Soil organic carbon (SOC) storage (± standard deviation) at sites secondary forest (SF-1 and SF-2) and restored grassland (RG-1 and RG-2).

<p>Soil organic carbon (SOC) storage (± standard deviation) at sites secondary forest (SF-1 and SF-2) and restored grassland (RG-1 and RG-2).</p

Variation of carbon isotope fractionation factors (α) at different depth among study sites.

<p>SF-1 and SF-2 are sites of secondary forest while RG-1 and RG-2 are sites of restored grassland. Error bars are standard error (plot to plot and depth to depth, N = 6).</p

The difference in soil organic carbon (SOC) content.

<p>SF-1 and SF-2 are sites of secondary forest while RG-1 and RG-2 are sites of restored grassland. Different lower-case letters denote significant differences among depths within an individual study site; different upper-case letters denote significant differences among vegetation restoration types (<i>P</i><0.05) (plot to plot and depth to depth, N = 6).</p

Changes in soil δ¹³C values with depth and vegetation restoration types.

<p>SF-1 and SF-2 are sites of secondary forest while RG-1 and RG-2 are sites of restored grassland. Error bars are standard error (plot to plot and depth to depth, N = 6).</p

Relationship between soil δ¹³C values and soil organic carbon (SOC) content.

<p>SF-1 and SF-2 are sites of secondary forest while RG-1 and RG-2 are sites of restored grassland.</p