scholarly journals Plasticity in Three-Dimensional Geometry of Branching Corals Along a Cross-Shelf Gradient

Diversity ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 44 ◽  
Author(s):  
Neil Doszpot ◽  
Michael McWilliam ◽  
Morgan Pratchett ◽  
Andrew Hoey ◽  
Will Figueira
Keyword(s):  
Surface Area ◽  
Environmental Gradients ◽  
Three Dimensional ◽  
Volume Ratio ◽  
Morphological Plasticity ◽  
Outer Shelf ◽  
Individual Species ◽  
Inner Shelf ◽  
Stylophora Pistillata ◽  
Wide Range

Scleractinian corals often exhibit high levels of morphological plasticity, which is potentially important in enabling individual species to occupy benthic spaces across a wide range of environmental gradients. This study tested for differences in the three-dimensional (3D) geometry of three branching corals, Acropora nasuta, Pocillopora spp. and Stylophora pistillata among inner-, mid- and outer-shelf reefs in the central Great Barrier Reef, Australia. Important attributes of coral morphology (e.g., surface area to volume ratio) were expected to vary linearly across the shelf in accordance with marked gradients in environmental conditions, but instead, we detected non-linear trends in the colony structure of A. nasuta and Pocillopora spp. The surface area to volume ratio of both A. nasuta and Pocillopora spp. was highest at mid-shelf locations, (reflecting higher colony complexity) and was significantly lower at both inner-shelf and outer-shelf reefs. The branching structure of these corals was also far more tightly packed at inner-shelf and outer-shelf reefs, compared to mid-shelf reefs. Apparent declines in complexity and inter-branch spacing at inner and outer-shelf reefs (compared to conspecifics from mid-shelf reefs) may reflect changes driven by gradients of sedimentation and hydrodynamics. The generality and explanations of observed patterns warrant further investigation, which is very feasible using the 3D-photogrammetry techniques used in this study.

scholarly journals A Review on Biosensors and Recent Development of Nanostructured Materials-Enabled Biosensors

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1109
Author(s):  
Varnakavi. Naresh ◽  
Nohyun Lee
Keyword(s):  
High Surface ◽  
Three Dimensional ◽  
Biological Response ◽  
Volume Ratio ◽  
Recent Decade ◽  
Disease Diagnosis ◽  
Electrical Signal ◽  
Detection Sensitivity ◽  
Wide Range ◽  
Color Tunability

A biosensor is an integrated receptor-transducer device, which can convert a biological response into an electrical signal. The design and development of biosensors have taken a center stage for researchers or scientists in the recent decade owing to the wide range of biosensor applications, such as health care and disease diagnosis, environmental monitoring, water and food quality monitoring, and drug delivery. The main challenges involved in the biosensor progress are (i) the efficient capturing of biorecognition signals and the transformation of these signals into electrochemical, electrical, optical, gravimetric, or acoustic signals (transduction process), (ii) enhancing transducer performance i.e., increasing sensitivity, shorter response time, reproducibility, and low detection limits even to detect individual molecules, and (iii) miniaturization of the biosensing devices using micro-and nano-fabrication technologies. Those challenges can be met through the integration of sensing technology with nanomaterials, which range from zero- to three-dimensional, possessing a high surface-to-volume ratio, good conductivities, shock-bearing abilities, and color tunability. Nanomaterials (NMs) employed in the fabrication and nanobiosensors include nanoparticles (NPs) (high stability and high carrier capacity), nanowires (NWs) and nanorods (NRs) (capable of high detection sensitivity), carbon nanotubes (CNTs) (large surface area, high electrical and thermal conductivity), and quantum dots (QDs) (color tunability). Furthermore, these nanomaterials can themselves act as transduction elements. This review summarizes the evolution of biosensors, the types of biosensors based on their receptors, transducers, and modern approaches employed in biosensors using nanomaterials such as NPs (e.g., noble metal NPs and metal oxide NPs), NWs, NRs, CNTs, QDs, and dendrimers and their recent advancement in biosensing technology with the expansion of nanotechnology.

scholarly journals Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures

2017 ◽  
Vol 17 (19) ◽  
pp. 12011-12030 ◽  
Author(s):  
Mathias Gergely ◽  
Steven J. Cooper ◽  
Timothy J. Garrett
Keyword(s):  
Surface Area ◽  
Cross Sections ◽  
Volume Ratio ◽  
High Sensitivity ◽  
Maximum Size ◽  
Strong Impact ◽  
Triple Frequency ◽  
Bounding Volume ◽  
Wide Range ◽  
Radar Signatures

Abstract. The snowflake microstructure determines the microwave scattering properties of individual snowflakes and has a strong impact on snowfall radar signatures. In this study, individual snowflakes are represented by collections of randomly distributed ice spheres where the size and number of the constituent ice spheres are specified by the snowflake mass and surface-area-to-volume ratio (SAV) and the bounding volume of each ice sphere collection is given by the snowflake maximum dimension. Radar backscatter cross sections for the ice sphere collections are calculated at X-, Ku-, Ka-, and W-band frequencies and then used to model triple-frequency radar signatures for exponential snowflake size distributions (SSDs). Additionally, snowflake complexity values obtained from high-resolution multi-view snowflake images are used as an indicator of snowflake SAV to derive snowfall triple-frequency radar signatures. The modeled snowfall triple-frequency radar signatures cover a wide range of triple-frequency signatures that were previously determined from radar reflectivity measurements and illustrate characteristic differences related to snow type, quantified through snowflake SAV, and snowflake size. The results show high sensitivity to snowflake SAV and SSD maximum size but are generally less affected by uncertainties in the parameterization of snowflake mass, indicating the importance of snowflake SAV for the interpretation of snowfall triple-frequency radar signatures.

scholarly journals 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy

2012 ◽  
Vol 6 (5) ◽  
pp. 939-951 ◽  
Author(s):  
N. Calonne ◽  
C. Geindreau ◽  
F. Flin ◽  
S. Morin ◽  
B. Lesaffre ◽  
...  
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Three Dimensional ◽  
Analytical Models ◽  
Simple Relationship ◽  
Snow Density ◽  
Average Value ◽  
Wide Range ◽  
Snow Samples

Abstract. We used three-dimensional (3-D) images of snow microstructure to carry out numerical estimations of the full tensor of the intrinsic permeability of snow (K). This study was performed on 35 snow samples, spanning a wide range of seasonal snow types. For several snow samples, a significant anisotropy of permeability was detected and is consistent with that observed for the effective thermal conductivity obtained from the same samples. The anisotropy coefficient, defined as the ratio of the vertical over the horizontal components of K, ranges from 0.74 for a sample of decomposing precipitation particles collected in the field to 1.66 for a depth hoar specimen. Because the permeability is related to a characteristic length, we introduced a dimensionless tensor K*=K/res2, where the equivalent sphere radius of ice grains (res) is computed from the specific surface area of snow (SSA) and the ice density (ρi) as follows: res=3/(SSA×ρi. We define K and K* as the average of the diagonal components of K and K*, respectively. The 35 values of K* were fitted to snow density (ρs) and provide the following regression: K = (3.0 ± 0.3) res2 exp((−0.0130 ± 0.0003)ρs). We noted that the anisotropy of permeability does not affect significantly the proposed equation. This regression curve was applied to several independent datasets from the literature and compared to other existing regression curves or analytical models. The results show that it is probably the best currently available simple relationship linking the average value of permeability, K, to snow density and specific surface area.

New Advances in Graphene-Based Three-Dimensional Structures

2022 ◽  
pp. 101-128
Author(s):  
Javier Cencerrero Fernández del Moral ◽  
Amaya Romero Izquierdo ◽  
Paula Sánchez Paredes ◽  
Osmín Avilés-García ◽  
Israel Fernandez-Reina
Keyword(s):  
Surface Area ◽  
Environmental Remediation ◽  
Three Dimensional ◽  
Single Atom ◽  
Synthesis Methods ◽  
High Porosity ◽  
Covalent Bonds ◽  
Dimensional Network ◽  
Wide Range ◽  
Electron Transfer Properties

Graphene is defined as a two-dimensional network of carbon atoms with a single atom thickness and a hexagonal crystalline structure with sp2 hybridization compacted by covalent bonds. Due to its structure and geometry, graphene has unique properties, including a large specific surface area, rapid mobility of load carriers, and high thermal and electrical conductivity. However, these characteristics are limited due to the restructuring of graphene sheets. For this reason, there are many studies devoted to the synthesis of three-dimensional structures that prevent the agglomeration of the sheets and the loss of properties of the graphene structure. These three-dimensional structures have low density, high porosity and surface area, stable mechanical properties, and good mass and electron transfer properties. This chapter aims to summarize the synthesis methods of the different three-dimensional structures derived from graphene as well as their wide range of applications in environmental remediation, sensors, biomedical and energy-related applications, among many others.

scholarly journals Methods for tuning plasmonic and photonic optical resonances in high surface area porous electrodes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lauren M. Otto ◽  
E. Ashley Gaulding ◽  
Christopher T. Chen ◽  
Tevye R. Kuykendall ◽  
Aeron T. Hammack ◽  
...  
Keyword(s):  
Photonic Crystal ◽  
Photonic Crystals ◽  
Titanium Nitride ◽  
Surface Area ◽  
Periodic Structures ◽  
High Surface ◽  
High Surface Area ◽  
Three Dimensional ◽  
Porous Electrodes ◽  
Wide Range

AbstractSurface plasmons have found a wide range of applications in plasmonic and nanophotonic devices. The combination of plasmonics with three-dimensional photonic crystals has enormous potential for the efficient localization of light in high surface area photoelectrodes. However, the metals traditionally used for plasmonics are difficult to form into three-dimensional periodic structures and have limited optical penetration depth at operational frequencies, which limits their use in nanofabricated photonic crystal devices. The recent decade has seen an expansion of the plasmonic material portfolio into conducting ceramics, driven by their potential for improved stability, and their conformal growth via atomic layer deposition has been established. In this work, we have created three-dimensional photonic crystals with an ultrathin plasmonic titanium nitride coating that preserves photonic activity. Plasmonic titanium nitride enhances optical fields within the photonic electrode while maintaining sufficient light penetration. Additionally, we show that post-growth annealing can tune the plasmonic resonance of titanium nitride to overlap with the photonic resonance, potentially enabling coupled-phenomena applications for these three-dimensional nanophotonic systems. Through characterization of the tuning knobs of bead size, deposition temperature and cycle count, and annealing conditions, we can create an electrically- and plasmonically-active photonic crystal as-desired for a particular application of choice.

scholarly journals Using snowflake surface area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures

2017 ◽  
Author(s):  
Mathias Gergely ◽  
Steven J. Cooper ◽  
Timothy J. Garrett
Keyword(s):  
Surface Area ◽  
Cross Sections ◽  
Volume Ratio ◽  
High Sensitivity ◽  
Maximum Size ◽  
Strong Impact ◽  
Triple Frequency ◽  
Bounding Volume ◽  
Wide Range ◽  
Radar Signatures

Abstract. The snowflake microstructure determines the microwave scattering properties of individual snowflakes and has a strong impact on snowfall radar signatures. In this study, the microstructure of individual snowflakes is approximated by collections of randomly distributed ice spheres where the size and number of the constituent ice spheres are specified by the snowflake mass and ice surface area-to-volume ratio (SAV) and the bounding volume is given by the snowflake maximum dimension. Radar backscatter cross sections for the ice sphere collections are calculated at X-, Ku-, Ka-, and W-band frequencies and then used to model snowfall triple-frequency radar signatures for exponential snowflake size distributions (SSDs). Additionally, first results are presented for using snowflake complexity values derived from high-resolution multi-view snowflake images as indicator of snowflake SAV. The modeled snowfall triple-frequency radar signatures cover a wide range of triple-frequency signatures that were previously determined from radar reflectivity measurements and illustrate characteristic differences related to snow type, quantified through snowflake SAV, and snowflake size. The results show high sensitivity to snowflake SAV and SSD maximum size but are less affected by uncertainties in the parameterization of snowflake mass, indicating the importance of a realistic description of snowflake SAV for a quantitative interpretation of snowfall triple-frequency radar signatures.

scholarly journals 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy

2012 ◽  
Vol 6 (2) ◽  
pp. 1157-1180 ◽  
Author(s):  
N. Calonne ◽  
C. Geindreau ◽  
F. Flin ◽  
S. Morin ◽  
B. Lesaffre ◽  
...  
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Three Dimensional ◽  
Analytical Models ◽  
Wide Range ◽  
Sphere Radius ◽  
Snow Microstructure ◽  
Microstructural Anisotropy ◽  
Good Agreement

Abstract. We used three-dimensional (3-D) images of snow microstructure to carry out numerical estimations of the full tensor of the intrinsic permeability of snow (K). This study was performed on 35 snow samples, spanning a wide range of seasonal snow types. Because the permeability is related to a characteristic length, we introduced a dimensionless tensor K*=K/ res2, where the equivalent sphere radius of ice grains (res) is computed from the specific surface area of snow (SSA) and the ice density (ρi) as follows: res=3/(SSA x ρi). Values of K*, the average of vertical and horizontal components of K*, were plotted vs. snow density (ρs) and compared to analytical models and data from the literature, showing generally a good agreement. The 35 values of K* were fitted to ρs and provide the following regression: K*=2.94 x exp(–0.013 ρs), with a correlation coefficient of 0.985. This indicates that permeability, if assumed isotropic, can be reasonably determined from SSA and ρs, which are both easily measurable in the field. However, the anisotropy coefficient of K, induced by the snow microstructure, ranges from 0.74 to 1.66 for the samples considered. This behavior is consistent with that of the effective thermal conductivity obtained in a previous work.

scholarly journals Predicting Drug Release from 3D Printed Oral Medicines Based on the Surface Area to Volume Ratio of Tablet Geometry

Pharmaceutics ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1453
Author(s):  
Hellen Windolf ◽  
Rebecca Chamberlain ◽  
Julian Quodbach
Keyword(s):  
Drug Release ◽  
Surface Area ◽  
Volume Ratio ◽  
Dosage Forms ◽  
Water Soluble ◽  
Drug Dissolution ◽  
Alcohol Water ◽  
Wide Range ◽  
3D Printed ◽  
Release Profiles

3D printing offers the advantage of being able to modify dosage form geometry, which can be exploited to modify release characteristics. In this study, we investigated the influence of the surface area to volume ratio (SA/V) to change and predict release profiles of 3D printed dosage forms. Geometries with varying SA/V and dosages were designed and printed, and drug dissolution was investigated. Three drug substances were used: pramipexole, levodopa (both BCS I) and praziquantel (BCS II). Two polymers were chosen as matrix formers: polyvinyl alcohol (water-soluble) and ethylene vinyl acetate (inert). Drug release was characterized using the mean dissolution time (MDT) and established equations that describe complete dissolution curves were applied. Predictions were validated with previously un-printed dosage forms. Based on an identified MDT-SA/V correlation, the MDT can be predicted with a deviation of ≤5 min for a given SA/V. Using correlations of fit parameters and SA/V, RMSEP values of 0.6–2.8% and 1.6–3.4% were obtained for the BCS I formulations and RMSEP values of 1.0–3.8% were obtained for the BCS II formulation, indicating accurate prediction over a wide range of dissolution profiles. With this approach, MDT and release profiles of dosage forms with a given SA/V can be precisely predicted without performing dissolution tests and vice versa, the required SA/V can be predicted for a desired release profile.

Effects of macroalgal morphology on marine epifaunal diversity

2019 ◽  
Vol 99 (8) ◽  
pp. 1697-1707 ◽  
Author(s):  
Su Xuan Gan ◽  
Ywee Chieh Tay ◽  
Danwei Huang
Keyword(s):  
High Surface ◽  
Algal Species ◽  
High Surface Area ◽  
Three Dimensional ◽  
Volume Ratio ◽  
High Turnover ◽  
Invertebrate Diversity ◽  
Wide Range ◽  
Host Habitat ◽  
Negative Effect

AbstractMacroalgae play important ecological roles, including as hosts for a wide range of epifauna. However, the diversity relationships between macroalgae and epifauna are poorly understood for most tropical host species and algal morphologies. This study aims to characterize and analyse the diversity of invertebrates present amongst macroalgae with three distinct morphologies (three-dimensional, filamentous and foliose) across different tropical intertidal sites in Singapore. Morphological and DNA barcoding tools were employed for epifaunal species identification, and ordination statistics and multiple linear regression were used to test the effects of algal morphology, species and site on community structure and diversity of epiphytic invertebrates. Overall, epifaunal communities were distinct among sites and algal morphologies, and diversity was affected significantly by algal morphology. In particular, filamentous macroalgae hosted the highest abundance of epifauna dominated mainly by amphipods, which were able to take advantage of the high surface area to volume ratio in filamentous algal mats as a consequence of their thinner forms. Foliose species showed a significantly negative effect on invertebrate diversity. Our findings highlight the diverse associations between intertidal macroalgae and invertebrates with high turnover between algal morphology and sites that contribute to the high biodiversity of tropical shores. Future studies should consider the effects of the host habitat, seasonality and more algal species on epifaunal diversity.

Toward the control of graphenic foams

2017 ◽  
Vol 89 (4) ◽  
pp. 565-577 ◽  
Author(s):  
Lucie Speyer ◽  
Océane Louppe ◽  
Sébastien Fontana ◽  
Sébastien Cahen ◽  
Claire Hérold
Keyword(s):  
Surface Area ◽  
High Surface ◽  
High Surface Area ◽  
Three Dimensional ◽  
Solvothermal Reaction ◽  
Synthesis Methods ◽  
Structure And Properties ◽  
Optimal Conditions ◽  
Experimental Conditions ◽  
Wide Range

AbstractGraphene-based materials are extensively studied, due to their excellent properties and their wide range of possible applications. Attention has recently been paid to three-dimensional-like graphenic structures, such as crumpled graphene sheets and graphenic foams: these kinds of materials can combine the properties of graphene associating high surface area and porosity, what is particularly interesting for energy or catalysis applications. Most of the synthesis methods leading to such structures are based on graphite oxide exfoliation and re-assembly, but in this work we focus on the preparation of graphenic foams by a solvothermal-based process. We performed a solvothermal reaction between ethanol and sodium at 220°C, during 72 h, under 200 bar, followed by a pyrolysis under nitrogen flow. An extended study of the influence of the temperature (800°C–900°C) of pyrolysis evidences an unexpected strong effect of this parameter on the characteristics of the materials. The optimal conditions provide multi-layer graphene (10 layers) foam with a surface area of 2000 m2·g−1. This work is an important step for the understanding of the mechanisms of the thermal treatment. Post-treatments in different experimental conditions are performed in order to modulate the structure and properties of the graphenic foams.

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