The classic methods of synthesis of graphene oxide derived from graphite require harsh oxidation with excessive chemicals (H2SO4, H3PO4, KMnO4, etc.) and multiple processes. In this paper, we present ...a facile one-pot process using HNO3 to obtain graphene oxide from coal (Coal-GO). Coal has a unique molecular structure comprising of small regions or clusters of graphene-like and aliphatic side chains, for which our process is successfully able to exclude aliphatic compounds while preserving graphene domains during oxidization and subsequent exfoliation. The Coal-GO was converted to reduced graphene oxide (Coal-rGO) by conventional method to produce a few-layered graphene nanosheets in lateral size of 300–700 nm. The surface characteristics of the Coal-GO indicate the persistence of N from the raw coal as well as that introduced in the process. Notably, the Coal-GO shows a considerable amount of COOH compared to the other oxygen groups. Our data indicates that the process is effective in oxidative scissoring of the edges of coal, with minimal effect on swelling of coal towards the c-direction. Lastly, we demonstrate that compared to Graphite-GO, the Coal-GO has superior interaction with single stranded DNA aptamer, which could result in higher sensitivity chemiluminescence resonance energy transfer-based biosensors.
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•Experimental and numerical study on array jet impingement on foams flushed with jets presented.•Different pore-densities 10, 20, 40 ppi and jet configurations x/d = 2,3 and 5 studied.•Largest pore ...density (40 ppi) and largest open area ratio jet configuration (x/d = 2) yield highest heat dissipation.
This paper reports an experimental and numerical investigation on flow and thermal transport in high porosity aluminum foams (ε~0.94–0.96) placed in a channel of square cross-section and subjected to jet array (5 × 5) impingement. The plate issuing the jets was flushed with the metal foam face. Experiments were conducted for three different values of jet-to-jet spacing (x/dj=y/dj) of 2, 3 and 5, and three foam samples with pore-densities 10, 20, and 40 PPI (pores per inch). Values of steady-state heat transfer rate and pressure drop were calculated for Reynolds number (based on channel hydraulic diameter and channel inlet velocity) ranging from 2500 to 13,500. The main findings are as follows: first, for all the test runs, the impingement configurations had higher heat transfer rate, h, compared to that for the baseline configuration of metal foams in a channel flow. Second, for all values of the jet-to-jet spacing, an increase in pore-density was accompanied by an increase in heat transfer. The enhancement (h/h0) varied between 26 and 48, with the highest gain observed for the widest jet (x/d=2) and the highest pore density (40 ppi) configuration, where h0 is the heat transfer coefficient for developed turbulent flow in a circular duct. The numerical computations reveal interesting recirculating flow structures immediately downstream of the jet exits and the extent of flow penetrating in the foam. Collectively, these flow patterns play a dominant role in determining the volume of metal foam volume participating in the thermal transport and the net convective heat transfer rate.
Abstract
Lactoferrin (LF) is a non-heme iron-binding glycoprotein involved in the transport of iron in blood plasma. In addition, it has many biological functions, including antibacterial, antiviral, ...antimicrobial, antiparasitic, and, importantly, antitumor properties. In this study, we have investigated the potential of employing lactoferrin-iron oxide nanoparticles (LF-IONPs) as a treatment modality for gastric cancer. The study confirms the formation of LF-IONPs with a spherical shape and an average size of 5 ± 2 nm, embedded within the protein matrix. FTIR and Raman analysis revealed that the Fe–O bond stabilized the protein particle interactions. Further, we conducted hyperthermia studies to ascertain whether the proposed composite can generate a sufficient rise in temperature at a low frequency. The results confirmed that we can achieve a temperature rise of about 7 °C at 242.4 kHz, which can be further harnessed for gastric cancer treatment. The particles were further tested for their anti-cancer activity on AGS cells, with and without hyperthermia. Results indicate that LF-IONPs (10 µg/ml) significantly enhance cytotoxicity, resulting in the demise of 67.75 ± 5.2% of cells post hyperthermia, while also exhibiting an inhibitory effect on cell migration compared to control cells, with the most inhibition observed after 36 h of treatment. These findings suggest the potential of LF-IONPs in targeted hyperthermia treatment of gastric cancer.
We report the findings of our experimental investigation on the performance of reduced graphene oxide (rGO)/silicone composite as a thermal interface material (TIM) influenced by the loading factor, ...surface functionality, and structural properties of graphene. The experimental data reveals that in addition to the loading factor, the thermal conductance of TIMs is greatly impacted by the density of oxygen-functionality (phenolic group) in rGO, and the morphological and structural properties introduced during the thermal reduction (deoxygenation) of graphene oxide to rGO. In particular, the phenolic groups prominently formed on the basal plane of rGO play a significant role in decreasing the interfacial thermal resistance. The results also show that the larger sp2 graphitic structures and the morphological properties of rGO increase the degree of dispersion in the matrix. A dynamic interplay between these factors determines the final value of the thermal conductance observed for different composites. An optimum combination of these factors led to the maximum thermal conductance (541 W/m2K) for the T-rGO600 (thermally-reduced graphene oxide processed at 600 °C)/silicone composite. The proposed underlying physics backed by the experimental data should be useful in designing high thermal performance TIMs with carbonaceous nanomaterials, including carbon nanotubes, graphene nanoplatelets, and carbon blacks acting as additives.
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Nanoporous graphene oxide (GO) membranes have shown great promise in separating water and ethanol with high flux and selectivity. The current design of these membranes focuses on tuning the pore ...sizes in GO sheets to achieve superior selectivity. In this paper, using molecular dynamics simulations, we study the feasibility of achieving effective water-ethanol separation by tuning the ionization of the functional groups on the periphery of pores in single-layer GO sheets. For pores featuring neutral carboxyl (COOH) groups, the water-to-ethanol selectivity coefficient is ∼7 when the pore diameter is 0.68 nm but decays to ∼1.5 when the pore diameter increases to ∼1.12 nm. However, our simulations suggest that through the ionization (deprotonation) of the COOH groups of the 1.12 nm-wide pores, we can achieve a water-to-ethanol selectivity coefficient of ∼7 in these pores. This improvement is mainly attributed to the enhanced (suppressed) accessibility of water (ethanol) molecules to the pore induced by the ionization of the functional groups.
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Metallic nanoparticles have emerged as a promising option for various biological applications, owing to their distinct characteristics such as small size, optical properties, and ability to exhibit ...luminescence. In this study, we have successfully employed a one-pot method to synthesize multifunctional insulin-protected iron Fe(II) nanoparticles denoted as IFe(II)NPs. The formation of IFe(II)NPs is confirmed by the presence of FTIR bonds at 447.47 and 798.28 cm
−1
, corresponding to Fe–O and Fe–N bonds, respectively. Detailed analysis of the HR-TEM-EDS-SAED data reveals that the particles are spherical in shape, partially amorphous in nature, and have a diameter of 28.6 ± 5.2 nm. Additionally, Metal Ion Binding (MIB) and Protein Data Bank (PDB) analyses affirm the binding of iron ions to the insulin hexamer. Our findings underscore the potential of IFe(II)NPs as a promising new platform for a variety of biomedical applications due to their high signal-to-noise ratio, and minimal background fluorescence. The particles are highly luminescent, biocompatible, and have a significant quantum yield (0.632). Exemplar applications covered in this paper include insulin receptor recognition and protection against reactive oxygen species (ROS), harmful molecules known to inflict damage on cells and DNA. The IFe(II)NPs effectively mitigate ROS-induced inflammation, which is a hinderance to wound recovery, thereby facilitating enhanced wound recovery.
Graphical abstract
In this paper, we present a novel method combining drop-casting GO dispersion with an Al-assisted partial reduction technique to fabricate a freestanding Janus GO/rGO film. The laminar structure of ...Janus film facilitates the diffusion pathway of water molecules efficiently. The asymmetrical oxygen content of the film promotes a significant gradient of moisture uptake in GO (hydrophilic) and rGO (hydrophobic) layers, resulting in a macroscopic deformation of the Janus film proportional to the change in relative humidity. The induced strain in the film changes the resistance of the rGO film, which systematically varies as a function of the strain amplitude or equivalently the change in relative humidity. In the range of relative humidity (5 to 100%), the resistance increases gradually with measurable change in response to a change in relative humidity (RH) as low as 1%, with the change being steeper at RH >85%. The results provide foundational knowledge for developing a relative humidity sensor with high sensitivity, excellent repeatability, and fast response-recovery without the complexity of the currently available interdigitated transducer-based humidity sensors.
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In this study, we compare the effect of various precursor‐based graphene oxide (GO) nanofillers on enhancing the mechanical performance of E‐glass fiber‐reinforced epoxy resin composites (EGFPs). GO ...derived from bituminous coal (BC‐GO) and graphite (Gr‐GO) were dispersed into an epoxy resin matrix. The resulting mixture was combined with E‐glass fiber mats using vacuum‐assisted resin infusion molding. Notable improvements (38.9% in flexural strength, 22.9% in tensile strength, and 21.6% in impact strength) were observed in BC‐GO‐reinforced EGFPs at 0.25 phr loading of BC‐GO. The improvements for Gr‐GO‐reinforced EGFPs were 28%, 9.3%, and 6.8%, respectively. XRD analysis of BC‐GO showed a diffraction peak at 2θ = 20.9°. Except for this peak, no other crystalline peaks were observed when BC‐GO was incorporated into EGFPs. FTIR spectra of both composite samples, with or without the nanofiller, were similar due to the spectral peaks overlap. TEM demonstrated the exfoliated morphology of BC‐GO in EGFPs. These findings underscore the potential of BC‐GO as a cost‐effective reinforcement for polymer nanocomposites across various industrial applications, including the development of lightweight and strong materials for aerospace and automotive industries, protective coatings, petroleum, and aerospace production systems.
Highlights
BC‐GO demonstrates superior mechanical performance compared to Gr‐GO in EGFPs.
0.25 phr BC‐GO improves 38.9% flexural, 22.9% tensile, and 21.6% impact strengths.
Beyond 0.25 phr, BC‐GO and Gr‐GO showed a decline in mechanical enhancement.
Role of particle size, loading & adhesion to matrix analyzed using XRD, FTIR, and DLS.
Coal‐GO is an attractive alternative nanofiller for EGFPs.
A comprehensive experimental study to assess the impact of bituminous coal‐derived graphene oxide (BC‐GO) and graphite‐derived graphene oxide (Gr‐GO) nanofillers on the mechanical properties of E‐glass fiber and epoxy resin composites.
Thermoelectric generators (TEGs) are rapidly becoming the mainstream technology for converting thermal energy into electrical energy. The rise in the continuous deployment of TEGs is related to ...advancements in materials, figure of merit, and methods for module manufacturing. However, rapid optimization techniques for TEGs have not kept pace with these advancements, which presents a challenge regarding tailoring the device architecture for varying operating conditions. Here, we address this challenge by providing artificial neural network (ANN) models that can predict TEG performance on demand. Out of the several ANN models considered for TEGs, the most efficient one consists of two hidden layers with six neurons in each layer. The model predicted TEG power with an accuracy of ±0.1 W, and TEG efficiency with an accuracy of ±0.2%. The trained ANN model required only 26.4 ms per data point for predicting TEG performance against the 6.0 minutes needed for the traditional numerical simulations.
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