Search

We have grown arrays of silver nanowires in pores of anodic alumina membranes (metamaterials with hyperbolic dispersion at λ ≥ 615 nm), spin coated them with the dye-doped polymer (HITC:PMMA), and studied the rates of radiative and nonradiative relaxation as well as the concentration quenching (Förster energy transfer to acceptors). The results were compared to those obtained on top of planar Ag films and glass (control samples). The strong spatial inhomogeneity of emission kinetics recorded in different spots across the sample and strong inhibition of the concentration quenching in arrays of Ag nanowires are among the most significant findings of this study.

Recent advancements in computing technologies coupled with the need to make sense of large amounts of raw data have renewed much interest in data-driven materials design and discovery. Traditional materials science research relies heavily on experimental data to gauge the properties of materials. However, this paradigm is purely based on trial and error and ongoing research can take decades to discover new materials. Data-driven modeling tools such as machine learning and its proven libraries can help speed up the materials' discovery process through the implementation of powerful algorithms on readily available material datasets mined from the ever-increasing private- and government-funded material databases. In this Perspective, we applied various machine learning models on tens of hundreds of thermoelectric compounds obtained from density functional theory calculation results. In our preliminary analysis, we made use of pymatgen and the powerful materials science library matminer to add and explore key material features that have the propensity to accurately predict our achievable target output. We evaluated the accuracy and performance of our models with the coefficient of determination (R2), the root mean square error, and K-fold cross-validation metrics and identified the most important descriptors for our materials. Finally, we reviewed the current state-of-the-art in data-driven thermoelectric materials' design and discovery, its current challenges, and prospects. [ABSTRACT FROM AUTHOR]

Thin-film transparent heaters (TFTHs) are gaining popularity in optoelectronics and a variety of domestic applications, including smart windows, car defrosters, and other devices. The deposition and characterization of TFTHs made of gallium-doped zinc oxide (GZO) are presented in this work. GZO thin films were deposited via pulsed laser deposition on glass substrates with varying oxygen partial pressures from 0 to 10 mTorr during deposition. The samples demonstrated very low sheet resistance values between 5 and 17 Ω/sq from 0 to 10 mTorr, respectively. UV/vis transmission spectra revealed that TFTHs have a high optical transparency above 80%. GZO-based TFTHs demonstrated a consistent and repeatable joule heating effect, with temperatures reaching 76 °C with a low input voltage of 10 V. This research could guide the future use of GZO as a transparent conducting oxide material for many potential cost-effective applications from low-powered electronics to lightweight and wearable devices. [ABSTRACT FROM AUTHOR]

The drawbacks of common anodes in lithium-ion batteries (LIBs) and hybrid supercapacitors (HSCs), such as the high voltage plateau of Li4Ti5O12 (1.55 V vs. Li/Li+) and the moderate capacity of graphite (372 mAh-g-1), have established a need for better materials. Conversion materials, and in particular iron oxide and CaFe2O4 (CFO), have amassed recent attention as potential anode replacements. In this study, we evaluate the material and electrochemical effects of the solution combustion synthesis (SCS) of porous CFO across novel fuel-to-oxidizer ratios and calcination temperatures. We demonstrate that nearly doubling the amount of fuel used during synthesis increases capacities between 120 and 150% at high current densities (~ 1000 mA-g-1) and across 500 additional charging-discharging cycles, an effect brought on in part by enhanced compositional purity in these samples. However, in order to ensure long-term cyclic stability, it is necessary to also calcine porous CFO to 900 °C to enhance crystallite size, particle size and spacing, and compositional purity. [ABSTRACT FROM AUTHOR]

All-solid-state batteries (ASSBs) are gaining traction in the arena of energy storage due to their promising results in producing high energy density and long cycle life coupled with their capability of being safe. The key challenges facing ASSBs are low conductivity and slow charge transfer kinetics at the interface between the electrode and the solid electrolyte. Garnet solid-state electrolyte has shown promising results in improving the ion conductivity but still suffers from poor capacity retention and rate performance due to the interfacial resistance between the electrodes. To improve the interfacial resistance, we prepared a composite consisting of Li7La2.75Ca0.25Zr1.75Nb0.25O12 (LLCZN) garnet material as the ceramic, polyethylene oxide (PEO) as the polymer, and lithium hexafluorophosphate (LiPF6) as the salt. These compounds are mixed in a stoichiometric ratio and developed into a very thin disc-shaped solid electrolyte. The LLCZN provides a lithium-ion transport path to enhance the lithium-ion conduction during charging and discharging cycles, while the LiPF6 contributes more lithium ions via the transport path. The PEO matrix in the composite material aids in bonding the compounds together and creating a large contact area, thereby reducing the issue of large interfacial resistance. FESEM images show the porous nature of the electrolyte which promotes the movement of lithium ions through the electrolyte. The fabricated LLCZN/PEO/LiPF6 solid-state electrolyte shows outstanding electrochemical stability that remains at 130 mAh g−1 up to 150 charging and discharging cycles at 0.05 mA cm−2 current. All the specific capacities were calculated based on the mass of the cathode material (LiCoO2). In addition, the coin cell retains 85% discharge capacity up to 150 cycles with a Coulombic efficiency of approximately 98% and energy efficiency of 90% during the entire cycling process. [ABSTRACT FROM AUTHOR]