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The copper (Cu) biotic ligand model (BLM) has been used for ecological risk assessment by taking into account the bioavailability of Cu in freshwater. The Cu BLM requires data for many water chemistry variables, such as pH, major cations, and dissolved organic carbon, which can be difficult to obtain from water quality monitoring programs. To develop an optimized predicted no‐effect concentration (PNEC) estimation model based on an available monitoring dataset, we proposed an initial model that considers all BLM variables, a second model that requires variables excluding alkalinity, and a third model using electrical conductivity as a surrogate for the major cations and alkalinity. Furthermore, deep neural network (DNN) models have been used to predict the nonlinear relationships between the PNEC (outcome variable) and the required input variables (explanatory variables). The predictive capacity of DNN models was compared with the results of other existing PNEC estimation tools using a look‐up table and multiple linear and multivariate polynomial regression methods. Three DNN models, using different input variables, provided better predictions of the Cu PNECs compared with the existing tools for the following four test datasets: Korean, United States, Swedish, and Belgian freshwaters. Consequently, it is expected that Cu BLM–based risk assessment can be applied to various monitoring datasets, and that the most applicable model among the three different types of DNN models could be selected according to data availability for a given monitoring database. Environ Toxicol Chem 2023;42:2271–2283. © 2023 SETAC [ABSTRACT FROM AUTHOR]

Biotic ligand models (BLMs) and the sensitivities of indigenous species are used to assess the environmental risk considering the bioavailability of metals, such as nickel. However, the BLM‐based acute–to–chronic ratio (ACR) is required if the predicted no‐effect concentration (PNEC) cannot be derived from the chronic species sensitivity distribution (SSD). The applicability of the ACR approach for estimating BLM‐based PNEC for nickel from acute toxicity data was evaluated in the present study. The BLM‐based acute SSD for nickel was built using the sensitivities of 21 indigenous species and different taxon‐specific BLMs for each taxonomic group. To predict the acute sensitivity of invertebrates, the chronic crustacean nickel BLM with pH effect term, which can account for nickel toxicity at high pH levels, was used. This was used instead of the existing acute BLM for crustacean, which has too narrow a pH range to cover the pH dependency of toxicity. The final BLM‐based ACR of nickel, determined within a factor of 1.53 from the species‐specific acute and chronic sensitivities of the six species, was more reliable than the typical ACR estimated within a factor of 1.84. A linear relationship (r2 = 0.95) was observed between the PNECs using BLM‐based ACR and the PNECs derived from the BLM‐based chronic SSD of the European Union Risk Assessment Reports. In conclusion, the BLM‐based PNEC for nickel could be derived using the ACR approach, unlike when copper BLM was applied. The BLM‐based ACR for nickel is the first result calculated by directly comparing acute and chronic species sensitivities, and will contribute to the application of BLM‐based risk assessment in broader ecoregions. Environ Toxicol Chem 2023;42:914–927. © 2023 SETAC [ABSTRACT FROM AUTHOR]

Nanocomposites based on biomaterials are promising candidates for emerging green‐ electronics benefiting from environment‐friendly, renewable, biocompatible, and biodegradable resources for sustainable research and development. Especially, the application of biocomposites‐based memristor for simulating artificial synapses called bio‐memristor has further facilitated the progress of ecologically benign bioelectronics. In this study, the authors present that the environment‐friendly nanocomposites films, consisting of Ag nanoparticles and cellulose nanocrystal (CNC)‐based bio‐memristor with excellent bipolar resistive switching behavior can perform the artificial bio‐synaptic emulation with continuous resistance modulation for memory storage and neuromorphic computing applications. The bio‐memristor exhibits a large resistive switching (ION/OFF as high as ≈104 and ultralow SET/RESET voltage of ≈0.2 V) and reliable switching characteristics through the electrochemical formation/rupture of Ag metallic filaments within the nanocomposite layer. The device presents coexistence of digital and analog switching properties favorable for both nonvolatile digital memory and neuromorphic computing applications. By applying appropriate pulse stimulations to the device, the authors demonstrate biological synaptic functions, including long‐term potentiation/depression, spike‐rate‐dependent plasticity, excitatory post‐synaptic current, paired‐pulse facilitation, and paired‐pulse depression. Thus, this CNC‐based bio‐memristor as an effective artificial synaptic device is beneficial towards the realization of green‐electronics and bio‐inspired neuromorphic systems. [ABSTRACT FROM AUTHOR]

In this study, we demonstrated the temperature effect of our previously developed topotatic catalysis for the formation of Mn0.005Co2.995O4 (MnCoO) spinel nanoparticles. Topotatic catalysis induces spinel MnCoO nanoparticles through the redox reaction of the metal cation (Co2+ and Mn2+) on the Co(OH)2 nanosheet surface, acting as a growth template. This study particularly elucidates the temperature effect on spinel MnCoO nanoparticles' size, morphology, and crystallinity based on their electrocatalytic performance in an oxygen reduction reaction (ORR). We found that lower temperature produces an amorphous phase, whereas higher temperature induces a large aggregate. We obtained the monodispersed MnCoO nanocubes at approximately 90°C, exhibiting the best ORR performance with an electron‐transfer number of 3.86. [ABSTRACT FROM AUTHOR]

A Mg(II)‐based coordination polymer was synthesized by a solvothermal reaction between Mg2+ and 2,5‐dimercaptoterephthalic acid (H4dmtp) in N,N‐diethylformamide (DEF). The thiol (─SH) groups in the H4dmtp ligand were oxidized to form the sulfinato (─SO2−) groups, which were structurally stabilized through coordination to the Mg2+ centers. The temperature‐dependent proton conductivities exhibited relatively low activation energy (0.19 eV) for proton transfer, suggesting that the hydrogen‐bonded networks formed by the water molecules and the sulfinato oxygen atoms produced efficient proton‐hopping pathways. [ABSTRACT FROM AUTHOR]

A highly effective way to produce an oxygen reduction electrocatalyst was developed through the self‐assembly of exfoliated single layers of cobalt hydroxide (Co(OH)2) and graphene oxide (GO). These 2D materials have complete contact with one another because of their physical flexibility and the electrostatic attraction between negatively charged GO and positively charged Co(OH)2 layers. The strong coupling induces transformation of the Co(OH)2 single layer into a discrete nanocrystal of spinel Co3O4 with an average size of 8 nm on reduced GO (RGO) during calcination, which could not be obtained with bulk‐layered cobalt hydroxide because of its rapid layer collapse. The ultrafine Co3O4/RGO hybrid exhibited not only comparable performance in the oxygen reduction reaction but also higher durability compared with the commercial 20 wt % Pt/C catalyst. [ABSTRACT FROM AUTHOR]

Abstract: The high‐temperature stability of YSZ and MSZ specimens was investigated in CaF2–MgF2–MgO molten salt at 1200°C. YSZ was mostly composed of m‐ZrO2 and a small part of YF3 in the early stages. The formation of YF3 was attributed to the chemical reaction between Y2O3 and MgF2, which can lead to the leaching of Y2O3 from YSZ. With an increase in exposure time, the degraded surface was coarser, and considerable amount of cracks, pores, and spallations were formed. Furthermore, no Y2O3 was found up to 120 μm of the YSZ bulk in the early stages. MSZ was composed of t‐ZrO2 after 24 hours. However, the volume fraction of m‐ZrO2 was 72% after 72 hours, and CaZrO3 was formed by the chemical reaction between CaO and ZrO2 after 168 hours. In addition, the volume fraction of m‐ZrO2 was 60% in 2.5 wt% MgO and 49% in 10 wt% MgO. In 5 wt% MgO, CaZrO3 was formed. We demonstrate that the high‐temperature stability of MSZ was better than that of YSZ, and that 10 wt% MgO was much more stable than the other concentrations of MgO. [ABSTRACT FROM AUTHOR]

AbstractThe liquid exfoliation of hydrotalcite-like α-Co(OH)2 in formamide produced a new pink β-form of Co(OH)2 nanosheets [Ex-NS-Co(OH)2] with unique nanoscopic properties: a larger surface area of active hydroxides and a much narrower oxidation–reduction potential for the Co2+ ions in the hydroxide layer than those of the bulk α-Co(OH)2. These unprecedented properties of Ex-NS-Co(OH)2 were applied to the topochemical synthesis of crystalline Co3O4 nanocubes (NCs) with clear edges and no impurity phases from an aqueous solution of Co2+ ions at 70 °C. A Co3O4 NC/C catalyst exhibited good catalytic activity for the oxygen reduction reaction (ORR) and higher stability under a continuous electrochemical operation than that of commercial Pt/C. [ABSTRACT FROM AUTHOR]

We demonstrate the facile microwave-assisted synthesis of a porous organic framework 1 and the sulfonated solid ( 1S) through postsubstitution. Remarkably, the conductivity of 1S showed an approximately 300-fold enhancement at 30 °C as compared to that of 1, and reached 7.72×10−2 S cm−1 at 80 °C and 90 % relative humidity. The superprotonic conductivity exceeds that observed for any conductive porous organic polymer reported to date. This material, which is cost-effective and scalable for mass production, also revealed long-term performance over more than 3 months without conductivity decay. [ABSTRACT FROM AUTHOR]

Combustion based synthesis of AlN nanoparticles using the "solid nitrogen" promotion reaction was investigated in Al2O3 + 3Mg system in nitrogen atmosphere. A controlled amount of Mg + 0.5NH4Cl mixture as a solid source of nitrogen was blended with the Al2O3 + 3Mg starting system and the synthesis reaction of AlN nanoparticles was conducted using the exothermic heat of the entire reaction system. The resulting AlN nanoparticles were characterized by X-ray diffraction (XRD), Raman and Fourier transform infrared spectroscopy (FTIR), PL spectroscopy, field-emission scanning electron microscopy, transmission electron microscopy, and Brunauer-Emmett-Teller surface area techniques. The analysis results confirmed that single phase and crystalline AlN nanoparticles with an average size of 50-500 nm were obtained from the developed approach. Photoluminescence spectra of AlN nanopowders under the excitation of 230-270 nm UV light revealed that AlN emits yellow-red light having a wavelength near to 590 nm. The chemistry of the combustion process is discussed and the basic reactions that led to the formation of AlN are presented. [ABSTRACT FROM AUTHOR]

We have developed a simple and facile method to fabricate gold nanoparticles (Au NPs) deposited on thin films of layered double hydroxide (LDH) nanocrystals. The oriented thin film of LDH nanocrystals was employed for the preferential deposition of Au NPs by in situ growth of Au NPs on the monolayer thin film of LDH nanocrystals, which effectively provided a large and uniform active hydroxide surface for deposition of a dense monolayer of Au NPs. The reactive hydroxide groups and the positive potential of the LDH surfaces play an important role in the uniform growth of the Au NPs and in their stabilization against agglomeration. This LDH-supported Au NP catalyst exhibits superior catalytic efficiency and reusability without significant loss in conversion efficiency for the reduction of p-nitrophenol with NaBH4, maintaining more than 96 % catalytic conversion efficiency. [ABSTRACT FROM AUTHOR]

RATIONALE: Quantifying polymers by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) with a conventional crystalline matrix generally suffers from poor sample-to-sample or shot-toshot reproducibility. An ionic-liquid matrix has been demonstrated to mitigate these reproducibility issues by providing a homogeneous sample surface, which is useful for quantifying polymers. In the present study, we evaluated the use of an ionic liquid matrix, i.e., 1-methylimidazolium α-cyano-4-hydroxycinnamate (1-MeIm-CHCA), to quantify polyhexamethylene guanidine (PHMG) samples that impose a critical health hazard when inhaled in the form of droplets. METHODS: MALDI-TOF mass spectra were acquired for PHMG oligomers using a variety of ionic-liquid matrices including 1-MeIm-CHCA. Calibration curves were constructed by plotting the sum of the PHMG oligomer peak areas versus PHMG sample concentration with a variety of peptide internal standards. RESULTS: Compared with the conventional crystalline matrix, the 1-MeIm-CHCA ionic-liquid matrix had much better reproducibility (lower standard deviations). Furthermore, by using an internal peptide standard, good linear calibration plots could be obtained over a range of PMHG concentrations of at least 4 orders of magnitude. CONCLUSIONS: This study successfully demonstrated that PHMG samples can be quantitatively characterized by MALDI-TOFMS with an ionic-liquid matrix and an internal standard. [ABSTRACT FROM AUTHOR]

The article offers an approach to prepare the exfoliated layered double hydroxide (LDH) nanosheet decorated with dense and uniform platinum (Pt) nanoparticals (NPs) through a precursor-exchange and a thermal reduction process. Topics discussed include the LDH nanosheet colloiding in formamide prepared by exfoliation of the nitrate form of the LDH nanocrystals; and dense and uniform Pt NPs being synthesized on the exfoliated LDH nanosheets through precursor exchange of the precursor ions.

A novel 2-dimensional catalytic system was developed in which platinum nanoparticles (Pt NPs) were immobilized on exfoliated MgAl-layered double hydroxide (LDH) nanosheets through an electrostatic self-assembly between negatively charged Pt NPs and positively charged LDH nanosheets. The LDH nanosheets effectively provided the large double sides of hydroxide functionality to absorb the Pt NPs, as well as fast diffusion rates of the incoming reactants into catalyst surfaces. This new nanostructure improved the rate of reaction, turnover frequency and reaction durability of Pt NPs on LDH nanosheet without significant loss in conversion efficiencies for the reduction of p-nitrophenol into p-aminophenol by NaBH4, maintaining more than 97% of catalytic conversions compared to free Pt NPs as well as commercial Pt/C catalyst. [ABSTRACT FROM AUTHOR]

The article presents a study on electrochemical properties of gold nanoparticles (Au NPs) and its electrocatalytics activity for glucose oxidation. Topics discussed include use of electrochemical oxidation of glucose for applications in glucose-oxygen fuel cells and in glucose sensors, optical properties of the nanocomposite of Au NPs and layered double hydroxide (LDH) nanosheet, and development of Au NPs and exfoliated LDH nanosheet by chemical reduction with sodium borohydride (NaBH4).

Two models, a Epolycyclic aromatic hydrocarbon (PAH) model based on equilibrium partitioning theory and a logistic-regression model, weredeveloped and evaluated to predict sediment-associated PAH toxicity to Hyalella azteca. A EPAH model was applied to freshwater sediments.This study is the first attempt to use a EPAH model based on water-only, median lethal concentration (LC50) toxic unit (TU) values for sediment-associated PAH mixtures and its application to freshwater sediments. To predict the toxicity (i.e., mortality) from contaminated sediments to H. azteca, an interstitial water TU, calculated as the ambient interstitial water concentration divided by the water-only LC50 in which the interstitial water concentrations were predicted by equilibrium partitioning theory, was used. Assuming additive toxicity forPAH, the sum of TUs was calculated to predict the total toxicity of PAH mixtures in sediments. The EPAH model was developed from 10- and 14-d H. azteca water-only LC50 values. To obtain estimates of LC50 values for a wide range of PAHs, a quantitative structure-activity relationship (QSAR) model (log LC50 -log Kow) with a constant slope was derived using the time-variable LC50 values for four PAH congeners. The logistic-regression model was derived to assess the concentration-response relationship for field sediments, which showed that 1.3 (0.6-3.9) TU were required for a 50% probability that a sediment was toxic. The logistic-regression model reflects both the effects of co-occurring contaminants (i.e., nonmeasured PAH and unknown pollutants) and the overestimation of exposure to sediment-associated PAH.An apparent site-specific bioavailability limitation of sediment-associated PAH was found for a site contaminated by creosote. At this site, no toxic samples were less than 3.9 TU. Finally, the predictability of the EPAH model can be affected by species-specific responses (Hyalella vs Rhepoxynius); chemical specific (PAH vs DDT in H. azteca) bias [ABSTRACT FROM AUTHOR]