Zeolitic-imidazolate frameworks-derived Co3S4/NiS@Ni foam heterostructure as highly efficient electrocatalyst for oxygen evolution reaction

Transition metals sulfide-based nanomaterials have recently received significant attention as a promising cathode electrode for the oxygen evolution reaction (OER) due to their easily tunable electronic, chemical, and physical properties. However, the poor electrical conductivity of metal-sulfide materials impedes their practical application in energy devices. Herein, firstly nano-sized crystals of cobalt-based zeolitic-imidazolate framework (Co-ZIF) arrays were fabricated on nickel-form (NF) as the sacrificial template by a facile solution method to enhance the electrical conductivity of the electrocatalyst. Then, the Co₃S₄/NiS@NF heterostructured arrays were synthesized by a simple hydrothermal route. The Co-ZIFs derived Co₃S₄ nanosheets are grown successfully on NiS nanorods during the hydrothermal sulfurization process. The bimetallic sulfide-based Co₃S₄/NiS@NF-12 electrocatalyst demonstrated a very low overpotential of 119 mV at 10 mA cm^?2 for OER, which is much lower than that of mono-metal sulfide NiS@NF (201 mV) and ruthenium-oxide (RuO₂) on NF (440 mV) electrocatalysts. Furthermore, the Co₃S₄/NiS@NF-12 electrocatalyst showed high stability during cyclic voltammetry and chronoamperometry measurements. This research work offers an effective strategy for fabricating high-performance non-precious OER electrocatalysts.     

Noncentrosymmetric Tetrel Pnictides RuSi4P4 and IrSi3P3: Nonlinear Optical Materials with Outstanding Laser Damage Threshold

Noncentrosymmetric (NCS) tetrel pnictides have recently generated interest as nonlinear optical (NLO) materials due to their second harmonic generation (SHG) activity and large laser damage threshold (LDT). Herein nonmetal-rich silicon phosphides RuSi₄P₄ and IrSi₃P₃ are synthesized and characterized. Their crystal structures are reinvestigated using single crystal X-ray diffraction and ²⁹Si and ³¹P magic angle spinning NMR. In agreement with previous report RuSi₄P₄ crystallizes in NCS space group P1, while IrSi₃P₃ is found to crystallize in NCS space group Cm, in contrast with the previously reported space group C2. A combination of DFT calculations and diffuse reflectance measurements reveals RuSi₄P₄ and IrSi₃P₃ to be wide bandgap (E_g) semiconductors, E_g = 1.9 and 1.8 eV, respectively. RuSi₄P₄ and IrSi₃P₃ outperform the current state-of-the-art infrared SHG material, AgGaS₂, both in SHG activity and laser inducer damage threshold. Due to the combination of high thermal stabilities (up to 1373 K), wide bandgaps (≈2 eV), NCS crystal structures, strong SHG responses, and large LDT values, RuSi₄P₄ and IrSi₃P₃ are promising candidates for longer wavelength NLO materials.     

The effect of rice bran on physicochemical,textural and glycaemic properties of ready-to-eat extruded corn snacks

In this work, corn extruded snack products were enriched with rice bran (RB) at 10% and 15%. A co-rotating twin-screw extruder was used with a feed moisture content of 16 g 100 g⁻¹, a screw speed of 240 r.p.m. and four heating sections of the barrel (100, 140, 150 and 150 °C). The impact of RB inclusion on nutritional profile, starch digestion, physicochemical and textural properties of snack products was evaluated. RB-enriched extrudates showed a lower specific volume and hardness and higher crispness than control. RB at 15% gave a water-holding capacity lower than control. Rheology of extrudate dispersions indicated an increase in elastic interactions and solid-like behaviour with RB supplementation. Differences in rheological properties resulted in attenuation of predictive glycaemic response for RB-enriched snacks.     

Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

The role of microbial electrogenesis in regulating methane and nitrous oxide emissions from constructed wetland-microbial fuel cell

This study assesses a sustainable solution to greenhouse gases (GHGs) mitigation using constructed wetland-microbial fuel cells (CW-MFC). Roots of wetland plant Acorus Calamus L. are placed in biological anode to better enable anode microorganisms to obtain rhizosphere secretion for power improvement. Three selected cathode materials have a large difference in GHG emissions, and among them, carbon fiber felt (CFF) shows the lowest emissions of methane and nitrous oxide, which are 0.77 ± 0.04 mg/(m²·h) and 130.78 ± 13.08 μg/(m²·h), respectively. The CFF CW-MFC achieves the maximum power density of 2.99 W/m³. As the influent pH value is adjusted from acidic to alkaline, the GHGs emissions are reduced. The addition of Ni inhibits GHGs emission but decreases the electricity, the power density is reduced to 1.09 W/m³, and the methane and nitrous oxide emission fluxes decline to 0.20 ± 0.04 mg/(m²·h) and 15.49 ± 1.86 μg/(m²·h), respectively. Low C/N ratio reduces methane emission, while high C/N ratio effectively inhibits nitrous oxide emission. At the influent pH 8 and C/N = 5:1, the methane emission flux is approximately 10.60 ± 0.27 mg/(m²·h), and the nitrous oxide emission flux is only 10.90 ± 1.10 μg/(m²·h). Based on the above experimental results by controlling variable factors, it is proposed that CW-MFC offers an environment-friendly solution to regulate GHG emissions.     

Psychrophilic hydrogen production from petrochemical wastewater via anaerobic sequencing batch reactor: techno-economic assessment and kinetic modelling

Independent hydrogen production from petrochemical wastewater containing mono-ethylene glycol (MEG) via anaerobic sequencing batch reactor (ASBR) was extensively assessed under psychrophilic conditions (15–25 °C). A lab-scale ASBR was operated at pH of 5.50, and different organic loading rates (OLR) of 1.00, 1.67, 2.67, and 4.00 gCOD/L/d. The hydrogen yield (HY) progressed from 134.32 ± 10.79 to 189.09 ± 22.35 mL/gMEG_initial at increasing OLR from 1.00 to 4.00 gCOD/L/d. The maximum hydrogen content of 47.44 ± 3.60% was achieved at OLR of 4.0 gCOD/L/d, while methane content remained low (17.76 ± 1.27% at OLR of 1.0 gCOD/L/d). Kinetic studies using four different mathematical models were conducted to describe the ASBR performance. Furthermore, two batch-mode experiments were performed to optimize the nitrogen supplementation as a nutrient (C/N ratio), and assess the impact of salinity (as gNaCl/L) on hydrogen production. HY substantially dropped from 62.77 ± 4.09 to 6.02 ± 0.39 mL/gMEG_initial when C/N ratio was increased from 28.5 to 114.0. Besides, the results revealed that salinity up to 10.0 gNaCl/L has a relatively low inhibitory impact on hydrogen production. Eventually, the cost/benefit analysis showed that environmental and energy recovery revenues from ASBR were optimized at OLR of 4.0 gCOD/L/d (payback period of 7.13 yrs).     

Transmission system restoration with co-optimization of repairs,load pickups,and generation dispatch

This paper studies the restoration of a transmission system after a significant disruption such as a natural disaster. It considers the co-optimization of repairs, load pickups, and generation dispatch to produce a sequencing of the repairs that minimizes the size of the blackout over time. The core of this process is a Restoration Ordering Problem (ROP), a non-convex mixed-integer nonlinear program that is outside the capabilities of existing solver technologies. To address this computational barrier, the paper examines two approximations of the power flow equations: The DC model and the recently proposed LPAC model. Systematic, large-scale testing indicates that the DC model is not sufficiently accurate for solving the ROP. In contrast, the LPAC power flow model, which captures line losses, reactive power, and voltage magnitudes, is sufficiently accurate to obtain restoration plans that can be converted into AC-feasible power flows. An experimental study also suggests that the LPAC model provides a robust and appealing tradeoff between accuracy and computational performance for solving the ROP.