First and Second Reductions in an Aprotic Solvent: Comparing Computational and Experimental One-Electron Reduction Potentials for 345 Quinones
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Nitrous oxide (N 2 O) is the third largest contributor to anthropogenic greenhouse gas emissions and plays a detrimental role in the depletion of ozone. Despite the contribution of N 2 O as an atmospheric pollutant, there are currently only a few examples of electrochemical N 2 O remediation to N 2 . Herein we report the electrocatalytic deoxygenation of N 2 O by iron tetraphenylporphyrin (FeTPP) to form N 2 with quantitative Faradaic efficiency and an observed rate of 1.91 s –1 . No degradation was observed after controlled potential electrolysis. Mechanistic investigation of the proposed catalytic steps determined that hydrogen-bond donors are critical for accelerating N 2 O activation and that proton transfer is involved in the rate-determining step.
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Dynamic load models add significant complexity to bulk power system time-domain simulations. The complexity is due to the large number of ordinary differential equations (ODEs) introduced by the dynamic load components such as induction motors. It is challenging to derive reduced-order models (ROMs) for dynamic loads due to the nonlinear functions in their governing equations. This paper applies the discrete empirical interpolation method enhanced proper orthogonal decomposition (DEIM-POD) to approximate the full dynamic load model with the ROM that minimizes the projection error of the nonlinear functions in dynamic load ODEs onto their dominant modes. This approach only requires evaluation of nonlinear functions at selected observation points. The observation points selected by DEIM also provide information for screening critical load buses where dynamic load model parameters contribute the most to the accuracy of ROM across multiple contingencies. The proposed approach is validated on IEEE 9-bus, WECC 179-bus and 2384-bus Polish systems.
A techno-economic analysis is underway examining the cost and performance of future large-scale photovoltaic (PV) plant components, including bifacial modules, tandem modules, increased plant voltage architectures, and module-level power electronics. Integration of these components into PV plant designs is compared with current PV technologies based on levelized cost of electricity (LCOE). Baseline models are developed and validated against recorded PV plant performance data. Expected cost and performance data of future PV technologies are incorporated into the baseline models. An evolutionary algorithm is utilized to optimize PV plant configuration, technology combination, and LCOE. Furthermore, this paper focuses on the bifacial module analysis.
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Due to the irregular nature of real waves, the power captured in a wave energy converter (WEC) system is highly variable. This is an important barrier to the effective use of WECs. To address this challenge, this study focuses on a rotational WEC power-take-off system in which high-speed and high-efficiency generators along with a torque/power smoothing inertia element can be effectively utilized. In the first phase of this study, the U.S. Department of Energy’s reference model 3 (WEC-Sim RM3; two-body point absorber), along with a slider-crank WEC, were integrated for linear to rotational conversion. Relative motion between the float and spar in RM3 was the driving force for this slider-crank WEC, which is connected to a motor/generator set through a gearbox. RM3 geometry was scaled down by 25 times to work within the limits of the physical motor/generator set used in the experimentation. Once the integration in a hardware-in-the-loop simulation environment was successfully completed, data on the peak-to-average power ratio was collected for various wave conditions including regular and irregular waves. The control algorithm designed to keep the system in resonance with waves was able to maintain relatively high speed depending on the specific gear ratio and wave period. Initial results with hardware-in-the-loop simulations reveal that gear ratio and crank radius have a strong impact on the peak-to-average power ratio. In addition, it was found that output power from the generator was maximized at a larger gear ratio, as the crank radius was increased.
High temperature structural acoustic sensors play an important role in many applications. Fused quartz waveguide is a popular choice due to its resistance to harsh environments and its convenience of modification. However, time of flight between pulse and echo, which is widely used in these sensors, tends to encounter drifts in fast temperature changing process even after temperature returns to initial value. In this article, different annealing process are performed for a special modified fused quartz waveguide with a sensor node. Annealing treatment is found able to reduce the drift when the waveguide undergoes a sudden temperature spike to 1000 °C at 500 kHz operating acoustic frequency, and the best annealing condition could make the drift one magnitude smaller. A following temperature test up to 1000 °C shows consistent measurement readings.
The enzyme nitrogenase uses a suite of complex metallocofactors to reduce dinitrogen (N 2 ) to ammonia. Mechanistic details of this reaction remain sparse. We report a 1.83-angstrom crystal structure of the nitrogenase molybdenum-iron (MoFe) protein captured under physiological N 2 turnover conditions. This structure reveals asymmetric displacements of the cofactor belt sulfurs (S2B or S3A and S5A) with distinct dinitrogen species in the two αβ dimers of the protein. The sulfur-displaced sites are distinct in the ability of protein ligands to donate protons to the bound dinitrogen species, as well as the elongation of either the Mo–O5 (carboxyl) or Mo–O7 (hydroxyl) distance that switches the Mo-homocitrate ligation from bidentate to monodentate. These results highlight the dynamic nature of the cofactor during catalysis and provide evidence for participation of all belt-sulfur sites in this process.
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While strategies to achieve net-zero emissions at an individual site are well understood, new analysis methods are required for organizations seeking to achieve net-zero across multiple facilities, each with concurrent priority goals. At a portfolio level, distinct locations present varied challenges that cannot be addressed through singular solutions, and competing goals can take precedence with the assumption that net-zero emissions strategies deter from energy resilience and cost savings, therefore negatively impacting nearby communities. This study tests these assumptions by analyzing 16 diverse sites (varying in size, climate, and energy use) to identify strategies that reduce emissions and assess the impact these strategies have on life cycle costs, resilience, and communities with environmental justice concerns. Methods were developed to approximate missing information essential to net-zero evaluation. Established methods were augmented to evaluate life cycle costs, resilience, and environmental justice impacts across a set of strategies and accommodate the multi-criteria analyses. Potential benefits from identified strategies were quantified using site characteristics and a set of corresponding metrics. The net-zero analysis found that 11 sites could use on-site strategies to eliminate all but 2% of emissions generated. The remaining emissions can be offset, for instance through sequestration, executed at the portfolio scale. On-site carbon-free energy was found to reduce 51% of emissions across all sites; efficiency reduced 19% of emissions; sequestration 16%; procured carbon-free energy 15%; fuel switching 1.6%; and fleet electrification 1.3%. Building electrification, however, increased emissions by 4.4%. Different strategies also provide cost, resilience, and/or environmental justice benefits—the degree to which varies with individual site conditions. The findings indicate an advantage to considering the strategies as a comprehensive set, which leads to co-benefits, both in the ability to achieve net-zero goals and in advancing other goals. The results present the case for comprehensive advanced planning at the portfolio level to prioritize investments that will balance the minimization of emissions and life cycle cost with the maximization of resilience and environmental justice benefits. The novel methods for evaluation and integration, valuation of benefits, and consideration at the portfolio scale allow organizations to select investments that simultaneously address multiple key priorities.
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