Synergistic enhancement of H2 and CH4 evolution by CO2 photoreduction in water with reduced Graphene oxide–bismuth monoxide quantum dot catalyst

Photocatalytic water splitting or CO2 reduction is one of the most promising strategies for solar energy conversion into hydrogen-containing fuels. However, these two processes typically compete with each other, which significantly decreases the solar energy conversion efficiency. Herein, we report for the first time this competition can be overcome by modulation of reactive sites and electron transfer pathway of heterogeneous photocatalysts. As a prototype, BiO composite reduced graphene oxide quantum dots (RGO-BiO QDs) were synthesized, which can provide large amounts of photogenerated electrons as well as individual reactive sites for H+ and CO2 reduction. The productivity of H2, CH4, and CO by the RGO-BiO QDs catalyst were 102.5, 21.75, and 4.5 μmol/(g·h), respectively, in pure water without the assistance of any cocatalyst or sacrificial agent. The apparent quantum efficiency at 300 nm reached to 4.2%, which is more than 10 times higher than that of RGO-TiO2 QDs (0.28%) under the same conditions. In situ DRIFT, ESR, and photoelectrochemical studies confirmed that the unique circled electron transfer pathway (Evb(BiO) → Ecb(BiO) → Ef(RGO) → EVo•(BiO)) and the large amount of separated different reactive sites are responsible for the highly efficient simultaneous H2 evolution and CO2 reduction performance

Contextual Dynamic Pricing with Strategic Buyers

Personalized pricing, which involves tailoring prices based on individual characteristics, is commonly used by firms to implement a consumer-specific pricing policy. In this process, buyers can also strategically manipulate their feature data to obtain a lower price, incurring certain manipulation costs. Such strategic behavior can hinder firms from maximizing their profits. In this paper, we study the contextual dynamic pricing problem with strategic buyers. The seller does not observe the buyer's true feature, but a manipulated feature according to buyers' strategic behavior. In addition, the seller does not observe the buyers' valuation of the product, but only a binary response indicating whether a sale happens or not. Recognizing these challenges, we propose a strategic dynamic pricing policy that incorporates the buyers' strategic behavior into the online learning to maximize the seller's cumulative revenue. We first prove that existing non-strategic pricing policies that neglect the buyers' strategic behavior result in a linear $\Omega(T)$ regret with $T$ the total time horizon, indicating that these policies are not better than a random pricing policy. We then establish that our proposed policy achieves a sublinear regret upper bound of $O(\sqrt{T})$. Importantly, our policy is not a mere amalgamation of existing dynamic pricing policies and strategic behavior handling algorithms. Our policy can also accommodate the scenario when the marginal cost of manipulation is unknown in advance. To account for it, we simultaneously estimate the valuation parameter and the cost parameter in the online pricing policy, which is shown to also achieve an $O(\sqrt{T})$ regret bound. Extensive experiments support our theoretical developments and demonstrate the superior performance of our policy compared to other pricing policies that are unaware of the strategic behaviors

Identification of Active Sites for Oxygen Reduction Reaction on Nitrogen- and Sulfur-Codoped Carbon Catalysts

This research was financially supported by ERA.Net RUS Plus funding mechanism (Project HeDoCat) and by the European Regional Development Fund project TK134.Nitrogen- and sulfur-codoped carbon catalysts were prepared as electrocatalytic materials for the oxygen reduction reaction (ORR). Herein, we propose a novel and effective one-pot synthetic approach to prepare a NS-doped carbon catalyst by using the mixture of graphene oxide and multi-walled carbon nanotubes as a carbon support. Successful NS-doping of carbon and formation of the catalytically active sites were confirmed by X-ray photoelectron spectroscopy and with energy dispersion spectroscopy. The ORR activity of NS-codoped carbon was investigated by using a rotating disc electrode method. The NS-doped carbon shows superior ORR performance in alkaline media, and the electrocatalytic mechanism for the reduction of oxygen was well explained by density functional theory calculations of graphene sheets.ERA.Net RUS Plus Project HeDoCat; ERDF TK134; Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART

Coupling Fuzzy Bi-Level Chance Constraint Programming and Spatial Analysis for Urban Ecological Management

In this study, a fuzzy bi-level chance constraint programming (FBCP) model is developed for urban ecological management in Xiamen, China. FBCP has advantages in balancing trade-offs between multiple decision makers and can address fuzzy and stochastic uncertainty in ecosystem management. It also can reflect the impact of different violation risk levels and emission reduction measures on system benefit, ecosystem service value, and land resource allocation. Then, the conversion of land use and its effects at small regional extent (CLUE-S) model is employed to provide the spatial allocation of future land resources under different scenarios. Results reveal that (i) carbon fixation and climate regulation are the major contributors to the ecosystem service value, with a proportion of [15.4, 15.6]% and [18.5, 18.8]%, respectively; (ii) the main environmental problem in Xiamen is the water pollution caused by the excessive discharge of commercial and residential land, with COD and NH3-N account for [68.81, 69.33]% and [67.65, 68.20]% of the total discharge of the city, respectively; (iii) the violation risk p level is the most impact factor, and the schemes with high system benefit would face greater default risk and lower ecological quality; (iv) FBCP model considers the trade-off between economic benefit and ecological quality, while the fuzzy chance constraint programming (FCP) model achieves a high system benefit at the expense of the environment. These findings help decision makers to understand the impact of parameter uncertainty and pollutant discharge policies on system benefit, and adjust land-use patterns to weigh ecological environment protection with urban economic development

Flexibly tunable surface plasmon resonance by strong mode coupling using a random metal nanohemisphere on mirror

We propose a unique random metal nanohemisphere on mirror (NHoM) structure to tune the surface plasmon (SP) resonance in a flexible manner. The SP resonance peak was split into two peaks owing to the strong coupling between the SP mode in the metal nanohemisphere and the mirror image mode generated in the metal substrate. This phenomenon is based on the fact that the strong coupling and the induced electromagnetic effects are similar to those pertaining to the Rabi splitting, Fano resonance, and electromagnetically induced transparency, thus providing quantum effect analogies. These phenomena have recently attracted increased attention and have been studied with nanocavities fabricated with top-down nanotechnologies. Compared with previous reports, NHoM structures can be fabricated in a much easier manner and are tunable in rather wider wavelength regions without nanofabrication technologies. The SP resonance peaks were enhanced, sharpened dramatically, and tuned flexibly, based on the optimization of the thickness of the spacer layer between the metal hemisphere and metal substrate. Experimental results were reproduced and were explained based on finite difference time domain (FDTD) simulations. These phenomena have never been observed previously on similar nanosphere on mirror (NSoM) because nanohemispherical structures were required. The NHoM nanocavity structure has a quality factor >200 that is surprisingly high for the localized SP mode of nanoparticles. Flexible tuning of the SP resonance with the use of NHoM is envisaged to lead to the development of new applications and technologies in the field of plasmonics and nanophotonics

The impact of bridge pier on ice jam evolution – an experimental study

The ice jam in a river can significantly change the flow field in winter and early spring. The presence of bridge piers further complicates the hydraulic process by interacting between the ice jam and bridge piers. Using the data collected from experiments in a laboratory flume, the evolution of an ice jam around bridge piers having three different diameters has been investigated in this study. Compared to results without-pier, it was found that the formation of an ice jam in the downstream of bridge pier is faster than that in the upstream. The thickness distribution of the ice jam shows clearly different characteristics in front and behind of bridge piers at different stages of the ice jam