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Gao, Wei

Publications and source records attributed to Gao, Wei.

Overview of recent experimental results on the EAST Tokamak

Since the last IAEA-FEC in 2021, significant progress on the development of long pulse steady state scenario and its related key physics and technologies have been achieved, including the reproducible 403 s long-pulse steady-state H-mode plasma with pure radio frequency (RF) power heating. A thousand-second time scale (~1056 s) fully non-inductive plasma with high injected energy up to 1.73 GJ has also been achieved. The EAST operational regime of high β P has been significantly extended (H 98y2 > 1.3, β P ~ 4.0, β N ~ 2.4 and n e /n GW ~ 1.0) using RF and neutral beam injection (NBI). The full edge localized mode suppression using the n = 4 resonant magnetic perturbations has been achieved in ITER-like standard type-I ELMy H-mode plasmas with q 95 ≈ 3.1 on EAST, extrapolating favorably to the ITER baseline scenario. The sustained large ELM control and stable partial detachment have been achieved with Ne seeding. The underlying physics of plasma-beta effect for error field penetration, where toroidal effect dominates, is disclosed by comparing the results in cylindrical theory and MARS-Q simulation in EAST. Breakdown and plasma initiation at low toroidal electric fields (<0.3 V m -1 ) with EC pre-ionization is developed. A beneficial role on the lower hybrid wave injection to control the tungsten concentration in the NBI discharge is observed for the first time in EAST suggesting a potential way toward steady-state H-mode NBI operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Impact of ultraviolet-B radiation on early-season morpho-physiological traits of indica and japonica rice genotypes

Ultraviolet (UV)-B radiation is considered one of the major detrimental rays coming from the Sun. UV-B radiation has a harmful impact on plant growth and development. The effect of UV-B radiation was studied on 64 rice (Oryza sativa L.) genotypes during the vegetative season. An equal number of genotypes from the japonica (50%) and indica (50%) subspecies were phenotyped using the Soil-Plant-Atmosphere-Research (SPAR) units. The 10 kJ UV-B was imposed 12 days after planting (DAP) and continued for three weeks (21 d). Based on the combined ultraviolet-B radiation response index (CUVBRI) for each genotype, the 64 rice genotypes were classified into sensitive, moderately sensitive, moderately tolerant, and tolerant. Various shoot traits, such as plant height, tiller, and leaf numbers, were measured. We also studied critical root phenological traits like root volume, diameter, tips, and forks. Out of all the studied shoot traits, leaf area showed maximum reduction for both indica (54%) and japonica (48%). Among the root traits, root length decreased by negligible (1%) for indica as compared to japonica (5%), while root crossing and forks showed a maximum decline for japonica (37 and 42%), respectively. This study is timely, meaningful, and required because it will help breeders select a tolerant or sensitive rice line for better yield and production under abiotic stresses.

59 BASIC BIOLOGICAL SCIENCES↗

DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Meteorology & Atmospheric Sciences↗

Fast Frequency Response using Reinforcement Learning-Controlled Wind Turbines

To fulfill the auxiliary grid services such as load regulation, spin and non-spin reserve, and frequency support during emergencies, power system operators often require certain wind farms to operate in de-loaded modes. By leveraging the fast response capability of wind farms, the reserved power in deloaded modes can significantly enhance the stability and reliability of power grids. This paper presents a novel methodology that incorporates wind turbines into reinforcement learning-based solutions for frequency response. The proposed approach employs the state-of-the-art reinforcement learning algorithm, surrogategradient- based evolution strategy (GSES), for continuous control of the wind farm output. Our methodology is tested on a modified IEEE-39 bus system, and simulation outcomes demonstrate that the proposed approach can reliably support the frequency of the power system and prevent unnecessary load shedding.

Gao, Wei↗

Correlation of Broad Absorption Band with Small Singlet‐Triplet Energy Gap in Organic Photovoltaics

Abstract Organic photovoltaics (OPV) are one of the most effective ways to harvest renewable solar energy, with the power conversion efficiency (PCE) of the devices soaring above 19 % when processed with halogenated solvents. The superior photocurrent of OPV over other emerging photovoltaics offers more opportunities to further improve the efficiency. Tailoring the absorption band of photoactive materials is an effective way to further enhance OPV photocurrent. However, the field has mostly been focusing on improving the near‐infrared region photo‐response, with the absorption shoulders in short‐wavelength region (SWR) usually being neglected. Herein, by developing a series of non‐fullerene acceptors (NFAs) with varied side‐group conjugations, we observe an enhanced SWR absorption band with increased side‐group conjugation length. The underpinning factors of how molecular structures and geometries improve SWR absorption are clearly elucidated through theoretical modelling and crystallography. Moreover, a clear relationship between the enhanced SWR absorption and reduced singlet‐triplet energy gap is established, both of which are favorable for the OPV performance and can be tailored by rational structure design of NFAs. Finally, the rationally designed NFA, BO‐TTBr, affords a decent PCE of 18.5 % when processed with a non‐halogenated green solvent.

Chemistry↗