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Hu, Wei

Publications and source records attributed to Hu, Wei.

13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ferrorotational domain walls revealed by electric quadrupole second harmonic generation microscopy

Domain walls are ubiquitous in materials that undergo phase transitions driven by spontaneous symmetry breaking. Domain walls in ferroics and multiferroics have received tremendous attention recently due to their emergent properties distinct from their domain counterparts—for example, their high mobility and controllability, as well as their potential applications in nanoelectronics. However, it is extremely challenging to detect, visualize, and study the ferrorotational (FR) domain walls because the FR order, in contrast to ferromagnetism and ferroelectricity, is invariant under both the spatial-inversion and the time-reversal operations and, thus, hardly couple with conventional experimental probes. Here, a FR candidate NiTi⁢O 3 is investigated by ultrasensitive electric quadrupole (EQ) second-harmonic generation rotational anisotropy (SHG RA) to probe the point symmetries of the two degenerate FR domain states, showing their relation by the vertical mirror operations that are broken below the FR critical temperature. We then visualize the real-space FR domains by scanning EQ SHG microscopy, and further, resolve the FR domain walls by revealing a suppressed SHG intensity at the domain walls. By taking local EQ SHG RA measurements, we show the restoration of the mirror symmetry at FR domain walls and prove their unconventional nonpolar nature. In conclusion, our findings not only provide a comprehensive insight into FR domain walls, but also demonstrate a unique and powerful tool for future studies on domain walls of unconventional ferroics both of which pave the way towards future manipulations and applications of FR domain walls.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Genome‐wide association studies reveal genetic basis of ionomic variation in cassava

SUMMARY As one of the most important food crops, cassava ( Manihot esculenta ) is the main dietary source of micronutrients for about 1 billion people. However, the ionomic variation in cassava and the underlying genetic mechanisms remain unclear so far. Herein, genome‐wide association studies were performed to reveal the specific single nucleotide polymorphisms (SNPs) that affect the ionomic variation in cassava. We identified 164 SNPs with P‐ values lower than the threshold located in 88 loci associated with divergent ionomic variations. Among them, 13 SNPs are related to both calcium (Ca) and magnesium (Mg), and many loci for different ionomic traits seem to be clustered on specific chromosome regions. Moreover, we identified the peak SNPs in the promoter regions of Sc10g003170 (encoding methionyl‐tRNA synthetase [MetRS]) and Sc18g015190 (encoding the transcriptional regulatory protein AlgP) for nitrogen (N) and phosphorus (P) accumulation, respectively. Notably, these two SNPs (chr10_32807962 and chr18_31343738) were directly correlated with the transcript levels of Sc10g003170 ( MetRS ) and Sc18g015190 ( AlgP ), which positively modulated N accumulation and P concentration in cassava, respectively. Taken together, this study provides important insight into the genetic basis of cassava natural ionomic variation, which will promote genetic breeding to improve nutrient use and accumulation of elements in cassava.

Yin, Hongyan↗
DOE OSTI2022

What you get is not always what you see—pitfalls in solar array assessment using overhead imagery

Effective integration planning for small, distributed solar photovoltaic (PV) arrays into electric power grids requires access to high quality data: the location and power capacity of individual solar PV arrays. Unfortunately, national databases of small-scale solar PV do not exist; those that do are limited in their spatial resolution, typically aggregated up to state or national levels. While several promising approaches for solar PV detection have been published, strategies for evaluating the performance of these models are often highly heterogeneous from study to study. The resulting comparison of these methods for practical applications for energy assessments becomes challenging and may imply that the reported performance evaluations overly optimistic. The heterogeneity comes in many forms, each of which we explore in this work: the degree of diversity of the locations and sensors (e.g. different satellites, aerial photography) from which the training and validation data originate, the validation of ground truth (manual annotation of imagery vs known solar PV locations), the level of spatial aggregation (e.g. array-level vs regional estimates), and inconsistencies in the training and validation datasets (e.g. different datasets are used for each study and those data are not always made accessible). For each, we discuss emerging practices from the literature to address them or suggest directions of future research. As part of our investigation, we evaluate solar PV identification performance in two large regions: the entire state of Connecticut and the city of San Diego, CA. In Connecticut, we also use 33,114 known parcel-level solar PV installations from Berkeley Lab’s Tracking the Sun dataset to evaluate parcel-level performance and evaluate capacity estimates using 169 municipalities. We also make our code (which we call SolarMapper), pre-trained models, training data, and predictions publicly available and provide a web portal for interactively inspecting each prediction that was made. Here our findings suggest that traditional performance evaluation of the automated identification of solar PV from satellite imagery may be optimistic due to common limitations in the validation process. The takeaways from this work are intended to inform and catalyze the large-scale practical application of automated solar PV assessment techniques by energy researchers and professionals.

14 SOLAR ENERGY↗
DOE OSTI2022

KSSOLV 2.0: An efficient MATLAB toolbox for solving the Kohn-Sham equations with plane-wave basis set

KSSOLV (Kohn-Sham Solver) is a MATLAB toolbox for performing Kohn-Sham density functional theory (DFT) calculations with a plane-wave basis set. KSSOLV 2.0 preserves the design features of the original KSSOLV software to allow users and developers to easily set up a problem and perform ground-state calculations as well as to prototype and test new algorithms. Furthermore, it includes new functionalities such as new iterative diagonalization algorithms, k-point sampling for electron band structures, geometry optimization and advanced algorithms for performing DFT calculations with local, semi-local, and hybrid exchange-correlation functionals. It can be used to study the electronic structures of both molecules and solids. So, we describe these new capabilities in this work through a few use cases. We also demonstrate the numerical accuracy and computational efficiency of KSSOLV on a variety of examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Recycled polyethylene and crumb rubber composites modified asphalt with improved aging resistance and thermal stability

Crumb rubbers (CR) and recycled Polyethylene (PE) are commonly used as modifiers to improve the asphalt properties. However, the addition of these modifiers individually may result in phase separation of PE and inadequate degradation of CR, which may not simultaneously satisfy the rheological and aging resistance of the binder blends. In this study, a type of CR/PE composites manufactured through melt extrusion procedures was adopted for the improvement of the modified binder blends. The modified binder blends after short-term (RTFO) and long-term (PAV) aging were collected for dynamic shear rheometer and bending beam rheometer tests. FTIR tests were also used to quantify the aging resistance, while differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were applied to evaluate the thermal behaviors of the binder blends. Optical microscopy tests were used to explore the modification mechanism and visualize the microstructures of original and PAV aged binder blends. Test results showed that CR/PE composites could significantly improve the aging resistance of the binder blends. The dispersed PE particles still interacted with each other and meanwhile worked with the diffused rubbery phase, which could form a similar TPEs network. The oxidation and high-temperature aging of such binder blends would strengthen the network that resisted the aging severity of the binder blends. Furthermore, it was also revealed that CR/PE modified asphalt could sustain more heat before a rapid degradation and the well-dispersed PE particles could interact with the diffused CR particles to form a network to resist aging.

02 PETROLEUM↗
DOE OSTI2021

CD63-mediated cloaking of VEGF in small extracellular vesicles contributes to anti-VEGF therapy resistance

Despite wide use of anti-vascular endothelial growth factor (VEGF) therapy for many solid 30 cancers, most of them become resistant to this therapy and develop into progressive disease. 31 Therefore, new biomarkers and strategies for blocking adaptive resistance of cancer to anti-VEGF therapy are needed. As described herein, we found that cancer-derived small extracellular vesicles (EVs) package increasing quantities of VEGF and other factors in response to anti-VEGF therapy. Notably, small EV-VEGF (eVEGF) is not recognized by bevacizumab and can be transferred to endothelial cells and trigger intracrine signaling and promote angiogenesis. Also, serum eVEGF was present at higher levels in ovarian cancer mouse models with adaptive resistance to bevacizumab than in models sensitive to it. Ovarian cancer cell-derived eVEGF increased tumor growth despite treatment with bevacizumab. Notably, the eVEGF level was elevated in patient serum after bevacizumab-containing therapy. Proteomic data of small EVs from mouse models suggested that several novel biomarkers are promising for drug response prediction. Collectively, these data demonstrated a new mechanism whereby eVEGF evades recognition by therapeutic antibodies and promotes tumor angiogenesis and progression. These findings have clinical implications for biomarkers and new therapeutic strategies for ovarian cancer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Kohn-Sham Solver (KSSOLV) v2.0

KSSOLV is a MATLAB toolbox for solving Kohn-Sham density functional theory based electronic structure eigenvalue problems. It uses an object oriented features of MATLAB to represent atom, molecules, wavefunctions and Hamiltonians and their operations. It is designed to make it easier for users to prototype and test new algorithms for solving the Kohn-Sham problem. KSSOLV2.0 contains significant improvement over the original KSSOLV described in a paper published in ACM Transaction on Mathematical Software (attached). In addition to performing ground state calculation for small molecules, it can also perform geometry optimization for both molecules and solids. It uses standard pseudopotentials and implements local density approximation, generalized gradient approximation and hybrid functionals. Future releases will also include time-dependent DFT and post DFT calculations such as the GW quasi-particle energy calculation and Bethe-Salpeter equation solver for optical absorption.

Yang, Chao↗