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Li, Qi

Publications and source records attributed to Li, Qi.

At least 37 records · Page 2

Deep Learning for Subgrid‐Scale Turbulence Modeling in Large‐Eddy Simulations of the Convective Atmospheric Boundary Layer

Abstract In large‐eddy simulations, subgrid‐scale (SGS) processes are parameterized as a function of filtered grid‐scale variables. First‐order, algebraic SGS models are based on the eddy‐viscosity assumption, which does not always hold for turbulence. Here we apply supervised deep neural networks (DNNs) to learn SGS stresses from a set of neighboring coarse‐grained velocity from direct numerical simulations of the convective boundary layer at friction Reynolds numbers Re τ up to 1243 without invoking the eddy‐viscosity assumption. The DNN model was found to produce higher correlation between SGS stresses compared to the Smagorinsky model and the Smagorinsky‐Bardina mixed model in the surface and mixed layers and can be applied to different grid resolutions and various stability conditions ranging from near neutral to very unstable. The DNN model can capture key statistics of turbulence in a posteriori (online) tests when applied to large‐eddy simulations of the atmospheric boundary layer.

54 ENVIRONMENTAL SCIENCES↗

Method of making a photovoltaic device on a substrate at high speed with perovskite solution

A continuous inline method for production of photovoltaic devices at high speed includes: providing a substrate; depositing a first carrier transport solution layer with a first carrier transport deposition device to form a first carrier transport layer on the substrate; depositing a Perovskite solution comprising solvent and perovskite precursor materials with a Perovskite solution deposition device on the first carrier transport layer; drying the deposited Perovskite solution to form a Perovskite absorber layer; and depositing a second carrier transport solution with a second carrier transport deposition device to form a second carrier transport layer on the Perovskite absorber layer, wherein the deposited Perovskite solution is dried at least partially with a fast drying device which causes a conversion reaction and the Perovskite solution to change in optical density by at least a factor of 2 in less than 0.5 seconds after the fast drying device first acts on the Perovskite solution.

Christensen, Scott Kenneth↗

Data-driven cyber-attack detection for photovoltaic systems: A transfer learning approach

With increasing exposure to software-based sensing and control, power systems are facing higher risks of cyber/physical attacks. Here, to ensure system stability and minimize the potential economic losses, it is imperative to monitor the operating states and detect those attacks at the early stage. In this paper, a transfer learning method is proposed to detect cyber-attacks in photovoltaic (PV) systems with much less training data. First of all, two PV systems with a different number of PV inverters and power ratings are analyzed and their attack models are studied. Next, an attack detection Convolutional Neural Network (CNN) model was trained with rich amount of data from PV #1. Then, transfer learning was proposed to transfer the well-trained features from PV #1 to PV #2. Lastly, the attack detection model on PV #2 was trained based on the transferred CNN model. The experiment results show that the proposed transfer learning method achieves better accuracy and a faster convergence rate with a much less training dataset than conventional deep learning.

14 SOLAR ENERGY↗

Ingeniously enhanced ferromagnetism in chemically-reduced 2D Ti 3 C 2 T X MXene

Chemical reduction is a facile and cost-effective technique for the modulation of the physical and chemical properties of nanomaterials. In this work, we demonstrate an enhancement of the magnetic behavior of Ti 3 C 2 T x MXene after its chemical reduction via l-ascorbic acid treatment. Small ferromagnetic loops have been observed below 50 K for Ti 3 C 2 T x prepared by hydrofluoric acid (HF) etching of Al layers from Ti 3 AlC 2 . Such a ferromagnetic ordering of spins was significantly enhanced via a chemical reduction of Ti 3 C 2 T x with l-ascorbic acid. Ferromagnetic hysteresis loops were observed for reduced Ti 3 C 2 T x (r-Ti 3 C 2 T x ) up to 150 K indicating a significant upshift of the paramagnetic to the ferromagnetic transition temperature, pushing towards room temperature. The enhancement of ferromagnetism and upshift of the ferromagnetic transition temperature could be attributed to the localized unpaired electron in Ti-3d orbital of the r-Ti 3 C 2 T x crystal and increase in the number of unsaturated Ti atoms upon l-ascorbic acid treatment. Chemical reduction via l-ascorbic acid treatment shows a promising pathway towards the modulation and enhancement of magnetism in various MXene materials for the development of 2D metallic soft ferromagnets and spintronic devices.

36 MATERIALS SCIENCE↗

Identification of new marker genes from plant single‐cell RNA‐seq data using interpretable machine learning methods

Summary An essential step in the analysis of single‐cell RNA sequencing data is to classify cells into specific cell types using marker genes. In this study, we have developed a machine learning pipeline called single‐cell predictive marker (SPmarker) to identify novel cell‐type marker genes in the Arabidopsis root. Unlike traditional approaches, our method uses interpretable machine learning models to select marker genes. We have demonstrated that our method can: assign cell types based on cells that were labelled using published methods; project cell types identified by trajectory analysis from one data set to other data sets; and assign cell types based on internal GFP markers. Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, the new marker genes have more orthologous genes identifiable in the corresponding rice single‐cell clusters. The new root hair marker genes also include 172 genes with orthologs expressed in root hair cells in five non‐ Arabidopsis species, which expands the number of marker genes for this cell type by 35–154%. Our results represent a new approach to identifying cell‐type marker genes from scRNA‐seq data and pave the way for cross‐species mapping of scRNA‐seq data in plants.

54 ENVIRONMENTAL SCIENCES↗

Partitioning behavior and mechanisms of rare earth elements during precipitation in acid mine drainage

Rare earth elements (REEs) are frequently found concentrated in acid mine drainage (AMD). The recovery of REEs from AMD has been successfully achieved using selective chemical precipitation. However, a portion of the REEs is often lost to the precipitates of the dominant metal contaminant ions. To better understand the REE partitioning behavior and mechanisms during the precipitation process, a systematic study was performed on both natural and synthetic AMD solutions. Precipitation test results show that REE removal was noticeably elevated at pH 4.0 after adding H 2 O 2 to convert ferrous to ferric ions, causing nearly complete precipitation of iron. Solution equilibrium calculations suggested that the REE removal increase was realized through adsorption onto the surfaces of the ferric precipitates. The presence of aluminum species in the solutions reduced the adsorption of REEs on the ferric precipitates. Based on electro-kinetic test results, it was concluded that aluminum species neutralize the negative surface charge of the ferric precipitates and compete with REEs for the adsorption active sites. The presence of ferrous ions in the solutions reduced REE adsorption on the aluminum precipitates at lower pH values (e.g., 5.0) due to competitive adsorption. However, at higher pH values (e.g., 6.0), REE removal to the precipitate product increased due to the precipitation of ferrous ions. Additionally, to the electro-kinetic tests and solution equilibrium calculations, mineralogy characterization, specific surface area measurement, particle size analysis, and morphology analysis were also conducted to investigate and identify the partitioning mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Process development for recovering critical elements from acid mine drainage

The rapid development of advanced technologies has increased the demand for critical elements, such as Mn, Co, and Ni. For this work, a systematic study was conducted to develop a process for producing high-purity Mn, Co, and Ni products from an acid mine drainage (AMD). As major contaminants, Fe and Al in the solution were sequentially precipitated and eliminated by elevating the pH to around 4.00 and 6.50, respectively. After that, a pre-concentrated slurry containing 3,794 mg/L Mn, 59 mg/L Co, 127 mg/L Ni, and 300 mg/L Zn was obtained by collecting the precipitates formed in the pH range of 6.50 to 10.00. The pH of the pre-concentrated slurry was decreased to around 5.00 by adding HCl to re-dissolve Co, Ni, and Zn for further purification. At this pH, greater than 50% of Mn remained undissolved, and filtration of the undissolved material resulted in a product with around 30 wt.% Mn. Sodium sulfide was added into the re-dissolved solution to selectively precipitate Co, Ni, and Zn while remaining Mn in the solution. Almost 100% of Co, Ni, and Zn but only around 15% of Mn were precipitated using a sulfur to metal molar ratio of 1 at pH 4.00. The sulfide precipitate was calcined at 200 °C for 2 h and then completely dissolved in 1.2 M HCl. The critical elements existing in the dissolved solution were efficiently separated using a two-stage solvent extraction process. Ultimately, Co and Ni products with almost 94% and 100% purity were obtained by sulfide and alkaline precipitation, respectively.

42 ENGINEERING↗

Adaptive Hierarchical Cyber Attack Detection and Localization in Active Distribution Systems

Development of a cyber security strategy for the active distribution systems is challenging due to the inclusion of distributed renewable energy generations. Here this paper proposes an adaptive hierarchical cyber attack detection and localization framework for distributed active distribution systems via analyzing electrical waveforms. Cyber attack detection is based on a sequential deep learning model, via which even minor cyber attacks can be identified. The two-stage cyber attack localization algorithm first estimates the cyber attack sub-region, and then localize the specified cyber attack within the estimated subregion. We propose a modified spectral clustering-based network partitioning method for the hierarchical cyber attack ‘coarse’ localization. Next, to further narrow down the cyber attack location, a normalized impact score based on waveform statistical metrics is proposed to obtain a ‘fine’ cyber attack location by characterizing different waveform properties. Finally, compared with classical and state-of-art methods, a comprehensive quantitative evaluation with two case studies shows promising estimation results of the proposed framework.

42 ENGINEERING↗

CONGO²: Scalable Online Anomaly Detection and Localization in Power Electronics Networks

Rapid and accurate detection and localization of electronic disturbances simultaneously are important for preventing its potential damages and determining potential remedies. Existing anomaly detection methods are severely limited by the low accuracy, the expensive computational cost and the need for highly trained personnel. There is an urgent need for a scalable online algorithm for in-field analysis of large-scale power electronics networks. Here in this paper, we propose a fast and accurate algorithm for anomaly detection and localization of power electronics networks: stratified colored-node graph (CONGO2). This algorithm hierarchically models the change of correlated waveforms and then correlated sensors using the colored-node graph. By aggregating the change of each sensor with its neighbors’ inputs, we can spontaneously identify and localize the anomaly that cannot be detected by data collected from a single sensor. As our proposed method only focuses on the changes within a short time frame, it is highly computational efficient and only needs small data storage. Thus, our method is ideal for online and reliable anomaly detection and localization of large-scale power electronic networks. Compared to existing anomaly detection methods, our method is entirely data-driven without training data, highly accurate and reliable for wide-spectrum anomalies detection, and more importantly, capable of both detection and localization. Thus, it is ideal for infield deployment for large-scale power electronic networks. As illustrated by a distributed energy resources (DERs) power grid with 37-node, our method can effectively detect and localize various cyber and physical attacks.

42 ENGINEERING↗

Room-temperature large magnetoelectricity in a transition metal doped ferroelectric perovskite

There is increasing interest in novel magnetoelectric (ME) materials that exhibit robust ME coupling at room-temperature (RT) for advanced memory, energy, spintronics, and other multifunctional device applications, by making use of the ability to control polarization with a magnetic field and/or magnetization via an electric field. Obtaining ME materials with strong ME coupling, understanding the origin, and manipulating its processing along with composition to realize large ME coefficients at RT constitute an important step in multiferroic research. To address this, we have investigated the multiferroic and ME properties of Ni-doped Pb(Zr 0.20 Ti 0.80 )O 3 (PZT). We find that the ferroelectric (T C ~ 700 K) and weak ferromagnetic (~ 602 K) phase transitions of Ni-doped PZT are well above RT, leading to a strong ME coupling coefficient (α E,31 ) of 11.7 mVcm -1 Oe -1 (H ac = 1 Oe and f = 1 kHz). While X-ray diffraction suggests a single-phase material, high resolution transmission electron microscopy reveals regions with and without Ni present; thus magnetoelectric coupling between two phases is possible. First-principle calculations suggest the (Ni Pb ) × defect is likely to be responsible for the experimental observed magnetism and ME coupling in Ni-doped PZT. Furthermore, we demonstrate that Ni-doped PZT exhibits low loss tangent, low leakage current, large saturation polarization and weak ferromagnetism. Ultimately, our work demonstrates that Ni-doped PZT is a cost-effective RT multiferroic with strong ME coupling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Source of Bright Near-Infrared Luminescence in Gold Nanoclusters

Gold nanoclusters with near-infrared (NIR) photoluminescence (PL) have great potential as sensing and imaging materials in biomedical and bioimaging applications. In this work, Au 21 (S-Adm) 15 and Au 38 S 2 (S-Adm) 20 are used to unravel the underlying mechanisms for the improved quantum yields (QY), large Stokes shifts and long PL lifetimes in gold nanoclusters. Both nanoclusters show decent PL QY. In particular, the Au 38 S 2 (S-Adm) 20 nanocluster shows a bright NIR PL at 900 nm with QY up to 15% in normal solvents (such as toluene) at ambient conditions. The relatively lower QY for Au 21 (S-Adm) 15 (4%) compared to Au 38 S 2 (S-Adm) 20 is attributed to the lowest-lying excited state being symmetry-disallowed, as evidenced by the pressure-dependent anti-spectral shift of the absorption spectra compared to PL. Yet, Au 21 (S-Adm) 15 maintains some emissive properties due to a nearby symmetry-allowed excited state. Furthermore, our results show that suppression of non-radiative decay due to the surface “lock rings” which encircle the Au kernel and the surface “lock atoms” which bridge the fundamental Au-kernel units (e.g., tetrahedra, icosahedra, etc.) is the key to obtain high QYs in gold nanoclusters. Here, the complicated excited-state processes and the small absorption coefficient of the band-edge transition lead to the large Stokes shifts and the long PL lifetimes that are widely observed in gold nanoclusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamics of quantum Hall interfaces

A quantum Hall (QH) interface is different from an ordinary QH edge, as the latter has its location determined by the confining potential, while the former can be unpinned and behave like a free string. In this paper, we demonstrate this difference by studying three different interfaces formed by (i) the Laughlin state and the vacuum, (ii) the Pfaffian state and the vacuum, and (iii) the Pfaffian and the anti-Pfaffian states. We find that stringlike interfaces propagating freely in the QH system lead to very different dynamical properties from edges. This qualitative difference gives rise to fascinating physics and suggests a different direction for future research on QH physics. We also discuss briefly possible analogies between QH interfaces and concepts in string theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Method of making a perovskite layer at high speed

A method of making a perovskite layer includes providing a flexible substrate; providing a perovskite solution comprising an initial amount of solvent and perovskite precursor materials and a total solids concentration between 30 percent and 70 percent by weight of its saturation concentration; depositing the perovskite solution on the flexible substrate; removing a first portion of the solvent from the deposited perovskite solution and increasing the total solids concentration of the perovskite solution to at least 75 percent of its saturation concentration with a first drying step; and removing a second portion of the solvent from the deposited perovskite solution with a second drying step having a higher rate of solvent evaporation that causes saturation and a conversion reaction in the deposited perovskite solution resulting in perovskite crystal formation or formation of a perovskite intermediate phase, wherein the first drying step dwell time is at least 5 times longer than the second drying step dwell time.

Christensen, Scott Kenneth↗

Connection Between Mass Flux Transport and Eddy Diffusivity in Convective Atmospheric Boundary Layers

Turbulence parameterizations for convective boundary layer in coarse-scale atmospheric models usually consider a combination of the eddy-diffusive transport and a non-local transport, typically in the form of a mass flux term, such as the widely adopted eddy-diffusivity mass-flux (EDMF) approach. These two types of turbulent transport are generally considered to be independent of each other. Using results from large-eddy simulations, here, we show that a Taylor series expansion of the updraft and downdraft mass-flux transport can be used to approximate the eddy-diffusivity transport in the atmospheric surface layer and the lower part of the mixed layer, connecting both eddy-diffusivity and mass-flux transport theories in convective conditions, which also quantifies departure from the Monin-Obukhov similarity (MOS) in the surface layer. This study provides a theoretical support for a unified EDMF parameterization applied to both the surface layer and mixed layer and highlights important correction required for surface models relying on MOS

54 ENVIRONMENTAL SCIENCES↗

Capping layer influence and isotropic in-plane upper critical field of the superconductivity at the FeSe / SrTiO 3 interface

Understanding the superconductivity at the interface of FeSe/SrTiO 3 is a problem of great contemporary interest due to the significant increase in critical temperature (T c ) compared to that of bulk FeSe, as well as the possibility of an unconventional pairing mechanism and topological superconductivity. We report a study of the influence of a capping layer on superconductivity in thin films of FeSe grown on SrTiO 3 using molecular beam epitaxy. We used in vacuo four-probe electrical resistance measurements and ex situ magnetotransport measurements to examine the effect of three capping layers that provide distinct charge transfer into FeSe: insulating FeTe, nonmetallic Te, and metallic Zr. Our results show that FeTe provides an optimal cap that barely influences the inherent T c found in pristine FeSe/SrTiO 3 , while the transfer of holes from a nonmetallic Te cap completely suppresses superconductivity and leads to insulating behavior. Finally, we used ex situ magnetoresistance measurements in FeTe capped FeSe films to extract the angular dependence of the in-plane upper critical magnetic field. Our observations reveal an almost isotropic in-plane upper critical field, providing insight into the symmetry and pairing mechanism of high-temperature superconductivity in FeSe.

36 MATERIALS SCIENCE↗

Logarithmic profile of temperature in sheared and unstably stratified atmospheric boundary layers

The impact of buoyancy on the mean velocity, temperature, and scalar concentration profiles in the lower atmosphere is typically investigated within the framework of Monin-Obukhov similarity theory (MOST). MOST is the theoretical foundation for parametrizing surface-atmosphere exchanges in nearly all weather, climate, and hydrological models.According to MOST, the classic logarithmic profiles of mean velocity and temperature break down as the buoyancy effects become important. However, recent studies on turbulent Rayleigh-Bénard convection and natural convection along vertical walls suggest that the mean temperature in the near-surface region still follows a logarithmic profile.Motivated by these new results, we study the mean potential temperature profile in sheared and unstably stratified atmospheric boundary layers using direct numerical simulations and field observations. We find that the mean potential temperature profile remains logarithmic across a wide range of stability parameters, which characterizes the relative importance of buoyancy versus shear effects. Compared to MOST, our results suggest that the buoyancy force does not modify the logarithmic nature of the mean potential temperature profile, but instead modulates its slope, which is no longer universal and differs from 1/κ,whereκisthe von Kármán constant. Furthermore, this study provides another perspective on scalar turbulence in the atmospheric boundary layer

58 GEOSCIENCES↗

Bright NIR‐II Photoluminescence in Rod‐Shaped Icosahedral Gold Nanoclusters

Abstract Fluorophores with high quantum yields, extended maximum emission wavelengths, and long photoluminescence (PL) lifetimes are still lacking for sensing and imaging applications in the second near‐infrared window (NIR‐II). In this work, a series of rod‐shaped icosahedral nanoclusters with bright NIR‐II PL, quantum yields up to ≈ 8%, and a peak emission wavelength of 1520 nm are reported. It is found that the bright NIR‐II emission arises from a previously ignored state with near‐zero oscillator strength in the ground‐state geometry and the central Au atom in the nanoclusters suppresses the non‐radiative transitions and enhances the overall PL efficiency. In addition, a framework is developed to analyze and relate the underlying transitions for the absorptions and the NIR‐II emissions in the Au nanoclusters based on the experimentally defined absorption coefficient. Overall, this work not only shows good performance of the rod‐shaped icosahedral series of Au nanoclusters as NIR‐II fluorophores, but also unravels the fundamental electronic transitions and atomic‐level structure‐property relations for the enhancement of the NIR‐II PL in gold nanoclusters. The framework developed here also provides a simple method to analyze the underlying electronic transitions in metal nanoclusters.

Li, Qi↗