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At least 541 records · Page 30

Incorporating energy storage and user experience in isolated microgrid dispatch using a multi-objective model

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment, and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides microturbine units, energy storage is employed to provide spinning reserve services for microgirds; and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimisation and decision analysis is put forward to address this model. First, a powerful heuristic optimisation algorithm, called the -dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. Thereby, the best compromise solutions are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.

Li, Yang↗

Structure of the 2, 4′-dihydroxyacetophenone dioxygenase from Alcaligenes sp. 4HAP

The first X-ray structure of a 2, 4′-dihydroxyacetophenone dioxygenase from Alcaligenes sp. 4HAP at a resolution of 2.2 Å is reported. This structure establishes that the enzyme adopts the cupin-fold, forming compact dimers with a pronounced hydrophobic interface between the monomers. Each monomer possesses a catalytic ferrous iron that is coordinated by three histidines (76, 78 and 114) and an additional ligand which has been putatively assigned as a carbonate, although formate and acetate are possibilities. The enzyme 2, 4′-dihydroxyacetophenone dioxygenase (DAD) catalyses the conversion of 2, 4′-dihydroxyacetophenone to 4-hydroxybenzoic acid and formic acid with the incorporation of molecular oxygen. Whilst the vast majority of dioxygenases cleave within the aromatic ring of the substrate, DAD is very unusual in that it is involved in C—C bond cleavage in a substituent of the aromatic ring. There is evidence that the enzyme is a homotetramer of 20.3 kDa subunits, each containing nonhaem iron, and its sequence suggests that it belongs to the cupin family of dioxygenases. In this paper, the first X-ray structure of a DAD enzyme from the Gram-negative bacterium Alcaligenes sp. 4HAP is reported, at a resolution of 2.2 Å. The structure establishes that the enzyme adopts a cupin fold, forming dimers with a pronounced hydrophobic interface between the monomers. The catalytic iron is coordinated by three histidine residues (76, 78 and 114) within a buried active-site cavity. The iron also appears to be tightly coordinated by an additional ligand which was putatively assigned as a carbonate dianion since this fits the electron density optimally, although it might also be the product formate. The modelled carbonate is located in a position which is highly likely to be occupied by the α-hydroxyketone group of the bound substrate during catalysis. Modelling of a substrate molecule in this position indicates that it will interact with many conserved amino acids in the predominantly hydrophobic active-site pocket where it undergoes peroxide radical-mediated heterolysis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Python STXM Control (pystxmcontrol) v0.1

The software is a complete solution for controlling scanning microscopes. It provides a low level interface to device hardware via drivers, communication and coordination layers for managing scan execution and data acquisition, a graphical interface and scripting interface for user interaction. With optimized hardware drivers and low software overhead this software is 10 times faster than the legacy software it is replacing.

Shapiro, David [Lawrence Berkeley National Laborat↗

CRADA: Data Acquisition and Tomographic Software Development

Dr. Raymond R. Raylman, Professor and Vice Chair for Research, Radiology Department at WVU was the Principal Investigator for the project. The Jefferson Lab partner on this project was the Radiation Detector and Imaging Group in the Physics Division, led by Dr. Drew Weisenberger who was the coordinator of the project execution and the chief contact with WVU. The responsibility of Jefferson Lab was to facilitate optimization of data acquisition software, conversion of JLab Fortran iterative positron emission mammography computer code to C++ and to act as a computer code repository. During the two year project interactions and exchange of information was directed by Dr. Raylman and Dr. Wesienberger. WVU provided the expertise that allowed JLab to continue development of the current JLab data acquisition software referred to as JDAQ. JDAQ is a highly flexible Java language based data acquisition tool that helps to minimize software induced dead-time while maintaining the highest possible data rates from a JLab built FPGA based analog-to-digital convertor (ADC). JDAQ interfaces directly with the FPGA based multi-channel ADCs. Using JDAQ it is possible process data from a number of different detector types such as the PET systems at WVU. Because of the inherent flexibility of our processing software, we are also able adjust detector readout parameters during operation to provide the best possible data presentation and calibration parameters. To accommodate the high rate nature of PET detector systems JDAQ was designed to be scalable across an Ethernet network as well as for multi-cpu computer systems, and it also has the capability to synchronize many ADCs connected to multiple computers. During the project WVU will provided iterative reconstruction algorithm expertise and Fortran programming assistance to facilitate the conversion to C++ of a JLab developed Fortran positron emission mammography (PEM) reconstruction code. Also WVU provided acceptance testing of the new C++ based PEM reconstruction code. The PEM code is a maximization (MLEM) image reconstruction program that created images from the list-mode data acquired from the PET system.

97 MATHEMATICS AND COMPUTING↗

A Multistage Stochastic Transmission Expansion Algorithm for Wide-Area Planning under Uncertainty

The overall objective for this project was to develop and demonstrate a set of methods for solving the transmission investment problem for a large network considering many possible scenarios of future conditions and multiple decision points when investments can be made. Project sub-objectives achieved this goal through a succession of extending the methods to apply to problems with increasing complexity or additional features, including the number of decision points, whether generation and transmission are co-optimized, and whether AC or DC power flow is used. A transmission model was developed for the Western Electric Coordinating Council (WECC) region, the high-voltage transmission system that serves the western third of the continental U.S. Using a dataset provided by WECC and by researchers from John Hopkins University, we have validated and demonstrated the model and used it to compare the new method for solving multi-stage stochastic transmission planning to several state-of-the-art techniques. The project has resulted in several key outcomes and achievements: The covariance-based method for choosing a small set of hours to represent short-term variability has superior performance in terms of accuracy to existing methods, including K-means clustering and Importance Sampling; The combined partitioning method for long-term uncertainty with the nested clustering approach for choosing representative hours for each long-term group has superior accuracy for equivalent computational effort compared with existing methods; Using the partitioning/clustering method combined with Sample Average Approximation provides both statistical bounds on the quality of the solution and at the same time, a complete investment plan for all contingencies in the full uncertainty set; no existing methods can provide both at the same time; The method is demonstrated to work well for choosing both transmission and generation investments; A variant on the method allows for both scenario selection and simultaneous correction for the error from the DC power flow approximation to provide a tractable method for AC power flow-based transmission planning under uncertainty; The method applied to the WECC case study demonstrates the additional value to the system operator and the consumer of identifying flexible investment options in the near-term decisions. In particular, the case study exhibits significant option value in postponing some transmission additions that appear useful but in some long-term system states create new congestion problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗

Battery Energy Storage Scheduling for Optimal Load Variance Minimization

Generation portfolio can be significantly altered due to the deployment of distributed energy resources (DER) in distribution networks and the concept of microgrid. Generally,distribution networks can operate in a more resilient and economic fashion through proper coordination of DER. However, due to the partially uncontrollable and stochastic nature of some DER, the variance of net load of distribution systems increases, which raises the operational cost and complicates operation for transmission companies. This motivates peak shaving and valley filling using energy storage units deployed in distribution systems. This paper aims at theoretical formulation of optimal load variance minimization, where the infinity norm of net load is minimized. Then, the problem is reformulated equivalently as a linear program. A case study is performed with capacity limited battery energy storage model and the simplified power flow model of a radial distribution network. The influence of capacity limit and deployment location are studied.

Melin, Alexander↗

A simulation‐based integrated virtual testbed for dynamic optimization in smart manufacturing systems

Abstract In a manufacturing system, production control‐related decision‐making activities occur at different levels. At the process level, one of the main control activities is to tune the parameters of individual manufacturing equipment. At the system level, the main activity is to coordinate production resources and to route parts to appropriate workstations based on their processing requirement, priority indices, and control policy. At the factory level, the goal is to plan and schedule the processing of parts at different operations for the entire system in order to optimize certain objectives. Note that the results of such activities at different levels are closely coupled and affect the overall performance of the manufacturing system as a whole. Therefore, it is important to systematically integrate these control and optimization activities into one unified platform to ensure the goal of each individual activity is aligned with the overall performance of the system. In this paper, we develop a simulation‐based virtual testbed that implements dynamic optimization, automatic information exchange, and decision‐making from the process‐level, system‐level, and factory‐level of a manufacturing system into an integrated computation environment. This is demonstrated by connecting a Python‐based numerical computation program, discrete‐event simulation software (Simul8), and an optimization solver (CPLEX) via a third‐party master program. The application of this simulation‐based virtual testbed is illustrated by a case study in a machining shop.

Sun, Yuting↗

Generalized and efficient algorithm for computing multipole energies and gradients based on Cartesian tensors

Accurate representation of intermolecular forces has been the central task of classical atomic simulations, known as molecular mechanics. Recent advancements in molecular mechanics models have put forward the explicit representation of permanent and/or induced electric multipole (EMP) moments. The formulas developed so far to calculate EMP interactions tend to have complicated expressions, especially in Cartesian coordinates, which can only be applied to a specific kernel potential function. For example, one needs to develop a new formula each time a new kernel function is encountered. The complication of these formalisms arises from an intriguing and yet obscured mathematical relation between the kernel functions and the gradient operators. Here, I uncover this relation via rigorous derivation and find that the formula to calculate EMP interactions is basically invariant to the potential kernel functions as long as they are of the form f(r), i.e., any Green’s function that depends on inter-particle distance. I provide an algorithm for efficient evaluation of EMP interaction energies, forces, and torques for any kernel f(r) up to any arbitrary rank of EMP moments in Cartesian coordinates. The working equations of this algorithm are essentially the same for any kernel f(r). Recently, a few recursive algorithms were proposed to calculate EMP interactions. Depending on the kernel functions, the algorithm here is about 4–16 times faster than these algorithms in terms of the required number of floating point operations and is much more memory efficient. I show that it is even faster than a theoretically ideal recursion scheme, i.e., one that requires 1 floating point multiplication and 1 addition per recursion step. This algorithm has a compact vector-based expression that is optimal for computer programming. The Cartesian nature of this algorithm makes it fit easily into modern molecular simulation packages as compared with spherical coordinate-based algorithms. A software library based on this algorithm has been implemented in C++11 and has been released.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrated Metal and Metal-Nitrate Complexes in Water: Full Lanthanide(III) Series plus Miscellaneous Metal Ions

This is a dataset of hydrated metal complexes and metal–nitrate hydrated complexes intended for public use, reproducibility, and downstream structural analysis. A key feature is coverage across the full lanthanide(III) series (La–Lu), enabling systematic comparisons of coordination motifs and bonding trends across the entire lanthanide sequence. In addition to the lanthanides, the dataset also includes other metal ions such as UO2(VI), Fe(II), and Fe(III). The dataset provides optimized geometries for hydrated and nitrate-containing hydrated complexes, together with representative ab initio molecular dynamics (AIMD) trajectories saved in standard XYZ formats. The accompanying NWChem input decks enable reproduction of the reported calculations and provide a starting point for extending the simulations to related coordination environments. Computationally, DFT calculations employ the B3LYP functional with DFT-D3BJ dispersion corrections and a COSMO continuum solvent model (dielectric constant 78.4) to represent solvation beyond the explicitly treated first hydration shell. AIMD simulations are performed with the NWChem qmd module at 298 K, integrating nuclear motion with the velocity-Verlet algorithm and controlling temperature using a Nosé–Hoover thermostat. Trajectories are approximately 4.8 ps in length and are used primarily to assess short-time stability of candidate coordination motifs, including (for lanthanides) differences between 8- versus 9-water coordination and comparisons between nitrate-bound and nitrate-free hydrated complexes.

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗

Coordinated Model Predictive Control on Multi-Lane Roads

There are significant economic, environmental, energy, and other societal costs incurred by the road transportation sector. With the advent and penetration of connected and autonomous vehicles there are vast opportunities to optimize the control of individual vehicles for reducing energy consumption and increasing traffic flow. Model predictive control is a useful tool to achieve such goals, while accommodating ego-centric objectives typical of heterogeneous traffic and explicitly enforcing collision and other constraints. In this paper, we describe a multi-agent distributed maneuver planning and lane selection model predictive controller that includes an information sharing and coordination scheme. The energy saving potential of the proposed coordination scheme is then evaluated via large scale microscopic traffic simulations considering different penetration levels of connected and automated vehicles.

Goulet, Nathan↗

A first principles study of energetics and electronic structural responses of uranium-based coordination polymers to Np incorporation

Abstract Recently developed coordination polymers (CPs) and metal organic frameworks (MOFs) may find applications in areas such as catalysis, hydrogen storage, and heavy metal immobilization. Research on the potential application of actinide-based CPs (An-CP/MOFs) is not as advanced as transition metal-based MOFs. In order to modify their structures necessary for optimizing thermodynamic and electronic properties, here, we described how a specific topology of a particular actinide-based CP or MOF responds to the incorporation of other actinides considering their diverse coordination chemistry associated with the multiple valence states and charge-balancing mechanisms. In this study, we apply a recently developed DFT-based method to determine the relative stability of transuranium incorporated CPs in comparison to their uranium counterpart considering both solid and aqueous state sources and sinks to understand the mechanism and energetics of charge-balanced Np 5+ incorporation into three uranium-based CPs. The calculated Np 5+ +H + incorporation energies for these CPs range from 0.33 to 0.52 eV, depending on the organic linker, when using the solid oxide Np source Np 2 O 5 and U sink UO 3 . Incorporation energies of these CPs using aqueous sources and sinks increase to 2.85–3.14 eV. The thermodynamic and structural analysis in this study aides in determining, why certain MOF topologies and ligands are selective for some actinides and not for others. This means that once this method is extended across a variety of CPs with their respective linker molecules and different actinides, it can be used to identify certain CPs with certain organic ligands being specific for certain actinides. This information can be used to construct CPs for actinide separation. This is the first determination of the electronic structure (band structure, density of states) of these uranium- and transuranium-based CPs which may eventually lead to design CPs with certain optical or catalytic properties. While the reduction of the DFT-determined-bandgap goes from 3.1 eV to 2.4 eV when going from CP1 to CP3, showing the influence of the linker, Np 6+ incorporation reduces the bandgap for CP1 and CP3, while increasing it for CP2. The coupled substitution of U 6+ →Np 5+ +H + reduces the bandgap significantly, but only for CP3.

Chemistry↗

Secure State Estimation with Asynchronous Measurements for Coordinated Cyber Attack Detection in Active Distribution Systems

Coordinated cyber attacks tamper with measurement data to disrupt the situational awareness of active distribution systems. Various sensors report measurements asynchronously at different rates, which introduces challenges during state estimation. In addition, this forces cyber intruders to exert greater effort to compromise multiple communication channels and launch coordinated attacks. Therefore, multi-channel and asynchronous measurements could be harnessed to develop more secure cyber defense strategies. In this paper, a prediction-correction-based multi-rate observer is designed to exploit the value of asynchronous measurements for the detection of coordinated false data injection (FDI) attacks. First, a time-function-dependent prediction-correction strategy is proposed to adjust the sampling interval for each sensor’s measurement. Then, an observer is designed based on the trade-off between estimation error and the optimal period of the most recent sampling instant, with the convergence of estimation error with the maximum permitted sampling interval. Moreover, the conditions for exponential stability are developed using the Lyapunov–Krasovskii functional technique. Next, a coordinated FDI attack detection strategy is developed based on the dual nonlinear minimization problem. The proposed attack detection and secure state estimation strategies are tested on the IEEE 13-node system. Simulation results show that these schemes are effective in enhancing attack detection based on asynchronous measurements or compromised data.

asynchronous measurements↗

Correlating Macro and Atomic Structure with Elastic Properties and Ionic Transport of Glassy Li 2 S‐P 2 S 5 (LPS) Solid Electrolyte for Solid‐State Li Metal Batteries

Abstract A combination of high ionic conductivity and facile processing suggest that sulfide‐based materials are promising solid electrolytes that have the potential to enable Li metal batteries. Although the Li 2 S‐P 2 S 5 (LPS) family of compounds exhibit desirable characteristics, it is known that Li metal preferentially propagates through microstructural defects, such as particle boundaries and/or pores. Herein, it is demonstrated that a near theoretical density (98% relative density) LPS 75‐25 glassy electrolyte exhibiting high ionic conductivity can be achieved by optimizing the molding pressure and temperature. The optimal molding pressure reduces porosity and particle boundaries while preserving the preferred amorphous structure. Moreover, molecular rearrangements and favorable Li coordination environments for conduction are attained. Consequently, the Young's Modulus approximately doubles (30 GPa) and the ionic conductivity increases by a factor of five (1.1 mS cm −1 ) compared to conventional room temperature molding conditions. It is believed that this study can provide mechanistic insight into processing‐structure‐property relationships that can be used as a guide to tune microstructural defects/properties that have been identified to have an effect on the maximum charging current that a solid electrolyte can withstand during cycling without short‐circuiting.

Garcia‐Mendez, Regina↗

Nanoweb Surface-Mounted Metal–Organic Framework Films with Tunable Amounts of Acid Sites as Tailored Catalysts

Metal–organic frameworks (MOFs) are a promising class of materials for many applications, due to their high chemical tunability and superb porosity. By growing MOFs as (thin-)films, additional properties and potential applications become available. In this work, copper (II) 1,3,5-benzenetricarboxylate (Cu-BTC) metal–organic framework (MOF) thin-films are reported, which were synthesized by spin-coating, resulting in “nanowebs”, that is, fiber-like structures. These surface-mounted MOFs (SURMOFs) were studied by using photoinduced force microscopy (PiFM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). The optimal concentration of precursors (10 mm ) was determined that resulted in chemically homogeneous, pure nanowebs. Furthermore, the morphology and (un)coordinated Cu sites in the web were tuned by varying the rotation speed of the spin-coating process. X-ray diffraction (XRD) analysis showed that rotation speeds ≥2000 rpm (with precursors in a water/ethanol solution) generate the catena-triaqua-μ-(1,3,5-benzenetricarboxylate)-copper(II), or Cu(BTC)(H 2 O) 3 coordination polymer. X-ray photoelectron spectroscopy (XPS) highlighted the strong decrease in number of (defective) Cu + sites, as the nanowebs mainly consist of coordinated Cu 2+ Lewis acid sites (LAS) and organic linker–linker, for example, hydrogen-bonding, interactions. Finally, the Lewis-acidic character of the Cu sites is illustrated by testing the films as catalysts in the isomerization of α-pinene oxide. The higher number of LAS (≥3000 rpm), result in higher campholenic aldehyde selectivity reaching up to 87.7 %. Furthermore, the strength of a combined micro- and spectroscopic approach in understanding the nature of MOF thin-films in a spatially resolved manner is highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Porting DMRG++ Scientific Application to OpenPOWER

With the rapidly changing microprocessor designs and architectural diversity (multi-cores, many-cores, accelerators) for the next generation HPC systems, scientific applications must adapt to the hardware, to exploit the different types of parallelism and resources available in the architecture. To get the benefit of all the in-node hardware threads, it is important to use a single programming model to map and coordinate the available work to the different heterogeneous execution units in the node (e.g., multi-core hardware threads (latency optimized), accelerators (bandwidth optimized), etc.).Our goal is to show that we can manage the node complexity of these systems by using OpenMP for in-node parallelization by exploiting different “programming styles” supported by OpenMP 4.5 to program CPU cores and accelerators. Finding out the suitable programming-style (e.g., SPMD style, multi-level tasks, accelerator programming, nested parallelism, or a combination of these) using the latest features of OpenMP to maximize performance and achieve performance portability across heterogeneous and homogeneous systems is still an open research problem.We developed a mini-application, Kronecker Product (KP), from the original DMRG++ application (sparse matrix algebra) computational motif to experiment with different OpenMP programming styles on an OpenPOWER architecture and present their results in this paper.

Chatterjee, Ronnie↗

Crystal structures of tricalcium citrates

The crystal structures of calcium citrate hexahydrate, calcium citrate tetrahydrate, and anhydrous calcium citrate have been solved using laboratory and synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Both the hexahydrate and tetrahydrate structures are characterized by layers of edge-sharing Ca coordination polyhedra, including triply chelated Ca. An additional isolated Ca is coordinated by water molecules, and two uncoordinated water molecules occur in the hexahydrate structure. The previously reported polymorph of the tetrahydrate contains the same layers, but only two H 2 O coordinated to the isolated Ca and two uncoordinated water molecules. Anhydrous calcium citrate has a three-dimensional network structure of Ca coordination polyhedra. The new polymorph of calcium citrate tetrahydrate is the major crystalline phase in several commercial calcium supplements.

Kaduk, James A.↗

δ -Doping of oxygen vacancies dictated by thermodynamics in epitaxial SrTiO 3 films

Homoepitaxial SrTiO 3 (110) film is grown by molecular beam epitaxy in ultra-high vacuum with oxygen diffusing from substrate as the only oxidant. The resulted oxygen vacancies (V O s ) are found to be spatially confined within few subsurface layers only, forming a quasi-two-dimensional doped region with a tunable high concentration. Such a δ-function distribution of V O s is essentially determined by the thermodynamics associated with the surface reconstruction, and facilitated by the relatively high growth temperature. Here, our results demonstrate that it is feasible to tune V O s distribution at the atomic scale by controlling the lattice structure of oxide surfaces. Transition metal oxide interfaces have exhibited a variety of novel phenomena, including the high-mobility two-dimensional electron gas, superconductivity and unusual magnetism. While these phenomena are inherently related to the artificially designed architecture, oxygen vacancies (V O s ) are recognized to be particularly important in determining the exotic behaviors of the oxides systems. As electron donors in oxides, V O s were observed to be one of the major factors for the high carrier density at the LaAlO 3 /SrTiO 3 interface. V O s induce ferromagnetism in the epitaxial LaCoO 3 films via the ordering of excess electrons in Co 3d orbit. It was also suggested that the existence of V O s plays an important role in the formation of undesirable insulating phase in ultrathin films of many metallic oxide materials, referred to as the “dead layer” behavior. How V O s are involved in such complex phenomena is still unclear. One essential issue toward the design of emergent properties of oxide films is how to characterize and control V O s at the atomic scale. Recently, quantitative measurements of V O concentration have been realized with high spatial resolution benefited by the development of the state-of-the-art aberration-corrected scanning transmission microscope (STEM) and related spectroscopy techniques. However, tuning the V O density precisely by growth control is still extremely challenging. Different oxidants, i.e., molecular O 2 , O 3 and atomic O, have been used with different feeding pressure during the growth. This approach is limited by thermodynamics of the material since the pressure of oxidant has to coordinate with temperature and other parameters in order to ensure the formation of the desired phase. In many cases the optimal condition for oxygen stoichiometry cannot be reached, and residual V O s are inevitably formed. It has been reported that V O s even form inhomogeneous clusters in SrTiO 3 (STO) films. Post annealing is another thermodynamic approach and seems to be effective to reduce the V O density. However, it does not allow the precise control of V O s distribution at the atomic scale either. In the current work, to study the control of V O s at the atomic scale, we grow SrTiO 3 homoepitaxial films along the polar [110] direction. Atomically well-defined (4 × 1) reconstruction is maintained on the surface all through the growth [see Fig. 1 (a) and (b)], which compensates the polarity. More importantly, the energy configuration associated with the surface reconstruction results in the spatial confinement of V O s within only few subsurface layers of the film, while their concentration remains extremely low on the topmost surface and in the bulk of STO substrate. In conclusion, we show that such a quasi-two-dimensional (2D) V O -doped layer, mimicking the δ-doping case in conventional semiconductors, can be precisely controlled.

36 MATERIALS SCIENCE↗