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At least 1,243 records · Page 69

The Status and Ambitions of the US Heavy Element Program

The aim of this whitepaper is to highlight the current capabilities and priorities of the US Heavy Element community and to provide the framework for a coordinated advancement of nuclear science from these studies. This is an organized effort to reflect on what has been achieved in the field given the recommendations and initiatives of the 2015 NSAC Long Range Plan, and on what can be realized in the next decade given current and possibly expanded investments. Current investments have positioned the US community to be among the world leaders in studies of the nuclear and chemical properties of the heaviest elements. These include studies of reaction mechanisms, moving us ever closer to the “island of stability”, in spectroscopy, allowing us to better understand nuclear structure at these extreme proton numbers, in chemical behavior, looking to determine how these elements should be placed on the Periodic Table, in performing the first measurements where isotopes are directly identified by their mass numbers, and in laying the foundation for a potential US-led new element discovery experiment. At present, the highest priority of the US Heavy Element community is to capitalize on the current investments by supporting the operations of US facilities at optimal values. These facilities include the Argonne Tandem Linac Accelerator System at Argonne National Laboratory and other Department of Energy facilities such as the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory, which has a dedicated superheavy element program, as well as university laboratories, including Texas A&M University. The High Flux Isotope Reactor at Oak Ridge National Laboratory is crucial to providing the radioactive isotopes required for heavy element science targets. This facility should be supported to provide the actinide materials that are essential for US-based science. Production of stable, rare isotopes for beam material, including 48 Ca, 50 Ti, 54 Cr and 58 Fe, at the Stable Isotope Production and Research Center is critical to continued research in heavy element science and should be a priority. The continued development of targets for heavy element science and retaining US-based expertise is critical for the heavy element community. This is an area that is currently under pressure. For example, the target laboratory at Argonne National Laboratory serves a broad community and is currently under threat due to loss of critical personnel. The skills needed to make targets for nuclear science and develop new targetry methods need to be supported long term at Argonne, Oak Ridge and Lawrence Livermore National Laboratories as well as maintaining the programs at Oregon State University and San José State University as vital pipelines for training students. Advances in theory are the foundation to understand how nuclei behave and to predict those behaviors in new circumstances. Progress in these studies will necessitate continued and new investment and access to high-performance computing. The future health of the heavy element field is dependent on the continuous support of talented early-career professionals at all levels. It is critical that opportunities continue to be created for the next generation to become established in heavy element research so that we can ensure the field is attracting and retaining the best minds for continued success. It is also clear that to ensure diversity of ideas, perspectives and techniques, we need to recruit diverse personnel that are trained at the best facilities. The heavy element community is in support of continued investment to programs with initiatives in diversity, equity, and inclusion. Looking to the next decade of research, support needs to maintain and grow US leadership in heavy element science. Specifically, new investments in state-of-the-art instrumentation will be essential to scientific development of the field and in expanding scientific knowledge. Advances in the next generation of electron cyclotron resonance ion sources, multi-reflection time-of-flight devices, laser spectroscopy, trapping methods and next generation alpha and gamma spectroscopy systems should be prioritized.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

MPC solution for optimal load shifting for buildings with ON/OFF staged packaged units: Experimental demonstration, and lessons learned

Small and medium-sized commercial buildings (SMCB) are significant demand response resources, and it is important to develop grid-responsive control algorithms that exploit those resources and create financial benefits for building owners and HVAC service providers. Furthermore, unlike large-sized commercial buildings, there is an opportunity to have universally applicable control solutions for many SMCBs since those buildings have a consistent HVAC system configuration: SMCBs are commonly served by multiple-staged air conditioning units controlled by their own thermostats. Despite the demand response potential and scalability, however, very few control solutions are available for SMCBs. Typical model predictive control (MPC) and heuristic control approaches for cooling load shifting that lower thermostat setpoints before an electric price jump are suitable mainly for large-sized commercial buildings where a continuous capacity modulation is possible, e.g., via dampers in variable air volume terminal units. However, those approaches can cause undesired, high peaks for SMCBs due to the nature of ON/OFF unit staging and narrow thermostat deadbands. This could discourage the use of advanced grid-responsive controls for SMCBs due to the concern of high demand charges, and has to be resolved. This paper presents a MPC solution that overcomes this challenge. It has a hierarchical MPC structure where an upper level MPC is responsible for electrical load shifting in response to an electric price signal while a lower level MPC is responsible for coordinating compressor stages to eliminate unnecessary peaks and follows the setpoints determined by the upper level MPC. In this work, two one-month, comprehensive laboratory tests have been carried out to demonstrate load shifting and cost savings for the algorithm. Interesting trade-offs between energy efficiency and load flexibility were observed and are discussed, and lessons learned for applying MPCs for SMCBs are also presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Near-UV and blue wavelength excitable Mg{sub 0.6}Ca{sub 2.16}Mo{sub 0.2}W{sub 0.8}O{sub 6}: Eu{sub 0.12}{sup 3+}/Na{sub 0.12}{sup +} high efficiency red phosphors

Red phosphors with narrow emission around 615 nm (with FWHM~5–10 nm) having chemical compositions of A{sub 0.6}Ca{sub 2.16}Mo{sub 0.2}W{sub 0.8}O{sub 6}: Eu{sub 0.12}{sup 3+}/Na{sub 0.12}{sup +} (A=Mg, Sr) have been found to exhibit the highest luminescence amongst the molybdate–tungstate family when excited by sources in the 380–420 nm wavelength range. Thus they are most suitable for enhancing color rendering index and lowering color temperature in phosphor converted white LEDs (pc-WLEDs) with near-UV/blue LED excitation sources. The excitation band edge in the near UV/blue wavelength in the reported phosphor has been attributed to the coordination environment of the transition metal ion (Mo{sup 6+}, W{sup 6+}) and host crystal structure. Furthermore the quantum efficiency of the phosphors has been enhanced by adjusting activator concentration, suitable compositional alloying using substitutional alkaline earth metal cations and charge compensation mechanisms. - Graphical abstract: The charge transfer excitation of orthorhombic Mg{sub 0.6}Ca{sub 2.16}Mo{sub 0.2}W{sub 0.8}O{sub 6}: Eu{sub 0.12}{sup 3+}/Na{sub 0.12}{sup +} is significantly higher than tetragonal CaMoO{sub 4}: Eu{sup 3+} phosphors making Mg{sub 0.6}Ca{sub 2.16}Mo{sub 0.2}W{sub 0.8}O{sub 6}: Eu{sub 0.12}{sup 3+}/Na{sub 0.12}{sup +} prime candidates for fabrication of warm white phosphor-converted LEDs. - Highlights: • LED excitable Mg{sub 0.6}Ca{sub 2.16}Mo{sub 0.2}W{sub 0.8}O{sub 6}: Eu{sub 0.12}{sup 3+}/Na{sub 0.12}{sup +} phosphors were synthesized. • These phosphors are 10 times more intense than CaMoO{sub 4}: Eu{sup 3+} red phosphors. • Their intensity and efficiency were enhanced by materials optimization techniques. • Such techniques include compositional alloying, charge compensation, etc.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Control of Catalyst Isomers Using an N -Phenyl-Substituted RN(CH 2 CH 2 P i Pr 2 ) 2 Pincer Ligand in CO 2 Hydrogenation and Formic Acid Dehydrogenation

A novel pincer ligand, i Pr PN Ph P [PhN- (CH 2 CH 2 P i Pr 2 ) 2 ], which is an analogue of the versatile MACHO ligand, iPr PN H P [HN(CH 2 CH 2 P i Pr 2 ) 2 ], was synthesized and characterized. The ligand was coordinated to ruthenium, and a series of hydride-containing complexes were isolated and characterized by NMR and IR spectroscopies, as well as X-ray diffraction. Comparisons to previously published analogues ligated by iPr PN H P and iPr PN Me P [CH 3 N(CH 2 CH 2 P i Pr 2 ) 2 ] illustrate that there are large changes in the coordination chemistry that occur when the nitrogen substituent of the pincer ligand is altered. For example, ruthenium hydrides supported by the iPr PN Ph P ligand always form the syn isomer (where syn/anti refer to the relative orientation of the group on nitrogen and the hydride ligand on ruthenium), whereas complexes supported by iPr PN H P form the anti isomer and complexes supported by iPr PN Me P form a mixture of syn and anti isomers. We evaluated the impact of the nitrogen substituent of the pincer ligand in catalysis by comparing a series of iPr PN R P (R = H, Me, Ph)-ligated ruthenium hydride complexes as catalysts for formic acid dehydrogenation and carbon dioxide (CO 2 ) hydrogenation to formate. The iPr PN Ph P-ligated species is the most active for formic acid dehydrogenation, and mechanistic studies suggest that this is likely because there are kinetic advantages for catalysts that operate via the syn isomer. In CO 2 hydrogenation, the iPr PN Ph P-ligated species is again the most active under our optimal conditions, and we report some of the highest turnover frequencies for homogeneous catalysts. Experimental and theoretical insights into the turnover-limiting step of catalysis provide a basis for the observed trends in catalytic activity. Additionally, the stability of our complexes enabled us to detect a previously unobserved autocatalytic effect involving the base that is added to drive the reaction. Overall, by modifying the nitrogen substituent on the MACHO ligand, we have developed highly active catalysts for formic acid dehydrogenation and CO 2 hydrogenation and also provided a framework for future catalyst development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Image phase shift invariance based cloud motion displacement vector calculation method for ultra-short-term solar PV power forecasting

Irradiance received on the earth's surface is the main factor that affects the output power of solar PV plants, and is chiefly determined by the cloud distribution seen in a ground-based sky image at the corresponding moment in time. It is the foundation for those linear extrapolation-based ultra-short-term solar PV power forecasting approaches to obtain the cloud distribution in future sky images from the accurate calculation of cloud motion displacement vectors (CMDVs) by using historical sky images. Theoretically, the CMDV can be obtained from the coordinate of the peak pulse calculated from a Fourier phase correlation theory (FPCT) method through the frequency domain information of sky images. The peak pulse is significant and unique only when the cloud deformation between two consecutive sky images is slight enough, which is likely possible for a very short time interval (such as 1?min or shorter) with common changes in the speed of cloud. Sometimes, there will be more than one pulse with similar values when the deformation of the clouds between two consecutive sky images is comparatively obvious under fast changing cloud speeds. This would probably lead to significant errors if the CMDVs were still only obtained from the single coordinate of the peak value pulse. However, the deformation estimation of clouds between two images and its influence on FPCT-based CMDV calculations are terrifically complex and difficult because the motion of clouds is complicated to describe and model. Therefore, to improve the accuracy and reliability under these circumstances in a simple manner, an image-phase-shift-invariance (IPSI) based CMDV calculation method using FPCT is proposed for minute time scale solar power forecasting. First, multiple different CMDVs are calculated from the corresponding consecutive images pairs obtained through different synchronous rotation angles compared to the original images by using the FPCT method. Second, the final CMDV is generated from all of the calculated CMDVs through a centroid iteration strategy based on its density and distance distribution. Third, the influence of different rotation angle resolution on the final CMDV is analyzed as a means of parameter estimation. Simulations under various scenarios including both thick and thin clouds conditions indicated that the proposed IPSI-based CMDV calculation method using FPCT is more accurate and reliable than the original FPCT method, optimal flow (OF) method, and particle image velocimetry (PIV) method.

14 SOLAR ENERGY↗

INTERSTELLAR NEUTRAL HELIUM IN THE HELIOSPHERE FROM IBEX OBSERVATIONS. II. THE WARSAW TEST PARTICLE MODEL (WTPM)

We have developed a refined and optimized version of the Warsaw Test Particle Model of interstellar neutral gas in the heliosphere, specially tailored for analysis of IBEX-Lo observations. The former version of the model was used in the analysis of neutral He observed by IBEX that resulted in an unexpected conclusion that the interstellar neutral He flow vector was different than previously thought and that a new population of neutral He, dubbed the Warm Breeze, exists in the heliosphere. It was also used in the reanalysis of Ulysses observations that confirmed the original findings on the flow vector, but suggested a significantly higher temperature. The present version of the model has two strains targeted for different applications, based on an identical paradigm, but differing in the implementation and in the treatment of ionization losses. We present the model in detail and discuss numerous effects related to the measurement process that potentially modify the resulting flux of ISN He observed by IBEX, and identify those of them that should not be omitted in the simulations to avoid biasing the results. This paper is part of a coordinated series of papers presenting the current state of analysis of IBEX-Lo observations of ISN He. Details of the analysis method are presented by Swaczyna et al. and results of the analysis are presented by Bzowski et al.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Battery Degradation Modeling in Hybrid Power Plants: An Island System Unit Commitment Study: Preprint

As hybrid power plants (HPPs), such as photovoltaic (PV) and battery combinations, become increasingly important in power systems with high renewable energy penetration to address PV variability and ensure grid stability. This paper focuses on the urgent need to model the coordination between PV and battery systems in HPPs while accounting for battery degradation. We present a generation scheduling model that explicitly incorporates PV-battery hybridization in the unit commitment problem. Moreover, the cost function of the HPP scheduling problem endogenously considers battery degradation with adjustable weights to strike a balance between minimizing production costs and prolonging battery life, particularly when providing energy arbitrage and ancillary services. Using a realistic island system simulation, we demonstrate that accounting for battery degradation in the scheduling problem can significantly extend battery life with only minor additional production costs.

battery degradation↗

Precise Motion Control of Hybrid Hydraulic Electric Architecture (HHEA)

Off-highway heavy-duty vehicles have been long-standing users of hydraulic systems for power transmission and control. However, traditional hydraulic systems suffer from significant energy losses which lead to increased operating costs and a larger carbon footprint due to higher CO2 emissions. Improving the efficiency of these mobile machines is crucial not only for reducing their environmental impact but also for saving billions of dollars in operating costs. Currently, the state-of-the-art Load Sensing Architecture uses throttling valves for control, which significantly reduces its efficiency and does not recuperate energy from over-running loads. Researchers have developed several architectures such as Common Pressure Rail systems, Displacement Control, STEAM, and Electrohydraulic Architecture to improve the efficiency of off-road mobile machines. However, each of these architectures has its drawbacks. To increase system efficiency and take advantage of electrification benefits, our research group has developed a novel Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA can significantly improve efficiency, decrease the size of electrical components, and maintain control performance. This new architecture has the potential to revolutionize the off-highway mobile machine industry and lead to a more sustainable future. The HHEA uses a set of common pressure rails to provide the majority of power to the actuators via power-dense hydraulics and uses electric motors for precise control and power modulation. In the context of off-road mobile machines, energy savings are undoubtedly important but it is equally important to consider the machines’ ability to perform tasks with precision and accuracy according to given commands. Therefore, precise motion control is of utmost importance to maintain the utility of Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA presents a unique challenge to motion control due to the discrete pressure changes that occur when the system switches between selected pressure rails. These changes are made to minimize system inefficiencies or to keep the system within the torque capability of the electric motor. Hence, it is important to solve the motion control challenges for HHEA. This thesis aims at developing an effective motion control strategy for HHEA. The dissertation presents a two-tiered control strategy for HHEA, comprising a high-level and a low-level controller. The primary responsibility of the high- level controller is to optimize energy efficiency by making informed pressure rail selections. On the other hand, the low-level controller is focused on achieving precise motion control of the HHEA, which is crucial for realizing the desired reference trajectories. To achieve this, the low-level controller utilizes a passivity-based backstepping integral controller as the nominal control, which handles the motion control between two pressure rail switches. Additionally, a separate least norm controller is utilized as a transition controller to manage motion control during pressure rail transitions. The effectiveness of the combined control strategy is demonstrated through experiments conducted on two hardware-in-the-loop testbeds. Furthermore, the HHEA is installed on the boom and stick actuators of a backhoe arm to build a Human-in-the-Loop system that a human operator can control. A real-time rail switching algorithm is developed to determine pressure rail switching based on present duty cycle information from the operator. Modifications have been made to the human-machine interface to achieve more intuitive control. Modifications include performing control in the task-oriented coordinates, incorporating pressure feedback to enhance control with physical interaction, and using velocity field control to simplify multi-degree-of-freedom tasks and to enable novice operators to perform them with reduced risk, improved efficiency, and productivity. The research in this dissertation makes significant contributions to the field of off-road mobile machine control, providing a novel and effective control strategy for the HHEA, and demonstrating the potential for simplified machine operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhancing Cycling Stability of Lithium Metal Batteries by a Bifunctional Fluorinated Ether

Abstract The lifespan of lithium (Li) metal batteries (LMBs) can be greatly improved by the formation of inorganic‐rich electrode‐electrolyte interphases (EEIs) (including solid‐electrolyte interphase on anode and cathode‐electrolyte interphase on cathode). In this work, a localized high‐concentration electrolyte containing lithium bis(fluorosulfonyl)imide (LiFSI) salt, 1,2‐dimethoxyethane (DME) solvent and 1,2‐bis(1,1,2,2‐tetrafluoroethoxy)ethane (BTFEE) diluent is optimized. BTFEE is a fluorinated ether with weakly‐solvating ability for LiFSI so it also acts as a co‐solvent in this electrolyte. It can facilitate anion decomposition at electrode surfaces and promote the formation of more inorganic‐rich EEI layers. With an optimized molar ratio of LiFSI:DME:BTFEE = 1:1.15:3, LMBs with a high loading (4 mAh cm −2 ) lithium nickel manganese cobalt oxide (LiNi 0.8 Mn 0.1 Co 0.1 ) cathode can retain 80% capacity in 470 cycles when cycled in a voltage range of 2.8–4.4 V. The fundamental understanding on the functionality of BTFEE revealed in this work provides new perspectives on the design of practical high‐energy density battery systems.

25 ENERGY STORAGE↗

Development of a novel depth of interaction PET detector using highly multiplexed G-APD cross-strip encoding

Purpose: The aim of this study was to develop a prototype PET detector module for a combined small animal positron emission tomography and magnetic resonance imaging (PET/MRI) system. The most important factor for small animal imaging applications is the detection sensitivity of the PET camera, which can be optimized by utilizing longer scintillation crystals. At the same time, small animal PET systems must yield a high spatial resolution. The measured object is very close to the PET detector because the bore diameter of a high field animal MR scanner is limited. When used in combination with long scintillation crystals, these small-bore PET systems generate parallax errors that ultimately lead to a decreased spatial resolution. Thus, we developed a depth of interaction (DoI) encoding PET detector module that has a uniform spatial resolution across the whole field of view (FOV), high detection sensitivity, compactness, and insensitivity to magnetic fields. Methods: The approach was based on Geiger mode avalanche photodiode (G-APD) detectors with cross-strip encoding. The number of readout channels was reduced by a factor of 36 for the chosen block elements. Two 12 × 2 G-APD strip arrays (25μm cells) were placed perpendicular on each face of a 12 × 12 lutetium oxyorthosilicate crystal block with a crystal size of 1.55 × 1.55 × 20 mm. The strip arrays were multiplexed into two channels and used to calculate the x, y coordinates for each array and the deposited energy. The DoI was measured in step sizes of 1.8 mm by a collimated {sup 18}F source. The coincident resolved time (CRT) was analyzed at all DoI positions by acquiring the waveform for each event and applying a digital leading edge discriminator. Results: All 144 crystals were well resolved in the crystal flood map. The average full width half maximum (FWHM) energy resolution of the detector was 12.8% ± 1.5% with a FWHM CRT of 1.14 ± 0.02 ns. The average FWHM DoI resolution over 12 crystals was 2.90 ± 0.15 mm. Conclusions: The novel DoI PET detector, which is based on strip G-APD arrays, yielded a DoI resolution of 2.9 mm and excellent timing and energy resolution. Its high multiplexing factor reduces the number of electronic channels. Thus, this cross-strip approach enables low-cost, high-performance PET detectors for dedicated small animal PET and PET/MRI and potentially clinical PET/MRI systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance and Architecture Lab Modeling Tool

Analytical application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult. Furthermore, models are frequently expressed in forms that are hard to distribute and validate. The Performance and Architecture Lab Modeling tool, or Palm, is a modeling tool designed to make application modeling easier. Palm provides a source code modeling annotation language. Not only does the modeling language divide the modeling task into sub problems, it formally links an application's source code with its model. This link is important because a model's purpose is to capture application behavior. Furthermore, this link makes it possible to define rules for generating models according to source code organization. Palm generates hierarchical models according to well-defined rules. Given an application, a set of annotations, and a representative execution environment, Palm will generate the same model. A generated model is a an executable program whose constituent parts directly correspond to the modeled application. Palm generates models by combining top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. A model's hierarchy is defined by static and dynamic source code structure. Because Palm coordinates models and source code, Palm's models are 'first-class' and reproducible. Palm automates common modeling tasks. For instance, Palm incorporates measurements to focus attention, represent constant behavior, and validate models. Palm's workflow is as follows. The workflow's input is source code annotated with Palm modeling annotations. The most important annotation models an instance of a block of code. Given annotated source code, the Palm Compiler produces executables and the Palm Monitor collects a representative performance profile. The Palm Generator synthesizes a model based on the static and dynamic mapping of annotations to program behavior. The model -- an executable program -- is a hierarchical composition of annotation functions, synthesized functions, statistics for runtime values, and performance measurements.

Tallent, Nathan↗

GROWTH on S190426c: Real-time Search for a Counterpart to the Probable Neutron Star–Black Hole Merger using an Automated Difference Imaging Pipeline for DECam

The discovery of a transient kilonova following the gravitational-wave (GW) event GW170817 highlighted the critical need for coordinated rapid and wide-field observations, inference, and follow-up across the electromagnetic spectrum. In the southern hemisphere, the Dark Energy Camera (DECam) on the Blanco 4 m telescope is well suited to this task, as it is able to cover wide fields quickly while still achieving the depths required to find kilonovae like the one accompanying GW170817 to ~500 Mpc, the binary neutron star (NS) horizon distance for current generation of LIGO/Virgo collaboration (LVC) interferometers. Here, as part of the multi-facility follow-up by the Global Relay of Observatories Watching Transients Happen collaboration, we describe the observations and automated data movement, data reduction, candidate discovery, and vetting pipeline of our target-of-opportunity DECam observations of S190426c, the first possible NS-black hole merger detected in GWs. Starting 7.5 hr after S190426c, over 11.28 hr of observations, we imaged an area of 525 deg 2 ( r band) and 437 deg 2 ( z band); this was 16.3% of the total original localization probability, and nearly all of the probability visible from the southern hemisphere. The machine-learning-based pipeline was optimized for fast turnaround, delivering transients for human vetting within 17 minutes, on average, of shutter closure. We reported nine promising counterpart candidates 2.5 hr before the end of our observations. One hour after our data-taking ended (roughly 20 hr after the announcement of S190426c), LVC released a refined skymap that reduced the probability coverage of our observations to 8.0%, demonstrating a critical need for localization updates on shorter (~hour) timescales. Our observations yielded no detection of a bona fide counterpart to m z = 21.7 and m r = 22.2 at the 5σ level of significance, consistent with the refined LVC positioning. Here, we view these observations and rapid inferencing as an important real-world test for this novel end-to-end wide-field pipeline.

79 ASTRONOMY AND ASTROPHYSICS↗

Corn stover variability drives differences in bisabolene production by engineered Rhodotorula toruloides

Microbial conversion of lignocellulosic biomass represents an alternative route for production of biofuels and bioproducts. While researchers have mostly focused on engineering strains such as Rhodotorula toruloides for better bisabolene production as a sustainable aviation fuel, less is known about the impact of the feedstock heterogeneity on bisabolene production. Critical material attributes like feedstock composition, nutritional content, and inhibitory compounds can all influence bioconversion. Further, the given feedstocks can have a marked influence on selection of suitable pretreatment and hydrolysis technologies, optimizing the fermentation conditions, and possibly even modifying the microorganism's metabolic pathways, to better utilize the available feedstock. Here, this work aimed to examine and understand how variations in corn stover batches, anatomical fractions, and storage conditions impact the efficiency of bisabolene production by R. toruloides. All of these represent different facets of feedstock heterogeneity. Deacetylation, mechanical refining, and enzymatic hydrolysis of these variable feedstocks served as the basis of this research. The resulting hydrolysates were converted to bisabolene via fermentation, a sustainable aviation fuel precursor, using an engineered R. toruloides strain. This study showed that different sources of feedstock heterogeneity can influence microbial growth and product titer in counterintuitive ways, as revealed through global analysis of protein expression. The maximum bisabolene produced by R. toruloides was on the stalk fraction of corn stover hydrolysate (8.89 ± 0.47 g/L). Further, proteomics analysis comparing the protein expression between the anatomic fractions showed that proteins relating to carbohydrate metabolism, energy production, and conversion as well as inorganic ion transport metabolism were either significantly upregulated or downregulated. Specifically, downregulation of proteins related to the iron–sulfur cluster in stalk fraction suggests a coordinated response by R. toruloides to maintain overall metabolic balance, and this was corroborated by the concentration of iron in the feedstocks.

09 BIOMASS FUELS↗

Symmetry-mode analysis for intuitive observation of structure-property relationships in the lead-free antiferroelectric (1-x)AgNbO 3 -xLiTaO 3

Functional materials are of critical importance to electronic and smart devices. A deep understanding of the structure–property relationship is essential for designing new materials. In this work, instead of utilizing conventional atomic coordinates, a symmetry-mode approach is successfully used to conduct structure refinement of the neutron powder diffraction data of (1-x)AgNbO3–xLiTaO3 (0 ≤ x ≤ 0.09) ceramics. This provides rich structural information that not only clarifies the controversial symmetry assigned to pure AgNbO3 but also explains well the detailed structural evolution of (1-x)AgNbO3–xLiTaO3 (0 ≤ x ≤ 0.09) ceramics, and builds a comprehensive and straightforward relationship between structural distortion and electrical properties. It is concluded that there are four relatively large-amplitude major modes that dominate the distorted Pmc21 structure of pure AgNbO3, namely a Λ3 antiferroelectric mode, a T4+ a-a-c0 octahedral tilting mode, an H2 a0a0c+/a0a0c- octahedral tilting mode and a Γ4- ferroelectric mode. The H2 and Λ3 modes become progressively inactive with increasing x and their destabilization is the driving force behind the composition-driven phase transition between the Pmc21 and R3c phases. This structural variation is consistent with the trend observed in the measured temperature-dependent dielectric properties and polarization–electric field (P-E) hysteresis loops. The mode crystallography applied in this study provides a strategy for optimizing related properties by tuning the amplitudes of the corresponding modes in these novel AgNbO3-based (anti)ferroelectric materials.

36 MATERIALS SCIENCE↗

Systems Level Dissection of Anaerobic Methane Cycling: Quantitative Measurements of Single Cell Ecophysiology, Genetic Mechanisms, and Microbial Interactions

The global biological CH4 cycle is largely controlled through coordinated and often intimate microbial interactions between archaea and bacteria, the majority of which are still unknown or have been only cursorily identified. Members of the methanotrophic archaea, aka ‘ANME’, are believed to play a major role in the cycling of methane in anoxic environments coupled to sulfate, nitrate, and possibly iron and manganese oxides, frequently forming diverse physical and metabolic partnerships with a range of bacteria. The thermodynamic challenges overcome by the ANME and their bacterial partners and corresponding slow rates of growth are common characteristics in anaerobic ecosystems, and, in stark contrast to most cultured microorganisms, this type of energy and resource limited microbial lifestyle is likely the norm in the environment. While we have gained an in-depth systems level understanding of fast-growing, energy-replete microorganisms, comparatively little is known about the dynamics of cell respiration, growth, protein turnover, gene expression, and energy storage in the slow-growing microbial majority. These fundamental properties, combined with the observed metabolic and symbiotic versatility of methanotrophic ANME, make these cooperative microbial systems a relevant (albeit challenging) system to study and for which to develop and optimize culture-independent methodologies, which enable a systems-level understanding of microbial interactions and metabolic networks. We used an integrative systems biology approach to study anaerobic sediment microcosms and methane-oxidizing bioreactors and expanded our understanding of the methanotrophic ANME archaea, their interactions with physically-associated bacteria, ecophysiological characteristics, and underlying genetic basis for cooperative microbial methane-oxidation linked with different terminal electron acceptors. Our approach is inherently multi-disciplinary and multi-scaled, combining transcriptional and proteomic analyses with high resolution microscopy techniques, and stable isotopic and chemical analyses that span community level ‘omics investigations (cm scale) to interspecies consortia (µm scale), to the individual cell and its subcellular components (nm scale). We have organized our methodological approach into three broad categories, RNA-based, Protein-targeted and Geochemical, each encompassing a range of scales, with many techniques and resulting datasets that are highly complementary with one another, and together, offer a unique systems-level perspective of methane-based microbial interactions.

03 NATURAL GAS↗

Transmission and Distribution Real-Time Analysis Software for Monitoring and Control: Design and Simulation Testing

The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. This paper introduces software designed to meet these challenges. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. The software architecture along with selected analysis modules is presented. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hardware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.

14 SOLAR ENERGY↗

Optimizing End-to-End Big Data Transfers over Terabits Network Infrastructure

While future terabit networks hold the promise of significantly improving big-data motion among geographically distributed data centers, significant challenges must be overcome even on today's 100 gigabit networks to realize end-to-end performance. Multiple bottlenecks exist along the end-to-end path from source to sink, for instance, the data storage infrastructure at both the source and sink and its interplay with the wide-area network are increasingly the bottleneck to achieving high performance. In this study, we identify the issues that lead to congestion on the path of an end-to-end data transfer in the terabit network environment, and we present a new bulk data movement framework for terabit networks, called LADS. LADS exploits the underlying storage layout at each endpoint to maximize throughput without negatively impacting the performance of shared storage resources for other users. LADS also uses the Common Communication Interface (CCI) in lieu of the sockets interface to benefit from hardware-level zero-copy, and operating system bypass capabilities when available. It can further improve data transfer performance under congestion on the end systems using buffering at the source using flash storage. With our evaluations, we show that LADS can avoid congested storage elements within the shared storage resource, improving input/output bandwidth, and data transfer rates across the high speed networks. We also investigate the performance degradation problems of LADS due to I/O contention on the parallel file system (PFS), when multiple LADS tools share the PFS. We design and evaluate a meta-scheduler to coordinate multiple I/O streams while sharing the PFS, to minimize the I/O contention on the PFS. Finally, with our evaluations, we observe that LADS with meta-scheduling can further improve the performance by up to 14 percent relative to LADS without meta-scheduling.

97 MATHEMATICS AND COMPUTING↗

Development of Integrated Biomimetic Framework with Intelligent Monitoring, Cognition and Decision Capabilities for Control of Advanced Energy Plants

The objective of the project entitled “Development of Integrated Biomimetic Framework with Intelligent Monitoring, Cognition, and Decision Capabilities for Control of Advanced Energy Plants” is to develop algorithms and methodologies for designing a biomimetic control system for optimal control of advanced energy plants. Traditionally, control systems have been designed based on assumed a priori knowledge of the process system. A number of variables are manipulated to accomplish disturbance rejection and/or servo control performance. While it is possible to adapt the process model based on available data, the control structure and the controllers rarely change. Thus, the knowledge learnt during process operation is lost or remains underutilized. In addition, the business models of today, especially for power plants, are rapidly changing. The power plant operators are being pushed to the edge due to the penetration of renewable energy derived power to the grid, the demand for high efficiency, ever-tightening environmental regulations, and requirements for increased plant availability. Thus, power plant operations need to be agile and should adapt quickly to the dynamic requirements. A number of characteristics distinguish biological systems from the traditional process control systems. Self-organization, distributed intelligence, adaptability, intelligent monitoring, cognition, and decision capabilities are some of the powerful characteristics of the biological world that can be effectively utilized in process control. At the top, the central nervous system (CNS) integrates the information from and coordinates the activities of all parts of the bodies (for bilaterian animals). Inspired by these distinct characteristics, this project seeks to develop methodologies and algorithms to accomplish: (i) self-organization of the control structure for maximizing the plant’s operating profit by mimicking the function of the cortical areas in the human brain, (ii) distributed and adaptive controllers that mimic the rule of pursuit present in ants, (iii) intelligent monitoring of the controllers powered with cognition and decision capabilities that mimic the artificial immune systems, and (iv) seamless coordination and integration in the control system that mimics the CNS.

20 FOSSIL-FUELED POWER PLANTS↗