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At least 1,243 records · Page 69

DigiFloat (Final Scientific/Technical Report)

This purpose of this report is to document the development of a floating offshore wind platform Digital Twin for the ARPA-E-funded DigiFloat project led by Principle Power, Inc. In Offshore Wind, Digital Twins are aimed at reducing farm-wide OPEX expenditures through reduced-basis inspection, assessing life extension methods, and obtaining better knowledge of the deployed assets for future product optimization. There is a high level of technical effectiveness and economic feasibility for the technology investigated, as it uses commercial off-the-shelf sensors, and a commercial software package. A substantial portion of the project goals are improvement of existing technology for use with floating wind turbines, and new application of an existing technology to a rapidly-growing sector. A few sensors applied to a small number of units bring benefit to the entire fleet of floating wind turbines in a given farm, and in other future wind farms. The benefits to the public of this project are further optimization and maturation of floating wind technology, to bring it to the U.S. market faster and cheaper.

17 WIND ENERGY↗

Field Validation of a Grid-Interactive Efficient Building Software Solution

The U.S. General Services Administration's (GSA's) Green Proving Ground (GPG) program, in partnership with the National Laboratory of the Rockies (NLR), completed a field study of a Grid-Interactive Efficient Buildings (GEB) software solution. The study focused on a single testbed facility to test the GEB functionality of the software solution, along with other features. The testbed facility - a courthouse - is a common building type in GSA's vast building portfolio, offering potentially impactful findings on a scalable level. The study evaluated Prescriptive Data's technology, Nantum OS, a connected building operating system ("GEB Solution") which aggregates multiple sources of previously siloed building data and combines that data with external sources, such as weather information or utility signals, into a single integrated platform. A GEB Solution is a type of Energy Management Information System (EMIS). EMIS is defined as a system of devices, data services, and software applications that communicates with any building system or third-party data source to aggregate and transform data into new capabilities to aid in the optimization of energy use at the building, campus, or agency level. This specific GEB Solution is an EMIS with ASO, automated system optimization, offering supervisory control of certain aspects of the Building Automation System (BAS). Multiple features were evaluated including, but not limited to, Continuous Demand Management to avoid setting new monthly kilowatt (kW) peaks, energy efficiency for reduction of kilowatt hours (kWh) and natural gas consumption, and automated demand response (ADR) for purposes of lowering demand during a utility called Demand Response (DR) event. The testbed facility was the Foley Federal Building and US Courthouse ("Foley Federal Building") located in Las Vegas, NV. This is a 209,496 sq. ft. building constructed in the 1960s with major renovations in 2004. The facility was a good candidate due to the large prevalence of office and courthouse spaces in the GSA portfolio of buildings. It also has many features which allow integration into and control of the building and a strong facilities team to assist with the study. Quantitative and qualitative performance objectives were developed using GSA's GPG GEB project template along with input from the vendor and building facility staff; these are outlined in Table 1. The quantitative performance objectives focused on continuous demand management, energy efficiency, and automated demand response. The qualitative performance objectives focused on the ease of installation and commissioning as well as the operability of the GEB solution. Other performance metrics that are reported on include carbon reduction, cost effectiveness, and occupant acceptance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Validation of HVAC Hardware-in-the-Loop Simulation for Advanced Control Strategies in Smart Homes: Preprint

Residences with smart thermostats can use advanced control strategies to manage their cooling/heating demand, but it is difficult to evaluate optimal control strategies for flexible heating, ventilation, and air conditioning (HVAC) systems in a traditional laboratory setting. The HVAC hardware-in-the-loop (HIL) system combines physical HVAC equipment and a physical thermostat with a simulated house to enable realistic operation of the hardware in any climate. This HIL platform allows researchers to evaluate advanced control strategies for homes with different construction or vintage types, as well as different climates and occupancy schedules. To demonstrate the capabilities of the HVAC HIL system, experimental results with a SEER 16, HSPF 9.5, 3 ton single-speed air source heat pump are validated against past field data collected from a heavily instrumented, unoccupied, retrofit house located in Sacramento, California. Three different cooling strategies are recreated in the HVAC HIL platform, including two different pre-cooling schedules that were designed to shift energy use away from the evening peak. The room temperatures, heat pump energy use, and run time show good agreement between the field data and HIL experimental results for three strategies.

cooling strategies↗

High-throughput sequencing of the chloroplast and mitochondrion of Chlamydomonas reinhardtii to generate improved de novo assemblies, analyze expression patterns and transcript speciation, and evaluate diversity among laboratory strains and wild isolates

Chlamydomonas reinhardtii is a unicellular chlorophyte alga that is widely studied as a reference organism for understanding photosynthesis, sensory and motile cilia, and for development of an algal-based platform for producing biofuels and bio-products. Its highly repetitive, ~205-kbp circular chloroplast genome and ~15.8-kbp linear mitochondrial genome were sequenced prior to the advent of high-throughput sequencing technologies. Here, high coverage shotgun sequencing was used to assemble both organellar genomes de novo. These new genomes correct dozens of errors in the prior genome sequences and annotations. Gen-ome sequencing coverage indicates that each cell contains on average 83 copies of the chloroplast genome and 130 copies of the mitochondrial genome. Using protocols and analyses optimized for organellar tran-scripts, RNA-Seq was used to quantify their relative abundances across 12 different growth conditions. Forty-six percent of total cellular mRNA is attributable to high expression from a few dozen chloroplast genes. RNA-Seq data were used to guide gene annotation, to demonstrate polycistronic gene expression, and to quantify splicing of psaA and psbA introns. In contrast to a conclusion from a recent study, we found that chloroplast transcripts are not edited. Unexpectedly, cytosine-rich polynucleotide tails were observed at the 3’-end of all mitochondrial transcripts. A comparative genomics analysis of eight laboratory strains and 11 wild isolates of C. reinhardtii identified 2658 variants in the organellargenomes, which is 1/10th as much genetic diversity as is found in the nucleus.

ftsH↗

WaterTAP3 (The Water Technoeconomic Assessment Pipe-Parity Platform)

The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience.

Miara, Ariel↗

Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3)

The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience. A publicly available graphical user interface is currently under development.

Miara, Ariel↗

Complex Density Wave Orders and Quantum Phase Transitions in a Model of Square-Lattice Rydberg Atom Arrays

In this work, we describe the zero-temperature phase diagram of a model of a two-dimensional square-lattice array of neutral atoms, excited into Rydberg states and interacting via strong van der Waals interactions. Using the density-matrix renormalization group algorithm, we map out the phase diagram and obtain a rich variety of phases featuring complex density wave orderings, upon varying lattice spacing and laser detuning. While some of these phases result from the classical optimization of the van der Waals energy, we also find intrinsically quantum-ordered phases stabilized by quantum fluctuations. These phases are surrounded by novel quantum phase transitions, which we analyze by finite-size scaling numerics and Landau theories. Our work highlights Rydberg quantum simulators in higher dimensions as promising platforms to realize exotic many-body phenomena.

74 ATOMIC AND MOLECULAR PHYSICS↗

An Automated Microfluidic Assay for Photonic Crystal Enhanced Detection and Analysis of an Antiviral Antibody Cancer Biomarker in Serum

Here, we report on the implementation of an automated platform for detecting the presence of an antibody biomarker for human papillomavirus-associated oropharyngeal cancer from a single droplet of serum, in which a nanostructured photonic crystal surface is used to amplify the output of a fluorescence-linked immunosorbent assay. The platform is comprised of a microfluidic cartridge with integrated photonic crystal chips that interfaces with an assay instrument that automates the introduction of reagents, wash steps, and surface drying. Upon assay completion, the cartridge interfaces with a custom laser-scanning instrument that couples light into the photonic crystal at the optimal resonance condition for fluorescence enhancement. The instrument is used to measure the fluorescence intensity values of microarray spots corresponding to the biomarkers of interest, in addition to several experimental controls that verify correct functioning of the assay protocol. In this work, we report both dose-response characterization of the system using anti-E7 antibody introduced at known concentrations into serum and characterization of a set of clinical samples from which results were compared with a conventional enzyme-linked immunosorbent assay (ELISA) performed in microplate format. Finally, the demonstrated capability represents a simple, rapid, automated, and high-sensitivity method for multiplexed detection of protein biomarkers from a low-volume test sample.

59 BASIC BIOLOGICAL SCIENCES↗

Not just for programmers: How GitHub can accelerate collaborative and reproducible research in ecology and evolution

Abstract Researchers in ecology and evolutionary biology are increasingly dependent on computational code to conduct research. Hence, the use of efficient methods to share, reproduce, and collaborate on code as well as document research is fundamental. GitHub is an online, cloud‐based service that can help researchers track, organize, discuss, share, and collaborate on software and other materials related to research production, including data, code for analyses, and protocols. Despite these benefits, the use of GitHub in ecology and evolution is not widespread. To help researchers in ecology and evolution adopt useful features from GitHub to improve their research workflows, we review 12 practical ways to use the platform. We outline features ranging from low to high technical difficulty, including storing code, managing projects, coding collaboratively, conducting peer review, writing a manuscript, and using automated and continuous integration to streamline analyses. Given that members of a research team may have different technical skills and responsibilities, we describe how the optimal use of GitHub features may vary among members of a research collaboration. As more ecologists and evolutionary biologists establish their workflows using GitHub, the field can continue to push the boundaries of collaborative, transparent, and open research.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Advanced simulation capability for environmental management - current status and future applications

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater (EM-12), is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach that is currently aimed at understanding and predicting contaminant fate and transport in natural and engineered systems. ASCEM is a modular and open source high-performance computing tool. It will be used to facilitate integrated approaches to modeling and site characterization, and provide robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of capabilities, with current emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Tool-sets and High-Performance Computing (HPC) multi-process simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The integration of the Platform and HPC capabilities were tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities in 2012. The current maturity of the ASCEM computational and analysis capabilities has afforded the opportunity for collaborative efforts to develop decision analysis tools to support and optimize radioactive waste disposal. Recent advances in computerized decision analysis frameworks provide the perfect opportunity to bring this capability into ASCEM. This will allow radioactive waste disposal to be evaluated based on decision needs, such as disposal, closure, and maintenance. Decision models will be used in ASCEM to identify information/data needs, and model refinements that might be necessary to effectively reduce uncertainty in waste disposal decisions. Decision analysis models start with tools for framing the problem, and continue with modeling both the science side of the problem (for example, inventories, source terms, fate and transport, receptors, risk, etc.), and the cost side of the problem, which could include costs of implementation of any action that is chosen (e.g., for disposal or closure), and the values associated with those actions. The cost side of the decision problem covers economic, environmental and societal costs, which correspond to the three pillars of sustainability (economic, social, and environmental). These tools will facilitate stakeholder driven decision analysis to support optimal sustainable solutions in ASCEM. In this paper the current state of ASCEM is first described, followed by a description of the approach that will be taken to augment ASCEM for simulating fate and transport with tools that facilitate a top-down or systems level view of finding optimal, sustainable solutions to difficult environmental (including radioactive waste) problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Study of Successive Over-relaxation Method Parallelization over Modern HPC Languages

Successive over-relaxation (SOR) is a computationally intensive, yet extremely important iterative solver for solving linear systems. Due to recent trends of exponential growth in amount of data generated and increasing problem sizes, serial platforms have proved to be insucient in providing the required computational power. In this paper, we present parallel implementations of red-black SOR method using three modern programming languages namely Chapel, D and Go. We employ SOR method for solving 2D steady-state heat conduction problem. We discuss the optimizations incorporated and the features of these languages which are crucial for improving the program performance. Experiments have been performed using 2, 4, and 8 threads and performance results are compared with serial execution. The analysis of results provides important insights into working of SOR method.

Mittal, Sparsh↗

Catalytic Difunctionalization of Cyclic Dienes: Direct Entry to Novel ROMP Monomers

We developed a catalytic platform to convert simple hydrocarbon feedstocks into valuable, tunable materials by leveraging nickel-catalyzed difunctionalization of cyclic dienes to access a novel class of cyclic alkene monomers. These monomers undergo ring-opening metathesis polymerization (ROMP) to yield sequence-controlled polymers with defined stereochemistry. Through mechanistic studies and catalyst optimization, we established a scalable, gram-level synthesis for selective diarylation, and expanded the reaction scope to include arylalkylation through rationally tuning the organoboron coupling partner. The resulting polymers were systematically studied to understand how steric, electronic, and stereochemical features influence polymerization behavior and bulk material properties. Functionalized derivatives bearing sulfonated groups were explored as proton-exchange membranes, and chemical recycling pathways were developed to recover monomers from the final materials. This work bridges small-molecule catalysis and macromolecular design, enabling access to tunable, recyclable polymers from abundant hydrocarbon starting materials.

36 MATERIALS SCIENCE↗

REopt Screenings Catalyze Development of Hundreds of Megawatts of Renewable Energy for Federal Agencies

The Federal Energy Management Program (FEMP) offers renewable energy project assistance to federal agencies, which often begins with a desktop screening to develop a prioritized portfolio of project opportunities. FEMP uses the National Renewable Energy Laboratory's REopt energy planning platform to screen potential renewable energy opportunities at a single site or across a range of sites. REopt helps organizations prioritize the most economi­cally and technically viable projects for further study and identifies the size and mix of technologies that meet the orga­nization's goals at minimum cost, along with the optimal operating strategies.

FEMP↗

Exploration of superconducting multi-mode cavity architectures for quantum computing

Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high quality factor three-dimensional superconducting cavities to extend the lifetime of quantum systems. To increase the computational capability of this architecture, we are exploring a multimode approach. This paper presents the design optimization process of a multi-cell SRF cavity to perform quantum computation based on an existing design developed in the scope of particle accelerator technology. We perform parametric electromagnetic simulations to evaluate and optimize the design. In particular, we focus on the analysis of the interaction between a nonlinear superconducting circuit known as the transmon and the cavity. This parametric design optimization is structured to serve as a blueprint for future studies on similar systems.

Reineri, Alessandro↗

In Search of Stronger/Cheaper Chitin Nanofibers through Electrospinning of Chitin–Cellulose Composites Using an Ionic Liquid Platform

The ability of the ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate ([C 2 mim][OAc]) to solubilize natural biopolymers (e.g., chitin and cellulose) without any chemical modification has been used to develop a one-pot process to prepare a spinning dope by extracting chitin from shrimp shell, codissolving microcrystalline cellulose (MCC, DP = 270), and electrospinning nanomats from shrimp shell-extract/MCC solutions. The resulting spinning dopes were prepared with optimal viscosity of 380 to 900 cP, and conductivity and surface tension of ~2.8 mS/cm and ~36 dyn/cm, respectively; however, nanofibers could only be prepared when the chitin/MCC ratios in SS-extract/ MCC solution were between 9/1 and 6/4. Compared to nanomats electrospun from shrimp shell-extract solution, 7/3 chitin/MCC composite nanomats demonstrated a 2-fold improvement in hardness and 3-fold improvement in elasticity, although further increases in MCC content resulted in lowering both parameters which nonetheless were higher than the pure chitin nanomats. We conclude this one pot process for preparing spinning dopes directly from shrimp shell-extract is a viable method to prepare chitin/MCC composites of improved strength/elasticity at lower costs.

36 MATERIALS SCIENCE↗

Establishing a versatile toolkit of flux enhanced strains and cell extracts for pathway prototyping

Building and optimizing biosynthetic pathways in engineered cells holds promise to address societal needs in energy, materials, and medicine, but it is often time-consuming. Cell-free synthetic biology has emerged as a powerful tool to accelerate design-build-test-learn cycles for pathway engineering with increased tolerance to toxic compounds. However, most cell-free pathway prototyping to date has been performed in extracts from wildtype cells which often do not have sufficient flux towards the pathways of interest, which can be enhanced by engineering. Here, in this study, to address this gap, we create a set of engineered Escherichia coli and Saccharomyces cerevisiae strains rewired via CRISPR-dCas9 to achieve high-flux toward key metabolic precursors; namely, acetyl-CoA, shikimate, triose-phosphate, oxaloacetate, α-ketoglutarate, and glucose-6-phosphate. Cell-free extracts generated from these strains are used for targeted enzyme screening in vitro. As model systems, we assess in vivo and in vitro production of triacetic acid lactone from acetyl-CoA and muconic acid from the shikimate pathway. The need for these platforms is exemplified by the fact that muconic acid cannot be detected in wildtype extracts provided with the same biosynthetic enzymes. We also perform metabolomic comparison to understand biochemical differences between the cellular and cell-free muconic acid synthesis systems (E. coli and S. cerevisiae cells and cell extracts with and without metabolic rewiring). While any given pathway has different interfaces with metabolism, we anticipate that this set of pre-optimized, flux enhanced cell extracts will enable prototyping efforts for new biosynthetic pathways and the discovery of biochemical functions of enzymes.

59 BASIC BIOLOGICAL SCIENCES↗

Autonomous platform for solution processing of electronic polymers

The manipulation of electronic polymers’ solid-state properties through processing is crucial in electronics and energy research. Yet, efficiently processing electronic polymer solutions into thin films with specific properties remains a formidable challenge. We introduce Polybot, an artificial intelligence (AI) driven automated material laboratory designed to autonomously explore processing pathways for achieving high-conductivity, low-defect electronic polymers films. Leveraging importance-guided Bayesian optimization, Polybot efficiently navigates a complex 7-dimensional processing space. In particular, the automated workflow and algorithms effectively explore the search space, mitigate biases, employ statistical methods to ensure data repeatability, and concurrently optimize multiple objectives with precision. The experimental campaign yields scale-up fabrication recipes, producing transparent conductive thin films with averaged conductivity exceeding 4500 S/cm. Feature importance analysis and morphological characterizations reveal key design factors. This work signifies a significant step towards transforming the manufacturing of electronic polymers, highlighting the potential of AI-driven automation in material science.

Wang, Chengshi [Argonne National Laboratory (ANL),↗

Data-Driven Discovery of Bimetallic Nanoparticles Catalysts for the Hydrogenolysis of Polyethylene

Supported platinum nanoparticles are known to convert polyolefins to high-quality liquid hydrocarbons with hydrogen under relatively mild conditions. However, no systematic study has been undertaken using bimetallic catalysts for polyethylene upcycling. Specifically, a total of 98 monometallic and bimetallic combinations (Ag, Cr, Co, Cu, Fe, Ga, In, Mn, Ni, Pd, Pt, Rh, Ru, Zr) on alumina were synthesized utilizing surface organometallic chemistry (SOMC) technique via robotic platform. These were investigated at a small scale (10 mg of catalyst and 50 mg of polyethylene) for their activity for the hydrogenolysis of polyethylene in a high-throughput batch reactor. Combinations of Ni and Co were selected as candidates with high activity toward conversion into paraffin oils. Reaction conditions were optimized with Ni/Co/Al 2 O 3 catalyst at a larger scale (300 mg catalyst and 3 g polyethylene) to obtain a high yield (93.1%) of paraffin wax with desired properties (M n = 380 Da) and low polydispersity (Đ = 1.2). Ni/Co/Al 2 O 3 was compared against Co/Ni/Al 2 O 3 to understand the role of the deposition sequence. When Co is deposited before Ni, a layer of cobalt aluminate is formed upon reduction, stabilizing the deposition of 5 nm metallic Ni particles. When nickel is deposited before Co, particles are larger (average >20 nm) and more oxidized (Ni δ+ in NiAl 2 O 4 ), decreasing the availability of the catalytically active metallic Ni. In conclusion, the difference in electronic environments was also described by DFT calculations, which revealed that smaller 3D clusters of Ni are preferred on CoAl2O4 over the 3D clusters on NiAl 2 O 4 and that these smaller clusters are more reducible, as confirmed experimentally.

Polymer↗