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In this work the rapid alloy selection and subsequent processability via additive manufacturing of nickelbased superalloys was investigated. Rapid alloy selection protocols developed within the project produced two viable nickel-based superalloys. This phase I CRADA demonstrates a viable route for selecting new nickel-based superalloys for additive manufacturing.
In this work the rapid alloy selection and subsequent processability via additive manufacturing of nickelbased superalloys was investigated. Rapid alloy selection protocols developed within the project produced two viable nickel-based superalloys. This phase I CRADA demonstrates a viable route for selecting new nickel-based superalloys for additive manufacturing.
Performance of applications in production environments can he sensitive to network congestion. Cray Aries supports adaptively routing each network packet independently based on the load or congestion encountered as a packet traverses the network. Software can dictate different routing policies, adjusting between minimal and non-minimal bias, for each posted message. We have extensively evaluated the sensitivity of the routing bias selection on application performance as well as whole system performance in both production and controlled conditions. We show that the default routing bias used in Aries-based systems is often sub-optimal and that using a higher bias towards minimal routes will not only reduce the congestion effects on the application but also will decrease the overall congestion on the network. This routing scheme results in not only improved mean performance (by up to 12%) of most production applications hut also reduced run-to-run variability. Our study prompted the two supercomputing facilities (ALCF and NERSC) to change the default routing mode on their Aries-based systems. We present the substantial improvement measured in the overall congestion management and interconnect performance in production after making this change.
Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology of scheduled communication contacts in a network based on the DTN (Delay-Tolerant Networking) architecture. It is designed to enable dynamic selection of data transmission routes in a space network based on DTN. This dynamic responsiveness in route computation should be significantly more effective and less expensive than static routing, increasing total data return while at the same time reducing mission operations cost and risk. The basic strategy of CGR is to take advantage of the fact that, since flight mission communication operations are planned in detail, the communication routes between any pair of bundle agents in a population of nodes that have all been informed of one another's plans can be inferred from those plans rather than discovered via dialogue (which is impractical over long one-way-light-time space links). Messages that convey this planning information are used to construct contact graphs (time-varying models of network connectivity) from which CGR automatically computes efficient routes for bundles. Automatic route selection increases the flexibility and resilience of the space network, simplifying cross-support and reducing mission management costs. Note that there are no routing tables in Contact Graph Routing. The best route for a bundle destined for a given node may routinely be different from the best route for a different bundle destined for the same node, depending on bundle priority, bundle expiration time, and changes in the current lengths of transmission queues for neighboring nodes; routes must be computed individually for each bundle, from the Bundle Protocol agent's current network connectivity model for the bundle s destination node (the contact graph). Clearly this places a premium on optimizing the implementation of the route computation algorithm. The scalability of CGR to very large networks remains a research topic. The information carried by CGR contact plan messages is useful not only for dynamic route computation, but also for the implementation of rate control, congestion forecasting, transmission episode initiation and termination, timeout interval computation, and retransmission timer suspension and resumption.
A data-informed model to predict energy use for a proposed vehicle trip has been developed in this paper. The methodology leverages roughly one million miles of real-world driving data to generate the estimation model. Driving is categorized at the sub-trip level by average speed, road gradient, and road network geometry, then aggregated by category. An average energy consumption rate is determined for each category, creating an energy rate look-up table. Proposed vehicle trips are then categorized in the same manner, and estimated energy rates are appended from the look-up table. The methodology is robust and applicable to a wide range of driving data. The model has been trained on vehicle travel profiles from the Transportation Secure Data Center at the National Renewable Energy Laboratory and validated against on-road fuel consumption data from testing in Phoenix, Arizona. When compared against the detailed on-road conventional vehicle fuel consumption test data, the energy estimation model accurately predicted which route would consume less fuel over a dozen different tests. When compared against a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology should accurately select the route that consumes the least fuel 90% of the time. The model results can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations to reduce energy consumption. This work provides a highly extensible framework that allows the model to be tuned to a specific driver or vehicle type.
The Department of Energy (DOE) has a historic programmatic interest in the safe and secure routing, tracking, and transportation risk analysis of radiological materials in the United States. In order to address these program goals, DOE has funded the development of several tools and related systems designed to provide insight to planners and other professionals handling radioactive materials shipments. These systems include the WebTRAGIS (Transportation Routing Analysis Geographic Information System) platform. WebTRAGIS is a browser-based routing application developed at Oak Ridge National Laboratory (ORNL) focused primarily on the safe transport of spent nuclear fuel from US nuclear reactors via railway, highway, or waterway. It is also used for the transport planning of low-level radiological waste to depositories such as the Waste Isolation Pilot Plant (WIPP) facility. One particular feature of WebTRAGIS is its coupling with high-resolution population data from ORNL s LandScan project. This allows users to obtain highly accurate population count and density information for use in route planning and risk analysis. To perform the routing and risk analysis WebTRAGIS incorporates a basic routing model methodology, with the additional application of various constraints designed to mimic US Department of Transportation (DOT), DOE, and Nuclear Regulatory Commission (NRC) regulations. Aside from the routing models available in WebTRAGIS, the system relies on detailed or specialized modal networks for the route solutions. These include a highly detailed network model of the US railroad system, the inland and coastal waterways, and a specialized highway network that focuses on the US interstate system and the designated hazardous materials and Highway Route Controlled Quantity (HRCQ) -designated roadways. The route constraints in WebTRAGIS rely upon a series of attributes assigned to the various components of the different modal networks. Routes are determined via a constrained shortest-path Dijkstra algorithm that has an assigned impedance factor. The route constraints modify the various impedance weights to bias or prefer particular network characteristics as desired by the user. Both the basic route model and the constrained impedance function calculations are determined by a series of network characteristics and shipment types. The study examines solutions under various constraints modeled by WebTRAGIS including possible routes from select shut-down reactor sites in the US to specific locations in the US. For purposes of illustration, the designated destinations are Oak Ridge National Laboratory in Tennessee and the Savannah River Site in South Carolina. To the degree that routes express sameness or variety under constraints serves to illustrate either a) the determinism of particular transport modes by either configuration or regulatory compliance, and/or b) the variety of constrained routes that are regulation compliant but may not be operationally feasible.
This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed model is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.
The inertness of the C–H bond in CH 4 poses significant challenges to selective CH 4 oxidation, which often proceeds all the way to CO 2 once activated. Selective oxidation of CH 4 to high-value industrial chemicals such as CO or CH 3 OH remains a challenge. Presently, the main methods to activate CH 4 oxidation include thermochemical, electrochemical, and photocatalytic reactions. Of them, photocatalytic reactions hold great promise for practical applications but have been poorly studied. Existing demonstrations of photocatalytic CH 4 oxidation exhibit limited control over the product selectivity, with CO 2 as the most common product. The yield of CO or other hydrocarbons is too low to be of any practical value. In this work, we show that highly selective production of CO by CH4 oxidation can be achieved by a photoelectrochemical (PEC) approach. Under our experimental conditions, the highest yield for CO production was 81.9%. The substrate we used was TiO 2 grown by atomic layer deposition (ALD), which features high concentrations of Ti 3+ species. The selectivity toward CO was found to be highly sensitive to the substrate types, with significantly lower yield on P25 or commercial anatase TiO 2 substrates. Moreover, our results revealed that the selectivity toward CO also depends on the applied potentials. Based on the experimental results, we proposed a reaction mechanism that involves synergistic effects by adjacent Ti sites on TiO 2 . Spectroscopic characterization and computational studies provide critical evidence to support the mechanism. Furthermore, the synergistic effect was found to parallel heterogeneous CO 2 reduction mechanisms. Our results not only present a new route to selective CH 4 oxidation, but also highlight the importance of mechanistic understandings in advancing heterogeneous catalysis.
The activation of dioxygen at typically isolated two-electron reduced centers can lead to the formation of electrophilic superoxo or peroxo species, providing an essential route to form reactive O 2 -derived species in biological, organometallic, and heterogeneous catalysts. Alternatively, O 2 activation can proceed via outer sphere routes, circumventing the formation of bound peroxo (OO*) species during oxidation catalysis by forming H 2 O 2 (g), which can react with another reduced center to form H 2 O. The electronic and binding properties of metal oxides that determine the relative rates of these activation routes are assessed here by systematic theoretical treatments using density functional theory (DFT). These methods are combined with conceptual frameworks based on thermochemical cycles and crossing potential models to assess the most appropriate descriptors for the activation barriers for each route using Keggin polyoxometalates as illustrative examples. In doing so, we show that inner sphere routes, which form OO* species via O 2 activation on the O-vacancies (*) formed in the reduction part of redox cycles, are mediated by early transition states that only weakly sense the oxide binding properties. Outer sphere routes form H 2 O 2 (g) via O 2 activation on OH pairs (H/OH*) formed by dissociation of H 2 O on O-vacancies; their rates and activation barriers reflect the rates of the first H-atom transfer from H/OH* to O 2 . The activation barriers for this H-transfer step depend on the binding energy of more weakly-bound H-atom in H/OH* pairs (HAE 2 ) and on the ˙OOH-surface interaction energy at its product state ($E_{int}$ 0 ). The $E_{int}$ 0 values are similar among oxides unless a large charge-balancing cation is present and interacts with radical ˙OOH; consequently, HAE 2 acts as an appropriate descriptor of the outer sphere dynamics. HAE 2 also determines the thermodynamics of H 2 O dissociation on O-vacancies, which influence the inner and outer sphere rates by setting the relative coverage of * and H/OH*. So these results, in turn, show that HAE 2 is a complete descriptor of the reactivity and selectivity of oxides for O 2 activation; the O-atoms in more reducible oxides (more negative HAE 2 ) exhibit a greater preference for the inner sphere routes and for the formation of electrophilic OO* intermediates that mediate epoxidation and O-insertion reactions during catalytic redox cycles. Large charge-balancing cations locally modify $E_{int}$ 0 values that determine the outer sphere rates and thus can be used to alter the preference of O-atoms to either inner or outer sphere routes.
A dire need for real-time detection of toxic chemical compounds exists in both civilian and military spheres. In this paper, we demonstrate that inexpensive, commercially available Fe 2 O 3 nanoparticles are capable of selective sensing of chemical warfare agents (CWAs) using frequency-dependent impedance spectroscopy, with additional potential as an orthogonal magnetic sensor. X-ray magnetic circular dichroism analysis shows that Fe 2 O 3 nanoparticles possess moderately lowered moment upon exposure to 2-chloroethyl ethyl sulfide (2-CEES) and diisopropyl methylphosphonate (DIMP) and significantly lowered moment upon exposure to dimethyl methylphosphonate (DMMP) and dimethyl chlorophosphate (DMCP). Associated X-ray absorption spectra confirm a redox reaction in the Fe 2 O 3 nanoparticles due to CWA structural analog exposure, with differentiable energy-dependent features that suggest selective sensing is possible, given the correct method. Impedance spectroscopy performed on samples dosed with DMMP, DMCP, and tabun (GA, chemical warfare nerve agent) showed strong, differentiable, frequency-dependent responses. The frequency profiles provide unique “shift fingerprints” with which high specificity can be determined, even amongst similar analytes. The results suggest that frequency-dependent impedance fingerprinting using commercially available Fe 2 O 3 nanoparticles as a sensor material is a feasible route to selective detection.
LaserSnake2, a UK collaborative project, seeks to deliver remotely operated cutting techniques into high hazard nuclear environments. This paper describes the developments and results of combining proven robotic manipulators with high-powered laser cutting tools, to allow for selective dismantling within complex nuclear process cells. Decommissioning old and poorly catalogued nuclear plant is a problem faced the world over. Designed with little consideration for decommissioning, or adapted significantly from the original drawings, legacy plant and infrastructure is full of spaces where it is undesirable or impossible to send people. Typically, a process cell or cave will require modification to ensure suitability for human entry or deployment of heavy duty equipment to complete the decontamination processes. The process of widening access routes, or selectively moving sections of highly contaminated material, is ideally suited to remote handling technology. The results of TWI's research into fibre-delivered laser cutting techniques, and integration with a dexterous snake-arm robot, are presented. Coupled with novel laser process head design and diffractive optical elements, the result is an integrated system capable of cutting up to 100 mm thick C-Mn steel plate at significant stand-off distances, encompassing the range of infrastructure found in a typical nuclear plant. Two options have been considered for deployment of the laser cutting tool. The first is focused on a fixed installation using a standard industrial robot. The second is a large, highly flexible snake-arm robot capable of entering cluttered cells through existing penetrations. Designed to operate through a standard 11'' MSM port, the 4.5 m snake-arm robot has the capacity to carry grippers, sensors or the laser cutting tool at the tip. The snake-arm is sealed and housed within a glove box for contamination control, allowing operation within a radioactive environment. Significant technical developments and material research are presented which have led to improved operational life, payload and bend. This paper describes the series of inactive trials which have been conducted to demonstrate the LaserSnake2 system's capabilities. These include: horizontal and vertical deployment, underwater operation, object manipulation and laser cutting. With global nuclear decommissioning costs running in to the $trillions, safe and cost efficient tools such as the LaserSnake2 system are essential as part of the decommissioning toolbox. Remote handling can account for up to 20% of a decommissioning project's costs, however significant time and financial savings can be made by utilising this new technology to reduce operator exposure and reach previously inaccessible areas. (authors)
In a platoon, vehicles travel one after another with small intervehicle distances; trailing vehicles in a platoon save fuel because they experience less aerodynamic drag. This work presents a coordinated platooning model with multiple speed options that integrates scheduling, routing, speed selection, and platoon formation/dissolution in a mixed-integer linear program that minimizes the total fuel consumed by a set of vehicles while traveling between their respective origins and destinations. The performance of this model is numerically tested on a grid network and the Chicago-area highway network. We find that the fuel-savings factor of a multivehicle system significantly depends on the time each vehicle is allowed to stay in the network; this time affects vehicles’ available speed choices, possible routes, and the amount of time for coordinating platoon formation. For problem instances with a large number of vehicles, we propose and test a heuristic decomposed approach that applies a clustering algorithm to partition the set of vehicles and then routes each group separately. When the set of vehicles is large and the available computational time is small, the decomposed approach finds significantly better solutions than does the full model.
The efficient biological production of industrially and economically important compounds is a challenging problem. Brute-force determination of the optimal pathways to efficient production of a target chemical in a chassis organism is computationally intractable. Many current methods provide a single solution to this problem, but fail to provide all optimal pathways, optional sub-optimal solutions or hybrid biological/non-biological solutions. Here we present RetSynth, software with a novel algorithm for determining all optimal biological pathways given a starting biological chassis and target chemical. By dynamically selecting constraints, the number of potential pathways scales by the number of fully independent pathways and not by the number of overall reactions or size of the metabolic network. This feature allows all optimal pathways to be determined for a large number of chemicals and for a large corpus of potential chassis organisms. Additionally, this software contains other features including the ability to collect data from metabolic repositories, perform flux balance analysis, and to view optimal pathways identified by our algorithm using a built-in visualization module. This software also identifies sub-optimal pathways and allows incorporation of non-biological chemical reactions, which may be performed after metabolic production of precursor molecules. The novel algorithm designed for RetSynth streamlines an arduous and complex process in metabolic engineering. Our stand-alone software allows the identification of candidate optimal and additional sub-optimal pathways, and provides the user with necessary ranking criteria such as target yield to decide which route to select for target production. Furthermore, the ability to incorporate non-biological reactions into the final steps allows determination of pathways to production for targets that cannot be solely produced biologically. With this comprehensive suite of features RetSynth exceeds any open-source software or webservice currently available for identifying optimal pathways for target production.
The development of a decision support tool (DST) for the en-route domain with accurate conflict prediction time horizons of 20 minutes has introduced an interesting problem. A 20 minute time horizon for conflict prediction often results in the predicted conflict occurring one or more sectors downstream from the sector controller who "owns" (i-e., is responsible for the safe separation of aircraft) one or both of the aircraft in the conflict pair. Based on current roles and responsibilities of today's en route controllers, the upstream controller would not resolve this conflict. In most cases, the downstream controller would wait until the conflicting aircraft entered higher sector before resolving the conflict. This results in a delay of several minutes from the time when the conflict was initially predicted. This delay is inefficient from both a controller workload and user's cost of operations perspective. Trajectory orientation, a new concept for facilitating an efficient, conflict-free flight path across several sectors while conforming to metering or miles-in-trail spacing, is proposed as an alternative to today's sector-oriented method. This concept necessitates a fundamental shift in thinking about inter-sector coordination. Instead of operating independently, with the main focus on protecting their internal airspace, controllers would work cooperatively, depending on each other for well-planned, conflict-free flow of aircraft. To support the trajectory orientation concept, a long time horizon (15 to 20 minutes) for conflict prediction and resolution would most likely be a primary requirement. In addition, new tools, such as controller-pilot data link will be identified to determine their necessity and applicability for trajectory orientation. Finally, with significant controller participation from selected Air Route Traffic Control Centers, potential shifts in R-side/D-side roles and responsibilities as well as the creation of a new controller position for multi-sector planning will be examined to determine the most viable solutions.
Jahn–Teller polarons are quasiparticles that stem from symmetry breaking and strong local electron–phonon coupling. They originate from an excess charge carrier being dressed by a local lattice distortion, caused by the Jahn–Teller effect, and they critically impact electrical, structural, and magnetic properties in transition metal oxides. The observation of the microscopic steps involved in their formation is essential for enabling control over material properties through the targeted activation of local, site-specific modifications with light pulses. While Jahn–Teller distortion associated with polaron formation was predicted to contribute significantly to changes in electronic band gap and optical properties in Co 3 O 4 , its experimental observation remains elusive, requiring signatures of local symmetry reduction. In this work, we demonstrate Jahn–Teller polaron formation in spinel Co 3 O 4 . By exciting electronic transitions at 3.10 eV and 1.55 eV, we target either the Oh Cobalt(III) or the Td Cobalt(II) ions, and drive the subsequent coherent responses of the system through two different pathways. For the former, we demonstrate that ligand-to-metal charge transfer leads to Jahn–Teller polaron formation, which is linked to the deformation potential and magnetoelastic coupling. For the latter, we identify the coherent excitation of a T 2g phonon mode launched by on-site d-d electronic transitions. Key to our observations is the ability to target site-specific electronic excitations in spinel Co 3 O 4 using ultrafast optical pulses, while monitoring the ensuing low-energy collective modes through the coherent time-domain response of the material. Our approach, which combines the comparative analysis of experimental fingerprints with the support from density functional theory calculations, is broadly applicable to systems in which Jahn–Teller polaron physics has been theoretically predicted but remains experimentally unverified, and it underscores the potential of electronic-state targeting as a route to selectively excite and probe quasiparticle dynamics in solids.
Abstract This current research progress on the fabrication of hollow nanostructures by using self‐templating methods is reviewed. After a brief introduction to the unique properties and applications of hollow nanostructures and the three general fabrication routes, the discussions are focused on the five main self‐templating strategies, including galvanic replacement, the Kirkendall effect, Ostwald ripening, dissolution–regrowth, and the surface‐protected hollowing process. Some newly developed synthetic routes are selected and discussed in detail. In conclusion, a summary and the perspectives on the directions that might lead the future development of this exciting field are presented.
Textile waste, dominated by polyester-cotton blends, largely evades recycling and ends up in landfills or incinerators. Here, we demonstrate an aqueous ionic liquid–mediated route for selective depolymerization of textile waste, including polyester and polycotton (polyester/cotton blend). Using aqueous cholinium lysinate ([Ch][Lys]), we depolymerized poly(ethylene terephthalate) (PET) textiles with over 95 % terephthalic acid (TPA) yields, comparable to virgin PET resin. Notably, colored fabrics showed no inhibitory effect from dyes. While protic ionic liquids such as ethanolammonium acetate showed limited efficiency, their precursor amine enabled near-complete PET conversion—ethanolamine promoted aminolysis with byproduct formation whereas butylamine achieved higher TPA recovery through combined hydrolysis and aminolysis. Importantly, polycotton blends achieved complete PET depolymerization with TPA yield above 85 % and preserved cotton. These results establish aqueous ionic liquids as efficient, selective agents for deconstructing polyester in blended textiles, offering flexible product and ionic liquid management pathways toward scalable and facile textile recycling.
Hydrotalcites (HTCs) exhibit multiple adjustable parameters to tune catalytic activity, including interlayer anion composition, metal hydroxide layer composition, and catalyst preparation methods. Here in this paper, we report the influence of several of these parameters on β-O-4 bond scission in a lignin model dimer, 2-phenoxy-1-phenethanol (PE), to yield phenol and acetophenone. We find that the presence of both basic and NO 3 – anions in the interlayer increases the catalyst activity by 2–3-fold. In contrast, other anions or transition metals do not enhance catalytic activity in comparison to blank HTC. The catalyst is not active for C–C bond cleavage on lignin model dimers and has no effect on dimers without an α-OH group. Most importantly, the catalyst is highly active in the depolymerization of two process-relevant lignin substrates, producing a significant amount of low-molecular-weight aromatic species. The catalyst can be recycled until the NO 3 – anions are depleted, after which the activity can be restored by replenishing the NO 3 – reservoir and regenerating the hydrated HTC structure. These results demonstrate a route to selective lignin depolymerization in a heterogeneous system with an inexpensive, earth-abundant, commercially relevant, and easily regenerated catalyst.