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At least 955 records · Page 53

Coupling of NMR to ACOMP for Terpolymerization Monitoring and Control

Abstract Monitoring and control of free radical copolymerization using automatic continuous online monitoring of polymerization reactions (ACOMP) with UV detection has been recently achieved. It is difficult, however, to achieve spectral separation of similar monomers with UV alone. Here, nuclear magnetic resonance (NMR) is coupled to ACOMP for the first time and terpolymerization reactions involving acrylamide (Am), sodium acrylate (Ac), and styrene sulfonate (SS) are monitored, and a first attempt at active composition control is made. The NMR resolves the concentrations of Am and Ac, while the UV resolves SS and the sum of Am and Ac. NMR analysis is performed in water, using signal suppression, to eliminate the need for deuterated solvents. From this, instantaneous fractions of each comonomer in the terpolymer are continuously known, along with weight average molecular weight and intrinsic viscosity, IV. Am and Ac have similar reactivities, whereas the reactivity ratio of SS is much larger. Hence, there is high composition drift in batch polymerization and SS is rapidly consumed, leaving a final copolymer of Am and SS to form. Maintaining constant terpolymer composition is taken as a first step toward active control.

McAfee, Terry↗

Reinforcement learning for real-time process control in high-temperature superconductor manufacturing

With high efficiency and low energy loss, high-temperature superconductors (HTS) have demonstrated their profound applications in various fields, such as medical imaging, transportation, accelerators, microwave devices, and power systems. The high-field applications of HTS tapes have raised the demand for producing cost-effective tapes with long lengths in superconductor manufacturing. However, achieving the uniform and enhanced performance of a long HTS tape is challenging due to the unstable growth conditions in the manufacturing process. Although it is confirmed that the process parameters during the advanced metal organic chemical vapor deposition (A-MOCVD) process influence the uniformity of the produced HTS tapes, the high-dimensional process parameter signals and their complicated interactions make it difficult to develop an effective control policy. In this paper, we propose a local measure for the uniformity of HTS tapes to provide instant feedback for our control policy. Then, we model the manufacturing of HTS tapes as a Markov decision process (MDP) with continuous state and action spaces to assess the instant reward in real time in our feedback control model. As our MDP involves continuous and high-dimensional state and action spaces, a neural fitted Q-iteration (NFQ) algorithm is adopted to solve the MDP with artificial neural network (ANN) function approximation. The collinearity of process parameters can restrict our capability of adjusting the process parameters, which is addressed by the principal component analysis (PCA) in our method. The control policy adjusts the PCA of process parameters using the NFQ algorithm. In conclusion, based on our case studies on real A-MOCVD dataset, the obtained control policy increases the average uniformity of tapes by 5.6% and performs especially well on sample HTS tapes with a low uniformity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Integrated Power Source Grant

Traditional spacecraft power systems incorporate a solar array energy source, an energy storage element (battery), and battery charge control and bus voltage regulation electronics to provide continuous electrical power for spacecraft systems and instruments. Dedicated power conditioning components provide limited fault isolation between systems and instruments, while a centralized power-switching unit provides spacecraft load control. Battery undervoltage conditions are detected by the spacecraft processor, which removes fault conditions and non-critical loads before permanent battery damage can occur. Cost effective operation of a micro-sat constellation requires a fault tolerant spacecraft architecture that minimizes on-orbit operational costs by permitting autonomous reconfiguration in response to unexpected fault conditions. A new micro-sat power system architecture that enhances spacecraft fault tolerance and improves power system survivability by continuously managing the battery charge and discharge processes on a cell-by-cell basis has been developed. This architecture is based on the Integrated Power Source (US patent 5644207), which integrates dual junction solar cells, Lithium Ion battery cells, and processor based charge control electronics into a structural panel that can be deployed or used to form a portion of the outer shell of a micro-spacecraft. The first generation Integrated Power Source is configured as a one inch thick panel in which prismatic Lithium Ion battery cells are arranged in a 3x7 matrix (26VDC) and a 3x1 matrix (3.7VDC) to provide the required output voltages and load currents. A multi-layer structure holds the battery cells, as well as the thermal insulators that are necessary to protect the Lithium Ion battery cells from the extreme temperatures of the solar cell layer. Independent thermal radiators, located on the back of the panel, are dedicated to the solar cell array, the electronics, and the battery cell array. In deployed panel applications, these radiators maintain the battery cells in an appropriate operational temperature range.

Source record↗

Overview of Intelligent Power Controller Development for Human Deep Space Exploration

Intelligent or autonomous control of an entire spacecraft is a major technology that must be developed to enable NASA to meet its human exploration goals. NASA's current long term human space platform, the International Space Station, is in low earth orbit with almost continuous communication with the ground based mission control. This permits the near real-time control by the ground of all of the core systems including power. As NASA moves beyond Low Earth Orbit, the issues of communication time-lag and lack of communication bandwidth beyond geosynchronous orbit does not permit this type of operation. This paper presents the work currently ongoing at NASA to develop an architecture for an autonomous power control system as well as the effort to assemble that controller into the framework of the vehicle mission manager and other subsystem controllers to enable autonomous control of the complete spacecraft. Due to the common problems faced in both space power systems and terrestrial power system, the potential for spin-off applications of this technology for use in micro-grids located at the edge or user end of terrestrial power grids for peak power accommodation and reliability are described.

Space Flight↗

Overview of Intelligent Power Controller Development for Human Deep Space Exploration

Intelligent or autonomous control of an entire spacecraft is a major technology that must be developed to enable NASA to meet its human exploration goals. NASA's current long term human space platform, the International Space Station, is in low Earth orbit with almost continuous communication with the ground based mission control. This permits the near real-time control by the ground of all of the core systems including power. As NASA moves beyond low Earth orbit, the issues of communication time-lag and lack of communication bandwidth beyond geosynchronous orbit does not permit this type of operation. This paper presents the work currently ongoing at NASA to develop an architecture for an autonomous power control system as well as the effort to assemble that controller into the framework of the vehicle mission manager and other subsystem controllers to enable autonomous control of the complete spacecraft. Due to the common problems faced in both space power systems and terrestrial power system, the potential for spin-off applications of this technology for use in micro-grids located at the edge or user end of terrestrial power grids for peak power accommodation and reliability are described.

Space Flight↗

Mycorrhizal associations of temperate forest seedlings mediate rhizodeposition, but not soil carbon storage, under elevated nitrogen availability

Abstract Tree‐mycorrhizal associations are associated with patterns in nitrogen (N) availability and soil organic matter storage; however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)‐ and ectomycorrhizal (EcM)‐associated seedlings alter rhizodeposition in response to increased seedling inorganic N acquisition. We grew four species each of EcM and AM seedlings from forests of the eastern United States in a continuously 13 C‐labeled atmosphere within an environmentally controlled chamber and subjected to three levels of 15 N‐labeled fertilizer. We traced seedling 15 N uptake from, and 13 C‐labeled inputs (net rhizodeposition) into, root‐excluded or ‐included soil over a 5‐month growing season. N uptake by seedlings was positively related to rhizodeposition for EcM‐ but not AM‐associated seedlings in root‐included soils. Despite this contrast in rhizodeposition, there was no difference in soil C storage between mycorrhizal types over the course of the experiment. Instead root‐inclusive soils lost C, while root‐exclusive soils gained C. Our findings suggest that mycorrhizal associations mediate tree belowground C investment in response to inorganic N availability, but these differences do not affect C storage. Continued soil warming and N deposition under global change will increase soil inorganic N availability and our seedling results indicate this could lead to greater belowground C investment by EcM‐associated trees. This potential for less efficient N uptake by EcM‐trees could contribute to AM‐tree success and a shift toward more AM‐dominated temperate forests.

Fitch, Amelia A.↗

Resolving SPARC–HSA binding kinetics with an ultrasensitive photonic sensor based on bound states in the continuum

Secreted protein acidic and rich in cysteine (SPARC) is critical in cell-matrix interactions and tissue remodeling. It influences tumor progression through its affinity for human serum albumin (HSA) - the most abundant plasma protein, which also plays a crucial role in drug delivery. Strong molecular binding leads to a dissociation constant KD in the nanomolar range. Thus, determining KD requires detecting sub-nanomolar concentrations with ultrasensitive methods. This may be crucial for elucidating the nature of SPARC-HSA binding, as their interaction remains a subject of debate. Capturing these interactions accurately requires a platform capable of resolving rapid binding kinetics at extremely low analyte concentrations. In this work, we report on a microfluidics-integrated photonic nanostructure that supports bound states in the continuum (BICs) and is optimized for studying the fast kinetics of high-affinity protein-protein interactions. The unprecedented capability of detecting sub-nanomolar concentrations allows quantifying KD between SPARC and HSA beyond the state of the art. We leverage an all-dielectric photonic crystal slab (PhCS) sustaining two BIC branches arising from gapped Dirac cone dispersion. HSA is covalently immobilized on the PhCS bonded to a PDMS microfluidic chamber. SPARC dissociation is carried out using PBS buffer (pH 7.4), ensuring complete protein release through precise control of the flow rate and continuous spectral monitoring of the BICs. The measured KD=8.2±0.8 nM confirms the strong affinity of SPARC for HSA. This study highlights the potential of BIC-based sensing as a versatile tool for investigating protein interactions. These results also have implications for the optimization of drug delivery systems and cancer treatment strategies.

Albumin↗

Survey of Cyber Risk Analysis Techniques for Use in the Nuclear Industry

Using traditional probabilistic risk analysis methods for severe accident safety risk management on non-digital systems, structures, and components at nuclear power plants is well-established. In contrast, cyber risk analysis of digital assets is still an immature field with unproven techniques due, in part, to the continuously changing threat environment and the challenge of digital assets failing in unexpected ways. As the nuclear fleet continues to adopt digital instrumentation and control systems, it is increasingly important to have effective and efficient cyber risk analysis techniques to support risk management decisions, such as risk elimination by system redesign or risk mitigation by implementation of prioritized security controls. To understand the state of the art in cyber risk analysis for future research, we surveyed 36 publications across ten application domains. We describe our survey methodology and rate each technique based upon scope, adoptability, and repeatability. In this work, we examine the unique constraints of the nuclear industry and outline the strengths and weaknesses of using the cyber risk analysis techniques in the industry, highlighting gaps with current techniques. We also discuss challenges and potential research directions for advancing the science for both existing and new advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Influence of the Laser Scanning Rate on the Structure of Rotating Lattice Single Crystal Lines

Localized controlled heating of glass with a continuous wave laser has introduced the possibility of engineering the lattice of recently discovered rotating lattice single (RLS) crystals and thus obtaining novel metamaterials. On this account, we report the role of the laser scanning speed on the lattice structure of a model system: Sb 2 S 3 straight RLS crystal lines created in a 16SbI 3 -84Sb 2 S 3 glass. The electron backscatter diffraction analysis shows that above a critical laser scanning speed the lattice rotates along the direction of scanning, the rate of lattice rotation is relatively insensitive to scanning speed, and the growth front is symmetric. In contrast, for laser scanning speeds below this critical value, the rate and direction of lattice rotation are strongly affected by the speed. Further, the growth front becomes asymmetric, which promotes the formation of new grains misoriented by ≤10°. These observations are reported on in terms of the relative dominance of the temperature gradient from laser scanning vis-á-vis the intrinsic preferred crystallographic direction of crystal growth. In addition to providing guidelines for fabricating the RLS crystal of the desired rate of the lattice rotation, new insight is gained for the mechanism of plumose formation in spherulitic crystals.

36 MATERIALS SCIENCE↗

Bifunctional Electrocatalysts with High-Entropy Alloys: Bridging Hydrogen Evolution and Oxygen Reduction

High-entropy alloys (HEAs) have emerged as a promising class of bifunctional electrocatalysts capable of simultaneously driving the hydrogen evolution reaction (HER) and the oxygen reduction reaction (ORR) with high activity and durability. Their near-equiatomic multicomponent compositions give rise to unique physicochemical characteristics, including lattice distortion, sluggish diffusion, high-entropy stabilization, and pronounced electronic heterogeneity, that collectively generate diverse and synergistic active sites inaccessible in conventional alloys. This review summarizes recent progress in HEA-based bifunctional electrocatalysis, with a focus on the fundamental mechanisms governing HER and ORR activity, stability, and selectivity. We discuss advances in synthesis strategies, ranging from confined growth and step-alloying to scalable continuous-flow methods, that enable precise control over composition, size, and surface structure. Complementary computational and data-driven approaches, including density functional theory, machine-learning-assisted screening, and descriptor development, are highlighted as essential tools for navigating the vast HEA design space and establishing structure−property relationships. Particular attention is paid to adsorption-energy distributions, multisite cooperativity, and environmental effects under realistic electrochemical conditions. Finally, we outline current challenges and future opportunities for integrating mechanistic understanding with AI-guided, closed-loop design frameworks to accelerate the discovery of next-generation HEA bifunctional electrocatalysts for sustainable energy conversion.

Alloys↗

Transient Lattice Response upon Photoexcitation in CuInSe 2 Nanocrystals with Organic or Inorganic Surface Passivation

CuInSe 2 nanocrystals offer promise for optoelectronics including thin-film photovoltaics and printed electronics. Additive manufacturing methods such as photonic curing controllably sinter particles into quasi-continuous films and offer improved device performance. To gain understanding of nanocrystal response under such processing conditions, we investigate impacts of photoexcitation on colloidal nanocrystal lattices via time-resolved X-ray diffraction. We probe three sizes of particles and two capping ligands (oleylamine and inorganic S 2- ) to evaluate resultant crystal lattice temperature, phase stability, and thermal dissipation. Elevated fluences produce heating and loss of crystallinity, the onset of which exhibits particle size dependence. We find size-dependent recrystallization and cooling lifetimes ranging from 90 to 200 ps with additional slower cooling on the nanosecond time scale. Sulfide-capped nanocrystals show faster recrystallization and cooling compared to oleylamine-capped nanocrystals. Using these lifetimes, we find interfacial thermal conductivities from 3 to 28 MW/(m 2 K), demonstrating that ligand identity strongly influences thermal dissipation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehicles

The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.

33 ADVANCED PROPULSION SYSTEMS↗

Engineering the Spectrum of Dipole Field-Localized Spin-Wave Modes to Enable Spin-Torque Antidamping

Auto-oscillation of a ferromagnet due to spin-orbit torques in response to a dc current is of wide interest as a flexible mechanism for generating controllable high-frequency magnetic dynamics. However, degeneracies of the spin-wave modes and nonlinear magnon-magnon scattering impede coherent precession. Discretization of the spin-wave modes can reduce this scattering. Furthermore, spatial localization of the spin-wave modes by the strongly inhomogeneous dipole magnetic field of a nearby spherical micromagnet provides variable spatial confinement, thus offering the option of systematic tunability of magnon spectrum for studying multimode interactions. Here we demonstrate that field localization generates a discrete spin-wave spectrum observable as a series of well-resolved localized modes in the presence of imposed spin currents arising from the spin Hall effect in a permalloy-platinum (Py/Pt) microstrip. The observation of linewidth reduction through damping control in this micromagnetically engineered spectrum demonstrates that localized modes can be controlled efficiently, an important step toward continuously tunable spin Hall effect–driven auto-oscillators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland

Abstract Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO 2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post‐thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post‐thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO 2 and CH 4 fluxes from decomposition. Thus, the increased C‐storage expected from higher productivity was limited and the high global warming potential of CH 4 contributed a net positive warming effect. Although post‐thaw peatlands are currently C sinks due to high NPP offsetting high CO 2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of Conduction Cooling Strategies for Wire Arc Additive Manufacturing

Metal additive manufacturing (AM) processing consists of numerous parameters which take time to optimize for various geometries. One aspect of the metal AM process that continues to be explored is the control of thermal energy accumulation during component manufacturing due to the melting and solidification of the feedstock. Excessive energy accumulation causes thermal failure of the component while minimal energy accumulation causes lack of fusion with the build plate or previous layer. The ability to simulate the thermal response of an AM component can increase research efficiency by reducing the time to optimize thermal energy accumulation. This paper presents an effective implementation of finite element analysis to determine the thermal response of a wire arc additive manufactured component with various build plate sizes and cooling methods including, integral build plate cooling, oversized build plates with passive cooling, and non-integral build plate cooling. The use of integral build plate cooling channels was shown to decrease the interpass temperature at the conclusion of the build process by 55% and build plate temperature by 96% compared to the conventionally deposited sample with 20 second dwell time. The use of a tall build plate with passive cooling was shown to reduce the interpass temperature by 32% as compared to the conventionally deposited sample with 20 second dwell time. Each cooling strategy evaluated decreased the interpass temperature within a range of 20–55% which enables higher deposition rates and decreased dwell times during depositions. The cooling strategies are designed to be implemented in a hybrid or retrofit AM platform to mitigate concerns of the thermal input from the additive process having detrimental effects on the precision of the machining process. This paper shows that accurate simulations of all strategies can be used to accurately predict the thermal response of the various strategies discussed. These cooling strategies will allow for increased deposition rates with comparable interpass temperature and decreased dwell time, increasing deposition efficiency. This model and these simulations are verified by experimental results. It is concluded that passive strategies, such as the over-sized tall build plate, can be used when liquid coolant in the AM environment could negatively affect the deposition process. Active cooling strategies, such as the integral build plate cooling could be used if low thermal conductivity materials are deposited or higher material deposition rates are desired. This paper discusses the use of active and passive cooling used during AM and shows how a simulation model can be used to make design choices for cooling strategies. The model also enables verification of select critical process parameters such as dwell times for a desired interpass temperature.

Heinrich, Lauren↗

pnnl/pecblocks

ConverterBlocks uses the output of detailed electromagnetic transient (EMT) simulations to produce generalized block diagram models of power electronic systems. The process uses deep learning with customized block architectures. The outputs are reduced-order models that meet specified accuracy requirements, while providing important advantages over the original EMT models: ConverterBlock models have fewer nodes and can take longer time steps, resulting in shorter simulation times ConverterBlock models are continuously differentiable, making them compatible with control design methodsGeneralized block diagram modeling of power electronic converters for grid solar and storage applications.

McDermott, Tom↗

Regional Algal Feedstock Testebed (RAFT) Final Report

The RAFT project completed detailed characterization of 12 twelve potential production strains and extensively tested 3 the three best strains in long term seasonal cultivation trials. A total of x 272 cultivation experiments were completed at the three outdoor testbed locations as part of long term cultivation trials conducted over a three year period. The cultivation experiments tested various harvest strategies, crop protection strategies, and seasonal effects along with strain rotation strategies. A sensor, that continuously monitors cell density, was developed and a patent application was submitted. Models were develop and validated for predicting strain performance, determining biomass productivity, evaluating cultivation system design and operations, and evaluating large scale production scenarios. A detailed data base was established for the long term cultivation trials with discrete data from the x 272 testbed cultivation experiments. This data base will be maintained at the University of Arizona https://raft.arizona.edu/cultivation-data/ for public access and continued academic evaluations.

09 BIOMASS FUELS↗