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At least 1,621 records · Page 90

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DOE OSTI2021

Role of the ionic environment in enhancing the activity of reacting molecules in zeolite pores

Tailoring the molecular environment around catalytically active site allows the enhancement of catalytic reactivity via a hitherto unexplored pathway. In zeolites, the presence of water creates an ionic environment via the formation of hydrated hydronium ions and the negatively charged framework Al tetrahedra. The high density of cation-anion pairs determined by the aluminum concentration of a zeolite induces a high local ionic strength that increases the excess chemical potential of sorbed and uncharged organic reactants. Charged transition states (as for example, the carbenium ions in the discussed alcohol dehydration) are stabilized, reducing the energy barrier and leading to a higher reaction rate. Using the intramolecular dehydration of cyclohexanol on H-MFI in water, we show quantitatively the enhancement of the reaction rate by the presence of high ionic strength as well as potential limitations of this strategy. The approach opens a new pathway to systematically enhance catalytic reactivity rates and has wide-ranging implications for understanding catalysis in condensed phase.

Pfriem, Niklas↗

NASA NTRS2013

Why Is the Overheating Problem Difficult: the Role of Entropy

The development of computational fluid dynamics over the last few decades has yielded enormous successes and capabilities being routinely employed today; however there remain some open problems to be properly resolved-some are fundamental in nature and some resolvable by operational changes. These two categories are distinguished and broadly explored previously. One, that belongs to the former, is the so-called overheating problem, especially in rarefying flow. This problem up to date still dogs every method known to the author; a solution to it remains elusive. The study in this paper concludes that: (1) the entropy increase is quantitatively linked to the increase in the temperature increase, (2) it is argued that the overheating is inevitable in the current shock capturing or traditional finite difference framework, and (3) a simple hybrid method is proposed that removes the overheating problem in the rarefying problems, but also retains the property of accurate shock capturing. This remedy (enhancement of current numerical methods) can be included easily in the present Eulerian codes.

Liou, Meng-Sing↗

DOE OSTI2023

Leaf angle as a leaf and canopy trait: Rejuvenating its role in ecology with new technology

Abstract Life on Earth depends on the conversion of solar energy to chemical energy by plants through photosynthesis. A fundamental challenge in optimizing photosynthesis is to adjust leaf angles to efficiently use the intercepted sunlight under the constraints of heat stress, water loss and competition. Despite the importance of leaf angle, until recently, we have lacked data and frameworks to describe and predict leaf angle dynamics and their impacts on leaves to the globe. We review the role of leaf angle in studies of ecophysiology, ecosystem ecology and earth system science, and highlight the essential yet understudied role of leaf angle as an ecological strategy to regulate plant carbon–water–energy nexus and to bridge leaf, canopy and earth system processes. Using two models, we show that leaf angle variations have significant impacts on not only canopy‐scale photosynthesis, energy balance and water use efficiency but also light competition within the forest canopy. New techniques to measure leaf angles are emerging, opening opportunities to understand the rarely‐measured intraspecific, interspecific, seasonal and interannual variations of leaf angles and their implications to plant biology and earth system science. We conclude by proposing three directions for future research.

Yang, Xi↗

DOE OSTI2026

Bio-Inspired Energy-Efficient Nanofabricated Electrical Contacts

Nanoscale electrical contacts, especially those between materials of dissimilar electronic properties, often represent one of the main causes of drops in energy transfer efficiency. They are also among the sources of above-threshold noise, and their performance often decreases over the lifetime of the nanodevices. Scale-down limitations from mesoscopic to nanoscale devices, and likewise, of nanoscale to quantum-scale devices are also impeded by contacts’ quality. Making more reliable, energy-efficient electrical contacts is among the goals of the nanoelectronics research within the framework of energy-efficient electronic systems. This report focuses on the design, nanofabrication, and testing of novel shapes of electrical contacts. Lithography and nanofabrication were utilized to mimic the approximate shape of insect setae for mesoscale contacts design. The contacts are tested for elementary charge transport via I–V curves and for the broadband, 1/f noise. Tests show that contacts design leads to a measurable decrease in the energy necessary to operate a contact as a switch by at least 12–20%, depending on temperature, while broadband noise shows measurably lower power spectra, for bio-inspired contacts. The proposed method is open to modifications and improvements as required by various on-chip applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Self–Healing and Stretchable Molecular Ferroelectrics with High Expandability

The interplay between crystal ordering and stretchability is frequently encountered in contemporary materials science, particularly in the case of ferroelectrics. The inherent dilemma arises when these materials need to withstand repetitive mechanical deformations or stretching without sacrificing their crystal integrity, all while retaining their remarkable ferroelectric properties and even exhibiting self-healing capabilities. This complexity further presents a significant challenge in the design and engineering of mechanically rigid molecular ferroelectric crystals, particularly for applications where both precise crystalline structure and mechanical adaptability are crucial. In this study, the humidity-controlled expansion and contraction, dissolution, and recrystallization of a self-assembled molecular ferroelectric-in-hydrogel framework are reported. Self-healing ferroelectric-in-hydrogel networks exhibit a recyclable humidity-tailored ionic conductivity from 2.86 × 10 –6 to 1.36 × 10 –5 S cm –1 , facilitating the stretchable piezoelectric sensing. Additionally, the dynamic bond reforming interactions are observed, leading to the tailoring of Young's modulus from 452 to 170 MPa, maintaining ferroelectricity under a strain of 20% with a piezoelectric coefficient of 15.7 pC N –1 . Upon lattice contraction, the molecular contacts undergo reforming, leading to the restoration of stretchable ferroelectrics/piezoelectrics and paving the way for stretchable bioelectronics for full-body motion monitoring. The capabilities highlighted here open avenues for stretchable and self-healing ferroelectric-in-hydrogel bioelectronic technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Unique Conductivity Behavior in Water-In-Salt Electrolytes Driven by Ion Clusters

Understanding and predicting ion transport in aqueous electrolytes are crucial for advanced energy storage and biophysics, and many emergent technologies yet remain elusive. Herein, we introduce a unified framework to quantitatively describe and predict electrolyte conductivity that shifts from conventional molar concentration-based metrics to a volume fraction-based approach. Through analyzing a variety of electrolyte solutions via this perspective, we observe a universal conductivity peak at a 37% volume fraction. Small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations reveal that nanometer-scale ion clusters drive this general behavior. Moreover, key geometric features of the ion transport pathwayssuch as pore size, tortuosity, and connectivityfollow a consistent dependence with respect to the volume fraction, reinforcing the argument for the universal conductivity trend. This paradigm shift opens new avenues for designing high-performance electrolytes and provides transformative insights for advancing studies in many fields, wherein molecular aggregates dictate transport properties.

Nguyen, Huong T. D.↗

DOE OSTI2022

Phase transformation and electrochemical charge storage properties of vanadium oxide/carbon composite electrodes synthesized via integration with dopamine

Abstract Chemically preintercalated dopamine (DOPA) molecules were used as both a reducing agent and a carbon precursor to prepare δ‐V 2 O 5 · n H 2 O/C, H 2 V 3 O 8 /C, VO 2 (B)/C, and V 2 O 3 /C nanocomposites via hydrothermal treatment or hydrothermal treatment followed by annealing under Ar flow. We found that the phase composition and morphology of the produced composites are influenced by the DOPA:V 2 O 5 ratio used to synthesize (DOPA) x V 2 O 5 precursors through DOPA diffusion into the interlayer region of the δ‐V 2 O 5 · n H 2 O framework. The increase of DOPA concentration in the reaction mixture led to a more pronounced reduction of vanadium and a higher fraction of carbon in the composites’ structure, as evidenced by X‐ray photoelectron spectroscopy and Raman spectroscopy measurements. The electrochemical charge storage properties of the synthesized nanocomposites were evaluated in Li‐ion cells with nonaqueous electrolytes. δ‐V 2 O 5 · n H 2 O/C, H 2 V 3 O 8 /C, VO 2 (B)/C, and V 2 O 3 /C electrodes delivered high initial capacities of 214, 252, 279, and 637 mAh g –1 , respectively. The insights provided by this investigation open up the possibility of creating new nanocomposite oxide/carbon electrodes for a variety of applications, such as energy storage, sensing, and electrochromic devices.

Materials Science↗

DOE OSTI2020

Parity- and Time-Reversal-Violating Nuclear Forces

Parity-violating and time-reversal conserving (PVTC) and parity-violating and time-reversal-violating (PVTV) forces in nuclei form only a tiny component of the total interaction between nucleons. The study of these tiny forces can nevertheless be of extreme interest because they allow one to obtain information on fundamental symmetries using nuclear systems. The PVTC interaction derives from the weak interaction between the quarks inside nucleons and nuclei, therefore the study of PVTC effects opens a window on the quark-quark weak interaction. The PVTV interaction is sensitive to more exotic interactions at the fundamental level, in particular to strong CP violation in the Standard Model Lagrangian, or even to exotic phenomena predicted in various beyond-the-Standard-Model scenarios. The presence of these interactions can be revealed either by studying various asymmetries in polarized scattering of nuclear systems, or by measuring the presence of non-vanishing permanent electric dipole moments of nucleons, nuclei and diamagnetic atoms and molecules. In this contribution, we review the derivation of the nuclear PVTC and PVTV interactions within various frameworks. We focus in particular on the application of chiral effective field theory, which allows for a more strict connection with the fundamental interactions at the quark level. We investigate PVTC and PVTV effects induced by these potentials on several few-nucleon observables, such as the longitudinal asymmetries in proton-proton scattering and the 3 He($\vec{n}$,p) 3 H reaction, the radiative neutron-proton capture, and the electric dipole moments of the deuteron and the trinucleon system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

Untethered soft robots that locomote using electrothermally-responsive materials like shape memory alloy (SMA) face challenging design constraints for sensing actuator states. At the same time, modeling of actuator behaviors faces steep challenges, even with available sensor data, due to complex electrical-thermal-mechanical interactions and hysteresis. This article proposes a framework for in-situ sensing and dynamics modeling of actuator states, particularly temperature of SMA wires, which is used to predict robot motions. A planar soft limb is developed, actuated by a pair of SMA coils, that includes compact and robust sensors for temperature and angular deflection. Data from these sensors are used to train a neural network-based on the long short-term memory (LSTM) architecture to model both unidirectional (single SMA) and bidirectional (both SMAs) motion. Predictions from the model demonstrate that data from the temperature sensor, combined with control inputs, allow for dynamics predictions over extraordinarily long open-loop timescales (10 min) with little drift. Prediction errors are on the order of the soft deflection sensor’s accuracy. This architecture allows for compact designs of electrothermally-actuated soft robots that include sensing sufficient for motion predictions, helping to bring these robots into practical application.

Sabelhaus, Andrew P.↗

DOE OSTI2026

Transient uncertainty quantification and Global Sensitivity Analysis of the open-source Molten Chloride Reactor Experiment (MCRE) using GP-PCA surrogate models

Uncertainties in the thermophysical properties of molten salts impact both the steady-state and transient behavior of Molten Salt Reactors (MSRs). In this work, we aim to quantify the influence of such uncertainties on the transient operation of the Molten Chloride Reactor Experiment (MCRE), utilizing the open-source specifications provided for this reactor. Seven representative transient scenarios are considered. For each scenario, we evaluate the impact of thermophysical property uncertainties on four key multiphysics model output variables of interest (VoIs): maximum power density, maximum fuel temperature, maximum reflector temperature, and average fuel velocity magnitude. In addition, we perform a Global Sensitivity Analysis (GSA) by computing Sobol’ indices for the uncertain input parameters to determine their contribution to the variability of each VoI. Conducting GSA is computationally intensive due to the large number of required evaluations of the high-fidelity multiphysics model. To mitigate this cost, we develop a surrogate modeling framework that combines Gaussian Process (GP) regression with Principal Component Analysis (PCA), enabling efficient sample generation for the GSA. Our results show that for energy-related VoIs, thermal conductivity is the dominant contributor to uncertainty. In contrast, for flow-related VoIs, density and dynamic viscosity are the primary sources of uncertainty. The specific heat of the fuel salt was found to play a secondary role in the transient analyses.

42 - ENGINEERING↗

DOE OSTI2023

Investigating the Unique Ability of Trichodesmium To Fix Carbon and Nitrogen Simultaneously Using MiMoSA

The open ocean is an extremely competitive environment, partially due to the dearth of nutrients. Trichodesmium erythraeum, a marine diazotrophic cyanobacterium, is a keystone species in the ocean due to its ability to fix nitrogen and leak 30 to 50% into the surrounding environment, providing a valuable source of a necessary macronutrient to other species. While there are other diazotrophic cyanobacteria that play an important role in the marine nitrogen cycle, Trichodesmium is unique in its ability to fix both carbon and nitrogen simultaneously during the day without the use of specialized cells called heterocysts to protect nitrogenase from oxygen. Here, we use the advanced modeling framework called multiscale multiobjective systems analysis (MiMoSA) to investigate how Trichodesmium erythraeum can reduce dimolecular nitrogen to ammonium in the presence of oxygen. Our simulations indicate that nitrogenase inhibition is best modeled as Michealis-Menten competitive inhibition and that cells along the filament maintain microaerobia using high flux through Mehler reactions in order to protect nitrogenase from oxygen. We also examined the effect of location on metabolic flux and found that cells at the end of filaments operate in distinctly different metabolic modes than internal cells despite both operating in a photoautotrophic mode. These results give us important insight into how this species is able to operate photosynthesis and nitrogen fixation simultaneously, giving it a distinct advantage over other diazotrophic cyanobacteria because they can harvest light directly to fuel the energy demand of nitrogen fixation.

09 BIOMASS FUELS↗

DOE OSTI2024

Enhancements and Deployment of the TDAQ System for the Mu2e Experiment

The Real Time Processing Systems Division at Fermilab has deployed new features to the Off-The-Shelf Data Acquisition framework (otsdaq) for the Mu2e experiment. The Mu2e experiment will search for the coherent neutrino-less conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement of 10,000 times over existing limits. Such a charged lepton flavor-violating reaction probes new physics at a scale unavailable at present or planned high-energy colliders. The Mu2e Trigger and Data Acquisition (TDAQ) system uses otsdaq as its online Data Acquisition System (DAQ) framework. otsdaq integrates the artdaq and art frameworks for event transfer, filtering, and processing. otsdaq is a web-based DAQ software suite focusing on flexibility and scalability and provides a multi-user interface accessible through a web browser. artdaq handles the entire data stream, which is read over the peripheral component interconnect express (PCIe) bus to a software filter algorithm that selects events combined with the data flux coming from a cosmic-ray veto (CRV) system. Detector front-ends are configured through the PCIe bus by customized otsdaq plugins. The otsdaq slow controls infrastructure has been further developed using the experimental physics and industrial control system (EPICS) open-source platform for monitoring, controlling, alarming, and archiving. The detector control system (DCS) for Mu2e has been integrated into otsdaq. The production TDAQ and DCS system has been deployed at the experimental hall and is being debugged and optimized for experiment operations. We report on the feature enhancements and deployment of otsdaq for Mu2e.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1998

A Formal Approach for Designing and Evaluating Procedures

Operator interaction with modern control systems is a topic of great concern in high-risk industries such as nuclear power and commercial aviation. The issues associated with such systems focus on the ability of the operators (e.g., pilots) to achieve mission goals safely while containing failures. Operators must be able to interact safely and reliably with highly automatic and complex systems across the full spectrum of possible operating conditions, including normal, abnormal, and emergency situations. In environments such as commercial aviation, operator interaction with the machine is specified through a set of standard operating procedures (SOP). A procedure represents a collective agreement on the 'best' way to perform a given task. The intent of this paper is to suggest a formal methodology, for designing and evaluating procedures, that is both reliable and systematic. Our approach involves two major elements: a model of the machine and a list of the operator's task specifications (goals). We use formal modeling paradigms for describing the system and super-imposing on it the operator's tasks. Such paradigms, based on recent frameworks such as Statecharts and Hierarchical Hybrid Machines appear to be adequate methods for analyzing operator interaction with modern control systems. To illustrate this methodology, we model and analyze the sequence of actions for an emergency procedure. The procedure, Irregular Engine Start, for a medium-range aircraft, specifies the sequence of immediate actions that must be performed by the crew to avoid an uncontrolled rise in engine temperature during start-up. A model of engine behavior during a hot start is constructed. It also describes the various actions that can be taken by the crew and the resulting outcomes. The model is then opened up as a tree of all possible action sequences. This action tree allows us to trace the correct sequences necessary to achieve the desired end-goal (secure and shut down of the engine). In conclusion, we argue that the current process of designing and evaluating procedures can be improved. We discuss the implications of this approach for designing and evaluating this and other types of procedures. We conclude with insights about the benefits and limitation of this methodology, and offer suggestions for future research.

Degani, Asaf↗

NASA NTRS2011

Lunabotics Mining Competition: Inspiration Through Accomplishment

NASA's Lunabotics Mining Competition is designed to promote the development of interest in space activities and STEM (Science, Technology, Engineering, and Mathematics) fields. The competition uses excavation, a necessary first step towards extracting resources from the regolith and building bases on the moon. The unique physical properties of lunar regolith and the reduced 1/6th gravity, vacuum environment make excavation a difficult technical challenge. Advances in lunar regolith mining have the potential to significantly contribute to our nation's space vision and NASA space exploration operations. The competition is conducted annually by NASA at the Kennedy Space Center Visitor Complex. The teams that can use telerobotic or autonomous operation to excavate a lunar regolith geotechnical simulant, herein after referred to as Black Point-1 (or BP-1) and score the most points (calculated as an average of two separate 10-minute timed competition attempts) will eam points towards the Joe Kosmo Award for Excellence and the scores will reflect ranking in the on-site mining category of the competition. The minimum excavation requirement is 10.0 kg during each competition attempt and the robotic excavator, referred to as the "Lunabot", must meet all specifications. This paper will review the achievements of the Lunabotics Mining Competition in 2010 and 2011, and present the new rules for 2012. By providing a framework for robotic design and fabrication, which culminates in a live competition event, university students have been able to produce sophisticated lunabots which are tele-operated. Multi-disciplinary teams are encouraged and the extreme sense of accomplishment provides a unique source of inspiration to the participating students, which has been shown to translate into increased interest in STEM careers. Our industrial sponsors (Caterpillar, Newmont Mining, Harris, Honeybee Robotics) have all stated that there is a strong need for skills in the workforce related to robotics and automated machines. In 2010, 22 United States (US) universities competed, and in May 2011 the competition was opened to international participation, with 46 Universities attending. There were 12 international teams and 34 US teams. This combined total directly inspired an estimated 544 university students. More students and the public were engaged via internet broadcasting and social networking media. This is expected to be of value for actual future space missions, as knowledge is gained from testing many innovative prototypes in simulated lunar regolith. More information is available at www.nasa.gov/lunabotics/.

Mueller, Robert P.↗

NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

This paper establishes the feasibility of using Natural Language Processing (NLP) to classify NOTAMs or Notices to Airmen – a pilot messaging framework to gather real-time situational awareness. Present day air mobility operations heavily rely on NOTAMs. However, pilots often have difficulty interpreting NOTAMs due to the sheer volume of inapplicable messages and unclear abbreviations. Using NLP, the presented study analyzes the accuracy of classifying NOTAMs and, thereby, the efficiency of generating actionable interpretations in real time. To this effect, efficacies of four NLP neural network architectures were analyzed, including three Recurrent Neural Networks (RNNs) with GloVe, Word2Vec, and FastText word embeddings, and one trained Bi-Directional Encoder Representations from Transformers (BERT) model. The four neural networks were trained and evaluated on three open-source datasets of varying text lengths, vocabularies, and grammars, taken from e-commerce product descriptions, social media tweets, and unstructured descriptions for data and analytics services on open data marketplaces such as NASA’s Data and Reasoning Fabric (DRF) platform. This provided cross-analysis of each neural network architecture’s performance per text type. The best performing architecture, BERT, was then fine-tuned on a collection of open-source NOTAM data. Post-training, a real-time NOTAM classification service was implemented to draw inference on new NOTAMs using the trained model, which demonstrated close to 99% accuracy in classification. This modular classification service is envisioned to be integrated with a data and analytics delivery platform, such as the DRF, thus availing real-time contextualization of NOTAMs to air mobility clients, humans, and machines for enhanced decision making.

Aiden C. Szeto↗

NASA NTRSDate not supplied

Classification of Notices to Airmen using Natural Language Processing

Aiden Szeto↗

DOE OSTI2021

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

Automation and optimization of chemical systems require well-informed decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. Here we introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian optimization algorithms and supports both automated an d human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

The Analysis Description Language Ecosystem: Latest developments and physics applications

We present latest developments in Analysis Description Language (ADL), a declarative domain-specific language describing the physics algorithm of a HEP data analysis decoupled from software frameworks. Analyses written in ADL can be integrated into any framework for various tasks. ADL is a multipurpose construct with uses ranging from analysis design to preservation, reinterpretation, queries, visualisation, combination, etc. The most advanced infrastructure to execute ADL on events is the CutLang runtime interpreter. Recent technical developments include an automated interface with different data types, generation of the abstract syntax tree, a visualization tool that that auto-converts analysis flows to graphs, incorporation of trained machine learning models and a Jupyter-based plotting tool. We also report physics implications including a large scale LHC analysis implementation and validation effort for beyond the standard model reinterpretation purposes and studies with ATLAS and CMS open data.

Sekmen, Sezen [Kyungpook National Univ., Daegu (Ko↗