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NASA NTRS2018

Biocene 2018 - Welcome to the Period of New Life

Biocene is the period of new life. When our descendants look back at this period in time, they will see evidence, in the geologic and electronic record, of anthropic climate change, growing population, and scarcity of resources. But they will also see the rebirth of human ingenuity as we overcame the challenges that faced us through nature-inspired exploration. The Periodic Table of Life (PeTaL) is a proposed tool and open source framework that uses artificial intelligence to aid in the systematic inquiry of biology for its application to human systems. This presentation defines the PeTaL concept and workflow. Biomimicry, biophysics, biomimetics, bionics and numerous other terms refer to the use of biology and biological principles to inform practices in other disciplines. For the most part, the domain of inquiry in these fields have been confined to extant biological models with the proponents of biomimicry often citing the evolutionary success of extant organisms relative to extinct ones. The primary objective of this paper is to expand the domain of inquiry for human processes that seek to model those that are, were or could be found in nature with examples that relate to the field of aerospace and to spur development of tools that can work together to accelerate the use of artificial intelligence in problem solving. Specifically specialized fields such as paleomimesis, anthropomimesis and physioteleology are proposed in conjunction with artificial evolution. Blockchain technology may be vital in allowing open source design tools such as PeTaL to democratize design and yet protect intellectual property. The overarching philosophy outlined here can be thought of as physiomimetics, a holistic and systematic way of learning from natural history. The backbone of PeTaL integrates an unstructured database with an ontological model consisting of function, morphology, environment, state of matter and ecosystem. Tools include text classification, thesaurus, data visualization, and analysis. Applications of PeTaL include guiding human space exploration, understanding human and geological history, and discovering new or extinct life.

Biocene↗
DOE OSTI2023

Theoretical upper limits of the thermal conductivity of Si3N4

Silicon nitride (Si3N4) is a promising substrate for high-power electronics due to its superior mechanical properties and potential outstanding thermal conductivity (κ). As experiments keep pushing the upper limit of κ of Si3N4, it is believed that it can reach 450 W/mK, similar to SiC, based on classical models and molecular dynamics simulations. In this work, we reveal from first principles that the theoretical κ upper limits of β-Si3N4 are only 169 and 57 W/mK along the c and a axes at room temperature, respectively. Those of α-Si3N4 are about 116 and 87 W/mK, respectively. The predicted temperature-dependent κ matches well with the highest available experimental data, which supports the accuracy of our calculations, and suggests that the κ upper limit of Si3N4 has already been reached in the experiment. Compared to other promising semiconductors (e.g., SiC, AlN, and GaN), Si3N4 has a much lower κ than expected even though the chemical bonding and mechanical strengths are close or even stronger. We find the underlying reason is that Si3N4 has much lower phonon lifetimes and mean free paths (<0.5 μm) due to the larger three-phonon scattering phase space and stronger anharmonicity. Interestingly, we find that the larger unit cell (with more basis atoms) that leads to a smaller fraction of acoustic phonons is not the reason for lower κ. Grain size-dependent κ indicates that the grain boundary scattering plays a negligible role in most experimental samples. This work clarifies the theoretical κ upper limits of Si3N4 and can guide experimental research.

Physics↗
DOE OSTI2025

Atomic-Scale Insights into Carbon Dissolution in α-, γ-, and θ-Al 2 O 3 : Phase-dependent Transport Dynamics from First-Principles Calculations

α-Al 2 O 3 exhibits superior carburizing corrosion resistance compared to metastable γ-Al 2 O 3 and θ-Al 2 O 3 phases in high-temperature CO 2 environments, yet its atomic-scale origins remain unclear. Using first-principles density functional theory, we systematically investigate carbon dissolution and diffusion in α-Al 2 O 3 , γ-Al 2 O 3 , and θ-Al 2 O 3 , including the effects of oxygen (O) and aluminum (Al) vacancies. Our results show that α-Al 2 O 3 consistently exhibits higher carbon solution enthalpies than γ-Al 2 O 3 and θ-Al 2 O 3 in both pristine and defective structures, indicating lower intrinsic carbon solubility in α-Al 2 O 3 . Vacancies significantly enhance carbon incorporation: O vacancies reduce solution enthalpy, while Al vacancies further amplify this effect, with a strong preference for carbon at Al vacancy sites. Carbon diffusion barriers are also highest in α-Al 2 O 3 , reflecting slower carbon mobility. Al vacancies increase diffusion barriers across all phases, while O vacancies raise barriers in α- and γ-Al 2 O 3 but slightly lower them in θ-Al 2 O 3 . These results reveal a dual mechanism behind the carburizing resistance of α-Al 2 O 3 : reduced carbon solubility and elevated diffusion barriers. Furthermore, this work provides atomic-scale insights to guide the design of alumina-based materials with improved carburizing resistance through phase selection and defect engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Genome-Wide Analysis of RNA Decay in the Cyanobacterium Synechococcus sp. Strain PCC 7002

ABSTRACT RNA degradation is an important process that influences the ultimate concentration of individual proteins inside cells. While the main enzymes that facilitate this process have been identified, global maps of RNA turnover are available for only a few species. Even in these cases, there are few sequence elements that are known to enhance or destabilize a native transcript; even fewer confer the same effect when added to a heterologous transcript. To address this knowledge gap, we assayed genome-wide RNA degradation in the cyanobacterium Synechococcus sp. strain PCC 7002 by collecting total RNA samples after stopping nascent transcription with rifampin. We quantified the abundance of each position in the transcriptome as a function of time using RNA-sequencing data and later analyzed the global mRNA decay map using machine learning principles. Half-lives, calculated on a per-ORF (open reading frame) basis, were extremely short, with a median half-life of only 0.97 min. Despite extremely rapid turnover of most mRNA, transcripts encoding proteins involved in photosynthesis were both highly expressed and highly stable. Upon inspection of these stable transcripts, we identified an enriched motif in the 3′ untranslated region (UTR) that had similarity to Rho-independent terminators. We built statistical models for half-life prediction and used them to systematically identify sequence motifs in both 5′ and 3′ UTRs that correlate with stabilized transcripts. We found that transcripts linked to a terminator containing a poly(U) tract had a longer half-life than both those without a poly(U) tract and those without a terminator. IMPORTANCE RNA degradation is an important process that affects the final concentration of individual mRNAs, affecting protein expression and cellular physiology. Studies of how RNA is degraded increase our knowledge of this fundamental process as well as enable the creation of genetic tools to manipulate RNA stability. By studying global transcript turnover, we searched for sequence elements that correlated with transcript (in)stability and used these sequences to guide tool design. This study probes global RNA turnover in a cyanobacterium, Synechococcus sp. strain PCC 7002, that both has a unique array of RNases that facilitate RNA degradation and is an industrially relevant strain that could be used to convert CO 2 and sunlight into useful products.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

Dynamics of Planets Orbiting in the Alpha Centauri AB Stellar System

The Alpha Centauri system contains the Solar System's closest stellar neighbors. If an earth-like planet is present in the system, it could in principle be detected using a small space-based telescope. As Alpha Centauri is billions of years old, planets are only expected to be found in regions where their orbits are long-lived. We evaluate the extent of the regions within the Alpha Centauri AB system where small planets are able to orbit for billion-year timescales, as well as how closely-spaced planetary orbits can be within those regions in which individual planets can survive. Individual planets on nearly circular, coplanar orbits can survive throughout the habitable zones of both stars. However, perturbations from the companion star imply that the spacing of such planets in multi-planet systems must be significantly larger than the spacing of similar systems orbiting single stars in order to be long-lived. Because the binary companion induces a forced eccentricity upon the orbits of planets in orbit around either star, appropriately-phased circumstellar orbits with small initial eccentricities are stable to slightly larger initial semi-major axes than are initially circular orbits. Small initial eccentricities have a much larger effect on how closely planetary orbits can be spaced. Our results are of special interest as they can guide observers designing instrumentation and search strategies to attempt to discover planets orbiting the nearest sun-like stars. Results remain significantly higher than for planets orbiting single stars.

Lissauer, Jack J.↗
DOE OSTI2016

Assessment of Potential Impact of Electromagnetic Fields from Undersea Cable on Migratory Fish Behavior

The US Department of Energy and US Department of the Interior, Bureau of Ocean Energy Management commissioned this study to address the limited scientific data on the impacts of high voltage direct current cables on aquatic biota, in particular migratory species within the San Francisco Bay. Empirical evidence exists that marine animals perceive and orient to local distortions in the earth’s main geomagnetic field magnetic field. The electromagnetic fields (EMF) generated by the cables that carry electricity from hydrokinetic energy sources to shore-based power stations may produce similar local distortions in the earth’s main field. Concern exists that animals that migrate along the continental shelves might orient to the EMF from the cables, and move either inshore or offshore away from their normal path. The Trans Bay Cable (TBC) is a ±200-kilovolt (kV), 400 MW 85-km long High Voltage Direct Current (DC) buried transmission line linking Pittsburg, CA with San Francisco, CA (SF) through the San Francisco Bay. The study addresses the following specific questions based on measurements and projections of the EMF produced by an existing marine cable, the TBC, in San Francisco Bay. Specifically, does the presence of EMF from an operating power cable alter the behavior and path of bony fishes and sharks along a migratory corridor? Does the EMF from an operating power cable guide migratory movements or pose an obstacle to movement? To meet the main study objectives several activities needed to be carried out: 1) modeling of the magnetic fields produced by the TBC, 2) assessing the migratory impacts on Chinook salmon smolts (Oncorhynchus tshawytscha) and green sturgeon (Acipenser medirostris) as a result of local magnetic field distortions produced by bridge structures and 3) analyzing behavioral responses by migratory Chinook salmon and green sturgeon to a high-voltage power cable. To meet the first objective, magnetic field measurements were made using two submerged Geometrics magnetometers towed behind a survey vessel in four locations in the San Francisco estuary along profiles crossing the cable path. We applied basic formulas to describe magnetic field from a DC cable summed vectorially with the background geomagnetic field (in the absence of other sources that would perturb the ambient field) to derive characteristics of the cable not immediately or otherwise observable. The magnetic field profiles of 76 survey lines were regressed against the measured fields, representing eight days of measurement. Many profiles were dominated by field distortions caused by bridge structures or other submerged objects, and the cable contribution to the field was not detectable. The regressions based on fundamental principles (Biot Savart law) and the vectorial summation of cable and geomagnetic fields provide estimates of cable characteristics consistent with plausible expectations. For the second objective, detailed gradiometer survey were examined. Distortions in the earth’s main field produced by bridges across the estuary were much greater than those from the TBC. The former anomalies exceeded the latter by an order of magnitude or more. Significant numbers of tagged Chinook salmon smolts migrated past bridges, which produced strong magnetic anomalies, to the Golden Gate Bridge, where they were recorded by dual arrays of acoustic tag-detecting monitors moored in lines across the mouth of the bay. Adult green sturgeon successfully swam upstream and downstream through the estuary on the way to and from their spawning grounds. Hence, the large anomalies produced by the bridges that run perpendicular to these migration routes do not appear to present a strong barrier to the natural seasonal movement patterns of salmonid smolts and adult green sturgeon. Finally, to assess the behavioral responses by migratory Chinook salmon and green sturgeon to a high- voltage power cable - the potential impacts effect of the TBC on fishes migrating through the San Francisco Estuary were examined. These included late-fall run Chinook salmon smolts (Oncorhynchus tshawytscha) that migrate downstream through the San Francisco Estuary to the Pacific Ocean and adult green sturgeon (Acipenser medirostris), which migrate upstream from the ocean through the estuary to their spawning habitat in the upper Sacramento River and return to the ocean after spawning occurs. Our results indicate Chinook salmon smolts may be attracted to the cable after activation (more cable location crossings, more detections at Bay Bridge, high importance of distance to cable in predicting fish location), but are not impeded from successfully migrating through the San Francisco Bay (similar proportions of successful exits, faster transit rates). Cable activity had opposite effects on outbound and inbound green sturgeon migrations: outbound migrations had significantly longer transit times while inbound migrations had significantly shorter migration times. However, the proportion of green sturgeon that successfully migrated through the San Francisco Bay was not strongly impacted after cable activation for either migration type. Based on the work, we provide the following conclusions: 1) calculations of magnetic fields for assessment of marine life can be performed; however, local anomalies in the fields resulting from submerged structures require validation of such calculations through collection of ambient DC magnetic field data, 2) the large anomalies produced by the bridges that run perpendicular to these migration routes do not appear to present a strong barrier to the natural seasonal movement patterns of salmonid smolts and adult green sturgeon and 3) Chinook salmon smolts may be attracted to the activated cable based on analysis of cable crossing, misdirections, and first presence at the array data, however, the cable activation does not appear to change the proportion of smolts that successfully migrate through the San Francisco Bay. Cable activation impacts inbound and outbound migrating adult green sturgeon: travel time was increased for outbound migrations but decreased for inbound migrations. However, cable activation did not appear to impact the success of either migration type in this species.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS2008

The Project Manager Who Saved His Country

George Meade defeated Robert E. Lee, one of the greatest military leaders of all time. How did he do it? By using the skills he had learned as a project manager and outperforming Lee in all aspects of project management. Most project managers are familiar with the Project Management Institute's "Guide to the Project Management Body of Knowledge" (PMBOK), which identifies the skills and knowledge crucial to successful project management. Project managers need to make sure that all the elements of a project work together. They must develop and execute plans and coordinate changes to those plans. A project manager must define the scope of the work, break it into manageable pieces, verify and control what work is being done, and make sure that the work being done is essential to the project. Every project manager knows the challenges of schedule and the value of schedule slack. Project managers must get the resources they need and use them effectively. Project managers get the people they need and use their talents to achieve mission success. Projects generate huge amounts of information. A key to project success is getting sufficient and accurate information to the people who need it when they need it. Project managers must identify and quantify the risks that jeopardize project success and make plans for dealing with them. Studying Meade and Lee's performances at Gettysburg can help modern project managers appreciate, develop, and use the skills they need to be good project managers. The circumstances may be different, but the basic principles are the same. This dramatic event in American history shows how the skills of project management can be used in almost any situation. Former project manager George Meade used those skills to change the tide of the Civil War.

Baniszewski, John↗
DOE OSTI2022

Ammonia synthesis on BaTiO 2.5 H 0.5 : computational insights into the role of hydrides

Perovskite oxyhydrides such as BaTiO 2.5 H 0.5 have been found to be able to catalyze NH3 synthesis, but the mechanism and the role of the catalyst's lattice hydrides in the catalytic reaction remain unknown. Here we employ first principles density functional theory to investigate the mechanism of ammonia synthesis and the role of lattice hydrides on a prototypical perovskite oxyhydride, BaTiO 2.5 H 0.5 (BTOH). Two mechanistic hypotheses, the distal and alternating pathways, have been tested on the Ti2O 2 termination of the BTOH (210) surface, previously determined to be the most stable surface termination under the reaction conditions considered. In the distal pathway, H atoms hydrogenate N 2 to form the *N–NH x key intermediates, followed by N–N bond breaking. In the alternating pathway, H atoms hydrogenate N 2 in an alternating fashion to form the *NH x –NH y intermediates before N–N bond breaking and formation of co-adsorbed *NH x /*NH y on the surface. We find that the subsurface hydride vacancy formed after reaction of *N 2 with the lattice hydride is key to the distal pathway, leading to surface nitride formation after breaking the *N–NH 3 bond, while the neighboring surface Ti sites are key to bridging and stabilizing the *NNH intermediate in the alternating pathway. In both pathways, desorption of NH 3 is the most uphill in energy. Our results provide important insights into the role of hydrides and surface vacancies in hydrogenation reactions over BTOH, which will be useful to guide future spectroscopic experiments such as operando IR and inelastic neutron scattering to verify the key intermediates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Integrated Issues and Risk Management: A Theoretical Framework Overview

The contractor requirements document for DOE O 226.1B, Implementation of Department of Energy Oversight Policy, requires DOE/NNSA contractors to establish an assurance system that includes, among other things, “Rigorous, risk-informed, and credible self-assessment and feedback and improvement activities. Assessment programs must be risk-informed, formally described and documented, and appropriately cover potentially high consequence activities” and “Contains an issues management process that is capable of categorizing the significance of findings based on risk and priority and other appropriate factors….” However, the term “risk-informed” is not defined in this or any other DOE order, and no formal guidance on how to integrate the two concepts currently exists. The Risk Management Guide for Defense Programs released by NA-18, Office of Systems Engineering and Integration (SE&I), states it is “a framework and general guidance to program office personnel on the effective management of program risks and issues”, however it then defines issues as “events with 100% likelihood of affecting program objectives” and states “unless specified otherwise, the term “risk” will also serve to represent issues for the remainder of this plan,” severally limiting its ability to provide adequate guidance on this topic. Outside of DOE scope, the U.S. Nuclear Regulatory Commission (U.S. NRC) imposes similar requirements. ASME NQA-1-2015 Requirement 16 states “Conditions adverse to quality shall be identified promptly and corrected as soon as practicable. In the case of a significant condition adverse to quality, the cause of the condition shall be determined, and corrective action taken to preclude recurrence. The identification, cause, and corrective action for significant conditions adverse to quality shall be documented and reported to appropriate levels of management. Completion of corrective actions shall be verified”. The purpose of this document is to provide a best-in-class framework for an integrated risk and issues management process. This process would provide a robust feedback loop between risk management and issues management to: Enhance risk identification and characterization, use risk handling principles to improve corrective action planning, and ensure regulatory compliance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Emerging anomaly detection techniques for electronic health records: A survey

Background Anomaly detection in electronic health records (EHRs) is a cornerstone of biomedical informatics, with direct implications for patient safety, clinical decision-making, and the prevention of healthcare fraud. Once guided primarily by simple rule-based methods, the field has advanced rapidly, driven by increased computing power, richer and more detailed health data, and the rise of machine learning and deep learning techniques. The objective of this paper is to provide a comprehensive overview of modern approaches to detecting anomalies in EHRs, outlining their strengths, limitations, and relevance to key healthcare challenges. We review traditional statistical methods alongside newer ML- and DL-based strategies and hybrid models, with particular attention to how these techniques support transparency and build clinical trust. Methods This paper presents a thorough and critical survey through systematic review (PRISMA-based) of the latest anomaly detection strategies in time-sequence data domains within electronic health record systems. Results We explore a broad spectrum of methodologies, including statistical models, supervised and unsupervised learning approaches, hybrid frameworks, and state-of-the-art ML-based techniques that collectively advance the precision and scalability of detecting anomalies in complex clinical datasets. In addition to mapping current capabilities, we address the enduring challenges that hinder widespread implementation and provide a forward-looking perspective on the future of anomaly detection in the data-rich landscape of modern healthcare. Summary The advancement in AI-based approaches is reported along with the basic principles of the individual approaches and their applicability. The increased availability of high-quality data, advancements in DL approaches, and enhanced computation power are leading to more frequent adaptation of DL-based approaches. Emerging DL-based approaches that have been adapted in other domains or recently applied in the EHR domain are also discussed in detail. Although DL-based approaches can improve model predictions by incorporating comorbidities, their application is limited in low-frequency data domains (e.g., when the total available data remains in the single digits). Therefore, the user must carefully consider the application based on data availability.

Anomaly detection↗
DOE OSTI2023

Evaluating energy justice metrics in early-stage science and technology research using the JUST-R metrics framework

Embedding principles of energy justice throughout all aspects of clean energy technology research and development (R&D) can facilitate a more just energy transition; yet gaps remain in our understanding of how to best integrate energy justice from the earliest R&D stages. The Justice Underpinning Science and Technology Research (JUST-R) metrics framework has been developed to enable early-stage energy researchers to assess and address justice considerations associated with their research, but the impacts of the framework, and others like it, have yet to be evaluated. This study seeks to evaluate the JUST-R metrics framework in terms of its effectiveness and appeal to researchers engaged in early-stage technical R&D using qualitative analyses of documents and workshop transcripts. We find that the metrics framework helps researchers identify problems and potential solutions surrounding the energy justice implications of their work and spurs a change in perspective for researchers, but, simultaneously, there is no evidence of solution follow-through within the evaluation timeframe. Greater institutional support, specialization to research areas, knowledge of energy justice fundamentals, and earlier incorporation of energy justice considerations in research projects arise as factors needed to aid continued use of the framework and pursuit of identified solutions. This evaluation protocol and these findings can serve as a guide for improving other frameworks with similar goals of encouraging sociotechnical engagement in early-stage energy R&D.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

First Principles Modeling of Cluster-Based Solid Electrolytes (Final Technical Report)

Given the trend of global warming and the urgent need to transition from fossil fuels to green energy, lithium-ion batteries continue to be an integral part of our lives. Design, development, and understanding of novel solid-state electrolyte materials play the key role for achieving next-generation all-solid-state batteries with high energy and great safety. The current modeling schemes to develop advanced solid electrolytes are focusing on materials in which the building blocks are individual atoms. Our theoretical approach is a paradigm shift in solid-state electrolyte design. Instead of atoms, we focus on clusters as the building blocks and model these solid electrolytes and their interfaces with electrodes, especially Li-metal anode, for their successful implementation in solid-state batteries. The advantage of using the cluster ions to replace elemental ions is that the size, composition, and shape of the former can be tailored to achieve higher ionic conductivity at room temperature, electrochemical stability, and charge transfer across solid-solid interfaces than conventional materials. Specifically, the project includes: (1) Developing cluster-based solid electrolytes, where the halogen components are replaced by cluster ions that mimic the chemistry of halogens but are characterized by additional degrees of freedom, including the size, shape, composition, and motional dynamics under excitation. (2) Providing a fundamental understanding of the ion conduction mechanism in the developed cluster-based solid electrolytes; (3) Modeling the interfacial properties (i.e., structural, chemical, and transport properties) between the cluster-based solid electrolytes and electrodes at the atomic level. For the cluster-based solid electrolytes incompatible with the Li-metal anode or cathode materials, potential candidates for interfacial coatings are identified and studied. (4) Providing a theoretical framework towards optimizing critical parameters of the solid-state electrolytes that guides experimentalists to attain desired cathode-electrode interface for cluster-based solid-state electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2020

Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making

It is widely believed that one’s peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the “pattern” by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game decides among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make a similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Monolayer Sc 2 CF 2 as a Potential Selective and Sensitive NO 2 Sensor: Insight from First-Principles Calculations

Two-dimensional materials with excellent surface–volume ratios and massive reaction sites recently have been receiving attention for gas sensing. With first-principles calculations, we explored the performance of monolayer Sc 2 CF 2 as a gas sensor. We investigated how molecule adsorption affects its electronic structure and optical properties. It is found that a large charge transfer quantity happens between Sc 2 CF 2 and NO 2 , which results from the fact that the lowest unoccupied molecular orbital (LUMO) of NO 2 is below the valence band maximum (VBM) of Sc 2 CF 2 . Moreover, the MD simulation shows that NO 2 can adsorb on the Sc 2 CF 2 surface stably at room temperature. We explored the effect of biaxial strain on the adsorption energy and charge transfer quantity of each system, and the results show that the biaxial strain can enhance both the adsorption energy and charge transfer quantity of the NO 2 system and thus can improve the sensitivity of Sc 2 CF 2 in detecting the NO 2 molecule. Furthermore, we investigated the adsorption behavior and charge transfer of polar polyatomic molecules at the Sc 2 CF 2 surface with h-BN as a substrate, and the results demonstrate that the h-BN substrate can hardly modify the main results. Our result predicts that Sc 2 CF 2 can be a promising selective and sensitive sensor to detect the NO 2 molecule, and could also give a theoretical guide for other terminated MXenes used for gas sensors or detectors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗
DOE OSTI2025

Phase-based velocity extraction method for photonic Doppler velocimetry with potential higher time resolution

We present an extension of the [Takeda et al., J. Opt. Soc. Am. 72, 156 (1982)] phase extraction method to heterodyne photonic Doppler velocimetry applications. The method yields results equivalent to those obtained by the short-time Fourier transform (STFT), while offering potential improvements in time resolution. Unlike STFT, which relies on window functions, such as the Hamming window, that emphasize central data points and diminish the influence of edges, the extended Takeda method utilizes all data uniformly. This uniform treatment allows for the derivation of empirical equations that directly relate velocity error to the actual time resolution rather than to the local analysis duration. The established equation provides a useful metric for both optimizing hardware configuration and guiding data analysis. Simulation and experimental results confirm that, for a given dataset, specifying a target time resolution yields consistent velocity errors for both methods. These findings underscore the Takeda method’s advantages, particularly its potential higher time resolution and reduced computational burden, making it a valuable tool for high-throughput applications such as laser dynamic compression experiments.

Computer simulation↗
DOE OSTI2021

Sub-pixel high-resolution imaging of high-energy x-rays inspired by sub-wavelength optical imaging

We have developed and demonstrated an image super-resolution method—XR-UNLOC: X-Ray UNsupervised particle LOCalization—for hard x-rays measured with fast-frame-rate detectors that is an adaptation of the principle of photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), which enabled biological fluorescence imaging at sub-optical-wavelength scales. We demonstrate the approach on experimental coherent Bragg diffraction data measured with 52 keV x-rays from a nanocrystalline sample. From this sample, we resolve the fine fringe detail of a high-energy x-ray Bragg coherent diffraction pattern to an upsampling factor of 16 of the native pixel pitch of 30 μ m of a charge-integrating fastCCD detector. This was accomplished by analysis of individual photon locations in a series of “nearly-dark” instances of the diffraction pattern that each contain only a handful of photons. Central to our approach was the adaptation of the UNLOC photon fitting routine for PALM/STORM to the hard x-ray regime to handle much smaller point spread functions, which required a different statistical test for photon detection and for sub-pixel localization. A comparison to a photon-localization strategy used in the x-ray community (“droplet analysis”) showed that XR-UNLOC provides significant improvement in super-resolution. We also developed a metric by which to estimate the limit of reliable upsampling with XR-UNLOC under a given set of experimental conditions in terms of the signal-to-noise ratio of a photon detection event and the size of the point spread function for guiding future x-ray experiments in many disciplines where detector pixelation limits must be overcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Optimizing the Synthetic Potential of O 2 : Implications of Overpotential in Homogeneous Aerobic Oxidation Catalysis

Molecular oxygen is the quintessential oxidant for organic chemical synthesis, but many challenges continue to limit its utility and breadth of applications. Extensive historical research has focused on overcoming kinetic challenges presented by the ground-state-triplet electronic structure of O 2 and the various reactivity and selectivity challenges associated with reactive oxygen species derived from O 2 reduction. This Perspective will analyze thermodynamic principles underlying catalytic aerobic oxidation reactions, borrowing concepts from the study of the oxygen reduction reaction (ORR) in fuel cells. This analysis is especially important for "oxidase"-type liquid-phase catalytic aerobic oxidation reactions, which proceed by a mechanism that couples two sequential redox half-reactions: (1) substrate oxidation, and (2) oxygen reduction, typically affording H 2 O 2 or H 2 O. The catalysts for these reactions feature redox potentials that lie between the potentials associated with the substrate oxidation and oxygen reduction reactions, and changes in the catalyst potential lead to variations in effective overpotentials for the two half reactions. Catalysts that operate at low ORR overpotential retain more thermodynamic driving force for the substrate oxidation step, enabling O 2 to be used in more challenging oxidations. While catalysts that operate at high ORR overpotential have less driving force available for substrate oxidation, they often exhibit different or improved chemoselectivity relative to the high-potential catalysts. The concepts are elaborated in a series of case studies to highlight their implications for chemical synthesis. Examples include comparisons of (a) NO x /oxoammonium and Cu/nitroxyl catalysts, (b) high-potential quinones and amine oxidase biomimetic quinones, and (c) Pd aerobic oxidation catalysts, with or without NO x cocatalysts. In addition, we show how reductive activation of O 2 provides a means to access potentials not accessible with conventional oxidase-type mechanisms. Altogether, this analysis highlights the central role of catalyst overpotential in guiding the development of aerobic oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗