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DOE OSTI2026

Local Chain Dynamics in Sequence-Controlled Polymers as a Tunable Handle for Rare Earth Sequestration

Chain dynamics govern the intricate behaviors of proteins, underpinning functions such as catalysis, recognition, and stimulus response, and are an increasingly appreciated aspect of structure–function relationships. Analogously, manipulating chain dynamics and structure in abiotic polymers via sequence control is an exciting, yet underexplored, strategy for improving material functions. In this work, we report a systematic study relating the sequence of polymeric sequestrants to their structure and dynamics, as well as to their binding affinity and selectivity for model substrates, rare earth elements (REEs). A series of sequence-controlled polymers with metal chelating, solubilizing, and structure forming monomers was synthesized via multiblock polymerization, yielding compositionally identical polymers with spectroscopically resolved domains and distinct morphologies. Using a combination of small-angle X-ray scattering and 19 F NMR relaxometry measurements, we connected differences in polymer structure and dynamics to polymer sequence variables such as the patchiness (density) of the structure forming monomer and the location of the chelating monomer. Furthermore, we found that, relative to calcium, all polymers in the series collapse more and have slower dynamics when binding REEs (lanthanum and lutetium) , though the extent of these effects were sequence-dependent and localized to specific domains within the polymer. Notably, sequence-controlled polymers that exhibited the largest conformational and dynamic changes upon binding REEs also bound REEs with the greatest affinity and modest selectivity. Collectively, these results correlate monomer patterning with dynamics, morphology, and REE binding performance en route to the development of efficient and selective macromolecular chelators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1993

Are the C delta light nitrogen and noble gases located in the same carrier?

Light nitrogen and the HL family noble gas components of C(sub delta) appear to be separable by high resolution pyrolysis experiments. Thus C(sub delta) is not a homogeneous material and probably consists of debris of many stars. The question of whether the N and Xe(HL) actually reside in different carriers continues to be addressed. It is well known that C(sub delta) which was identified as nanometer sized diamonds contains isotopically anamalous elements, in particular noble gases including Xe(HL) and its family and light nitrogen (delta(N-15) down to -350 percent). Before the true nature of C(sub delta) was recognized, it was easy to suppose that the Xe(HL) and light nitrogen were located in the same carrier. However, recognition that light nitrogen in diamond from different samples varies by greater than a factor of six compared to Xe(HL) fluctuations of ca. 20 percent makes such an assumption questionable. On the basis of simple arithmetic logic, the Xe and nitrogen cannot be absolutely co-located. The average diamond grain consists of only about 1000-2000 atoms of carbon; one grain among a few x 10(exp 6) contains an atom of Xe(HL) while 5-30 atoms of light nitrogen are the typical number which need to be in every diamond grain to account for observed concentrations. If some grains are devoid of N, the others have to have a higher N concentration. Even if we were able to analyze an individual grain of the diamond for noble gases and nitrogen, we would be faced with the monumental task of locating the one amongst 10(exp 6) identical grains containing the Xe atom to examine its nitrogen content. The problem can be simplified to some extent if instead of Xe, He which is 10(exp 4) times more abundant is assumed to be a member of the HL family. Attempts to fractionate the separate carriers might be attempted using He and N as guiding indicators but even experiments of this nature are for the future. Faced with apparently insoluble problems, we have returned to an investigation we last used in our original efforts to find isotopically light nitrogen, that is to compare release patterns of the different components during stepped pyrolysis and combustion.

Verchovsky, A. B.↗

DOE OSTI2023

PRIMED for the Future: Purposing Raw Intake for Machine Learning-Enabled Detection

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Artifact identification in X-ray diffraction data using machine learning methods

In situ synchrotron high-energy X-ray powder diffraction (XRD) is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices ( e.g. battery materials) or in complex sample environments ( e.g. diamond anvil cells or syntheses reactors). An atomic structure of a material can be identified by its diffraction pattern along with a detailed analysis of the Rietveld refinement which yields rich information on the structure and the material, such as crystallite size, microstrain and defects. For in situ experiments, a series of XRD images is usually collected on the same sample under different conditions ( e.g. adiabatic conditions) yielding different states of matter, or is simply collected continuously as a function of time to track the change of a sample during a chemical or physical process. In situ experiments are usually performed with area detectors and collect images composed of diffraction patterns. For an ideal powder, the diffraction pattern should be a series of concentric Debye–Scherrer rings with evenly distributed intensities in each ring. For a realistic sample, one may observe different characteristics other than the typical ring pattern, such as textures or preferred orientations and single-crystal diffraction spots. Textures or preferred orientations usually have several parts of a ring that are more intense than the rest, whereas single-crystal diffraction spots are localized intense spots owing to diffraction of large crystals, typically >10 µm. In this work, an investigation of machine learning methods is presented for fast and reliable identification and separation of the single-crystal diffraction spots in XRD images. The exclusion of artifacts during an XRD image integration process allows a precise analysis of the powder diffraction rings of interest. When it is trained with small subsets of highly diverse datasets, the gradient boosting method can consistently produce high-accuracy results. The method dramatically decreases the amount of time spent identifying and separating single-crystal diffraction spots in comparison with the conventional method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

PRIMED for the Future: Purposing Raw Intake for Machine Learning-Enabled Detection (Final Report)

The COVID-19 pandemic demonstrated how a novel, elusive, and diffuse biological threat can engender uncertainty and misinformation, and it underscored the need for flexible analytical modalities agnostic to the identity of biological material. Yet even before the pandemic, recognition of the limitations of the current, list-based approach, which focuses on known pathogens and biotoxins, and of the importance of agent-agnostic biodetection was growing within the biosecurity community. In a 2018 report on “Biodefense in the Age of Synthetic Biology,” for example, the National Academy of Sciences stated that “an overreliance on the Select Agent List is a systematic weakness affecting many aspects of the United States’ current biodefense mitigation capability”. More recently, a group of biodefense researchers proposed the identification and adoption of “bioagent-agnostic signatures (BASs)” as a way of detecting and characterizing not only existing agents but also novel ones, an approach they believe will “enable a more flexible and resilient biodefense posture”. Indeed, the future of biodetection requires us to begin developing novel analytics that can identify anomalies and/or characteristics that indicate a potential threat, whether known or unknown, without looking for a specific signature that has been identified previously. To assess potential threats more rapidly, it is critical to develop agnostic artificial intelligence (AI)/machine learning (ML) systems that can be employed for real-time assessment of the nature and source of a perturbation. Such systems should be multi scale and multi-dimensional, integrating sensor data from a range of biological, chemical, and physical application spaces. Emerging deep learning (DL) models demonstrate exceptional promise for identification of discriminatory features within multi-dimensional datasets. DL models have the capacity to recognize and encode highly complex patterns in a wide range of input data modalities, including images, text, and biological/chemical/physical spectra. As such, they can execute a wide range of assessments and determinations that have traditionally required a human operator. The promise of advances in DL is apparent in the realm of human health and medicine. DL models have been validated for evaluating a variety of clinical threats to human health in a range of contexts, including infection and cancer, and they demonstrated improved performance in predicting stroke relative to human neurologists in some categories of data. Continuously evolving advances in AI/ML are expected to support more efficient evaluation of raw sequence, spectroscopy, and spectrometry data. For instance, recent advances and deployment of large language models (LLM) such as Generative Pre training Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) have already motivated application of these models for biological function prediction. As frameworks such as LLMs become larger and more complex in their representations, their capacity to serve as pre-trained models that can be fine-tuned for biological/biodetection purposes will similarly be amplified. While existing and emerging AI/ML have found broad applicability and use cases in the clinical sciences, development for environmental evaluation and biodetection has been limited. Functionalizing such capabilities for this purpose requires an understanding of the existing technical landscape and how the respective tools and algorithms are currently being employed. This landscape awareness then allows an assessment of the current practical capabilities of existing models and the anticipated requirements and development efforts that will be needed to adapt available algorithms for biodetection applications relevant to DHS. Leveraging expertise in biodetection, ML, and operational biodetection, the effort described in this report is comprised of a systematic landscape assessment (Subtask 2.1), comparative evaluation (Subtask 2.2), and formulation of a value proposition (Subtask 2.3) for the prospect of ML-enabled, agnostic biodetection from raw, or minimally-processed, datasets.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗

NASA NTRS2000

On the Origin of Monsoon

The notion that the continental-scale land-sea contrast is the main reason that monsoon circulation exists has been a long-held belief. The purpose of this paper is to point out that this notion should be substantially modified. The central idea of this notion states that in summer, radiative heating of the continent, say Asia, gives rise to a continental-scale thermal low and surrounding the thermal low in its southeast direction the low level wind flows in from south-west. This low-level inflow creates a convergence of moisture, which maintains the cumulus convection. And in winter, radiative cooling of continent gives rise to a thermal high and to its southeast the low-level wind is from northeast. The mechanism in this interpretation does undoubtedly exist. However, this mechanism, though believed to be the main driving force of monsoon, has not been tested in numerical experiments. There has been an increasing recognition in the recent years that monsoon is inextricably tied to the heating in the intertropical convergence zone (ITCZ). We propose that the main cause of monsoon is ITCZ's being substantially away from the equator. A brief qualitative explanation of why the ITCZ can be a source of monsoon circulation can be offered based on the circulation field forced by the ITCZ heating. The existence of the ITCZ's does not always have to rely on land-sea contrast on the continental scale. This is hinted in the fact that in February the ITCZ close to Australia (and its associated monsoon circulation) covers a longitudinal range several times as long as that of Australia and thus cannot possibly be caused mainly by the land-sea contrast associated with Australia. Yet, this cannot be used as a proof that the ITCZ in the Asian summer monsoon is not mainly due to land-sea contrast. One of the purposes of this work is to provide a convincing proof. In this work the role of land-sea contrast in the origin of monsoon is examined through numerical simulation with the Goddard general circulation model. The Asian and Australian monsoon circulations are obtained in a four-year integration and then the integration is repeated with Asia, the maritime continent, and Australia replaced by ocean. The sea surface temperature (SST) at each affected grid is specified as the SST at the first grid to the east that is an ocean grid in the first experiment. The latter integration shows that the monsoon circulation pattern over where south Asia and Australia were and the surrounding region has largely remained. The results discount land-sea contrast as the main cause of Asian monsoon. A third experiment is the same as the first except that the topography of Asia, the maritime continent, and Australia is reduced to zero. This experiment reveals that the difference between the first two experiments is due more to the removal of topography than to the removal of land-sea contrast. August precipitation is shown averaged over the last three years of each of the three experiments. They show that the Asian monsoon rainy region is largely intact in the second experiment and the difference between the second and the third experiment is mainly in the longitudinal location of the maximum precipitation. Additionally, in Asian and Australian winter monsoons land-sea contrast also plays only a modifying role. Although land-sea contrast plays only a modifying role in Asian and Australian (and Central American including Mexican) monsoons, it is the main reason that ITCZ (and thus monsoon) exists in Africa and South America. Thus, monsoons can be classified into two groups depending on whether land-sea contrast plays a major role.

Chao, Winston C.↗

NASA NTRS2016

Africa's Megafans and Their Tectonic Setting

Megafans are a really extensive continental sediment bodies, fluvially derived, and fan-shaped in planform. Only those >80 km long were included in this study. Africa's megafans were mapped for purposes of both comprehensive geomorphic description and as a method of mapping by remote sensing large probable fluvial sediment bodies (we exclude sediment bodies deposited in well defined, modern floodplains and coastal deltas). Our criteria included a length dimension of >80 km and maximum width >40 km, partial cone morphology, and a radial drainage pattern. Visible and especially IR imagery were used to identify the features, combined with topographic SRTM data. We identified 99 megafans most of which are unstudied thus far. Their feeder rivers responsible for depositing megafan sediments rise on, and are consequent drainages oriented down the slopes of the swells that have dominated African landscapes since approximately 34 Ma (the high points in Africa's so-called basin-and-swell topography [1]). Most megafans (66%) have developed along these consequent rivers relatively near the swell cores, oriented radially away from the swells. The vast basins between the swells provide accommodation for megafan sediment wedges. Although clearly visible remotely, most megafans are inactive as a result of incision by the feeder river (which then no longer operates on the fan surface). Two tectonic settings control the location of Africa's megafans, 66% on swell flanks, and 33% related to rifts. (i) Swell flanks Most megafans are apexed relatively near the core of the parent swell, and are often clustered in groups: e.g., six on the west and north flanks of the Hoggar Swell (Algeria), seven on the north and south flanks of the Tibesti Swell (Libya-Chad borderlands), twelve on the west flank of the Ethiopian Swell, four on the east flank of the East African Swell (Kenya), Africa's largest, and eight around Angola's Bié Swell (western Zambia, northern Namibia). A cluster of possible fans lies on the western margin of the Congo Basin (Mayombe Swell), and on the coastal slopes of the Namibia Swell. Sheer size may have militated aginst the recognition of many megafans: the largest in the Sahara are the Teghahart (378 km, Hoggar Swell, Algeria), and the Wadi Albalata (340 km, Uweinat Swell, Egypt). In southern Africa the largest are the Cubango (320 km, Bié Swell, Angola/ Namibia), and the Limpopo (230 km, Mozambique). (ii) Rift zones (a) Steer's horns basins-wide depressions centered on rifts. The largest contiguous group (n=14) developed in a steer's-horns basin occupies the wide Muglad depression (200-350 km, South Sudan). Four rift-related megafans lie SE of Lake Chad (Chad). Nine megafans occupy the complex Anza Rift in Kenya/South Somalia. The Salamat megafan (Chad), is unusual because it oriented parallel with the linked Salamat, Doseo and Doba rift axes, and is consequently one of the longest in Africa (465 km). (b) Rift depressions sensu stricto. Most rifts are too narrow to provide a transverse dimension large enough to accommodate megafans. Although well-known, the Okavango Rift (NW Botswana, NE Namibia) is unique in Africa in hosting three megafans within identifiable faulted margins. The Nile megafan is Africa's largest (476 km) and comprises the vast Sudd wetland (South Sudan). An explanation for its remarkable size may be its location in a depression at the junction of two conducive tectonic zones, the East African Swell margin and the Muglad steer's-horns depression. Discharge of the River Nile, the largest in the region, has allowed the Nile megafan to outcompete neighboring megafans for space.

Wilkinson, M. J.↗