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At least 595 records · Page 33

Landsat 8: The Plans, the Reality, and the Legacy

Landsat 8, originally known as the Landsat Data Continuity Mission (LDCM), is a National Aeronautics and Space Administration (NASA)-U.S. Geological Survey (USGS) partnership that continues the legacy of continuous moderate resolution observations started in 1972. The conception of LDCM to the reality of Landsat 8 followed an arduous path extending over nearly 13 years, but the successful launch on February 11, 2013 ensures the continuity of the unparalleled Landsat record. The USGS took over mission operations on May 30, 2013 and renamed LCDM to Landsat 8. Access to Landsat 8 data was opened to users worldwide. Three years following launch we evaluate the science and applications impact of Landsat 8. With a mission objective to enable the detection and characterization of global land changes at a scale where differentiation between natural and human-induced causes of change is possible, LDCM promised incremental technical improvements in capabilities needed for Landsat scientific and applications investigations. Results show that with Landsat 8, we are acquiring more data than ever before, the radiometric and geometric quality of data are generally technically superior to data acquired by past Landsat missions, and the new measurements, e.g., the coastal aerosol and cirrus bands, are opening new opportunities. Collectively, these improvements are sparking the growth of science and applications opportunities. Equally important, with Landsat 7 still operational, we have returned to global imaging on an 8-day cycle, a capability that ended when Landsat 5 ceased operational Earth imaging in November 2011. As a result, the Landsat program is on secure footings and planning is underway to extend the record for another 20 or more years.

Loveland, Thomas R.↗

Completeness Index for Earthquake-Induced Landslide Inventories

Understanding the global relation between Earthquake-Induced Landslides (EQILs) and the factors contributing to their initiation is still an open topic within the geomorphological community. Accessing EQIL inventories and analyzing them concerning their potential causes is the key to explore such relation. However, each of the existing EQIL inventories has its level of completeness and associated uncertainty which makes any unified relationship which is challenging to obtain. So far, the completeness of EQIL inventories has never been clearly defined. As a result, it has never been accounted for in global EQIL predictive models. In this technical note, we propose a simple definition for the completeness of EQIL inventories. We analyze 30 digital EQIL for 21 earthquakes and develop a semi-quantitative method to estimate the completeness level, which we refer to as Completeness Index (CI). The CI results from a combination of topographic factors, ground shaking parameters, and a measure derived from landslide size statistics. The proposed CI consists of Low, Moderate, and High completeness classes which can be used to evaluate any landslide inventory. We made the whole procedure to compute the CI accessible in an ArcGIS toolbox together with a test dataset.

Hakan Tanyas↗

Synthesis of fluorinated radiopharmaceuticals via electrochemical fluorination

Provided herein are methods and compositions for the electrochemical selective radiofluorination of aromatic molecules. The resulting fluorine-18 labeled compounds are ideal radionuclides for use in Positron Emission Tomography (PET); they are also difficult to radiolabel efficiently and with high specific activity using existing approaches. For example, radiopharmaceuticals such as [F18]L-DOPA, which is indispensable in PET brain disease imaging, may be made electrochemically with high radiochemical yield and high specific activity using 18F-. The invention process described herein opens new possibilities and provides wider access to PET tracers such as 18F-L-Dopa, since 18F- is much more widely available than the 18F2, currently used for synthesis of electron rich substrates.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Optimizing Geant4 Hadronic Models

Geant4, the leading detector simulation toolkit used in high energy physics, employs a set of physics models to simulate interactions of particles with matter across a wide range of energies. These models, especially the hadronic ones, rely largely on directly measured cross-sections and inclusive characteristics, and use physically motivated parameters. However, they generally aim to cover a broad range of possible simulation tasks and may not always be optimized for a particular process or a given material. The Geant4 collaboration recently made many parameters of the models accessible via a configuration interface. This opens a possibility to fit simulated distributions to the thin target experimental datasets and extract optimal values of the model parameters and the associated uncertainties. Such efforts are currently undertaken by the Geant4 collaboration with the goal of offering alternative sets of model parameters, also known as "tunes", for certain applications. The effort should subsequently lead to more accurate estimates of the systematic errors in physics measurements given the detector simulation role in performing the physics measurements. Results of the study are presented to illustrate how Geant4 model parameters can be optimized through applying fitting techniques, to improve the agreement between the Geant4 and the experimental data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Metal–Carbodithioate-Based 3D Semiconducting Metal–Organic Framework: Porous Optoelectronic Material for Energy Conversion

Solar energy conversion requires the working compositions to generate photoinduced charges with high potential and the ability to deliver charges to the catalytic sites and/or external electrode. These two properties are typically at odds with each other and call for new molecular materials with sufficient conjugation to improve charge conductivity but not as much conjugation as to overly compromise the optical band gap. In this work, we developed a semiconducting metal-organic framework (MOF) prepared explicitly through metal-carbodithioate"(-CS 2 ) n M" linkage chemistry, entailing augmented metal-linker electronic communication. The stronger ligand field and higher covalent character of metal-carbodithioate linkages-when combined with spirofluorene-derived organic struts and nickel-(II) ion-based nodes-provided a stable, semiconducting 3D-porous MOF, Spiro-CS 2 Ni. This MOF lacks long-range ordering and is defined by a flexible structure with non-aggregated building units, as suggested by reverse Monte Carlo simulations of the pair distribution function obtained from total scattering experiments. The solvent-removed "closed pore"material recorded a Brunauer-Emmett-Teller area of similar to 400m 2 /g, where the "open pore" form possesses90 wt % solvent-accessible porosity. Electrochemical measurements suggest that Spiro-CS 2 Ni possesses a band gap of 1.57 eV(sigma = 10 -7 S/cm at -1.3 V bias potential),which can be further improved by manipulating the d-electron configuration through an axial coordination (ligand/substrate), the latter of which indicates usefulness as an electrocatalyst and/or a photoelectrocatalyst(upon substrate binding). Transient-absorption spectroscopy reveals a long-lived photo-generated charge-transfer state (τ CR = 6.5 mu s) capable of chemical transformation under a biased voltage. Spiro-CS 2 Ni can endure a compelling range of pH(1-12 for weeks) and hours of electrochemical and photoelectrochemical conditions in the presence of water and organic acids. We believe this work provides crucial design principles for low-density, porous,light-energy-conversion materials.

36 MATERIALS SCIENCE↗

Improving and Automating Building Model Data Exchange

There are many instances throughout a project’s lifecycle where there arises a need for quick and accurate risk assessment of building designs. For example, an unexpected design change during construction may necessitate structural engineers to perform a seismic risk assessment on analytical models of the updated building design using high fidelity structural analysis software, such as ANSYS or Abaqus. However, the efficiency of such workflows often depends upon the interoperability of architectural design software and structural analysis software. When the quality of this interoperability is lacking or even non-existent, the efficiency of virtual engineering workflows is hampered, which increases project costs. A McGraw Hill industry survey of professional users of Building Information Modeling (BIM) technologies found that there is high demand for BIM interoperability for structural analysis, but that the value/difficulty ratio is currently too low for practical use. There have been efforts by the academic community to facilitate model data exchange between the architectural design and structural analysis domains, but such solutions have not been widely adopted by industry, face technical challenges, and oftentimes are limited in applicability for users of various BIM software. Therefore, INL is developing capabilities to improve, automate, and generalize model data exchange between architectural BIM software (e.g., Revit) and structural analysis software (e.g., SAP2000, ANSYS). The goal is to help expedite and automate as much of the pre-processing step for creating analytical models in finite element analysis software as reasonably as possible. Such a "BIM-to-FEA" conversion tool should provide direct benefit to end-users through accuracy, automation, quick turn-around, and wide applicability. To generalize the application of this BIM-to-FEA conversion tool and increase its useability among the many different commercial BIM software currently used by industry, the program is being developed with the concept of openBIM. OpenBIM is the application of non-proprietary, open data standards that allow for BIM model data exchange in a format that is accessible, retainable, and useable for all users. The most widely used open, non-proprietary data exchange format for BIM is the Industry Foundation Classes (IFC) schema. IFC is developed by buildingSMART international and is ISO certified (ISO 16739-1:2018). The BIM-to-FEA conversion tool is being developed for compatibility with typical commercial building designs of steel framed structures. The tool is currently capable of importing architectural BIM data of framed building structures, recognizing and extracting the aspects of the model that are required for structural analysis, adjusting the connectivity of frame members, and finally exporting to an analytical model stored in the IFC format. The exported IFC analytical model can then be imported into various openBIM compliant software, such as SAP2000. Such capabilities have already been tested on commercial software, as shown above, and continue to be improved. Work is underway to test the conversion on various commercial BIM software, develop a user-friendly interface, incorporate the program into the broader DeepLynx data warehouse project being developed by INL, and to eventually open-source the tool for the benefit of the community. Future development of the tool envisions the ability for efficient iterative risk assessment of generative building designs, all within a workflow utilizing open-source tools. One such open-source tool will be MOOSE, an advanced finite element analysis tool developed at INL. The conversion tool will also branch out from typical commercial building designs and will aim to incorporate nuclear construction. The aim will be to convert both structural and non-structural components of nuclear facilities, such as curved concrete containment structures and piping systems, respectively.

97 MATHEMATICS AND COMPUTING↗

Data Access Services that Make Remote Sensing Data Easier to Use

This slide presentation reviews some of the processes that NASA uses to make the remote sensing data easy to use over the World Wide Web. This work involves much research into data formats, geolocation structures and quality indicators, often to be followed by coding a preprocessing program. Only then are the data usable within the analysis tool of choice. The Goddard Earth Sciences Data and Information Services Center is deploying a variety of data access services that are designed to dramatically shorten the time consumed in the data preparation step. On-the-fly conversion to the standard network Common Data Form (netCDF) format with Climate-Forecast (CF) conventions imposes a standard coordinate system framework that makes data instantly readable through several tools, such as the Integrated Data Viewer, Gridded Analysis and Display System, Panoply and Ferret. A similar benefit is achieved by serving data through the Open Source Project for a Network Data Access Protocol (OPeNDAP), which also provides subsetting. The Data Quality Screening Service goes a step further in filtering out data points based on quality control flags, based on science team recommendations or user-specified criteria. Further still is the Giovanni online analysis system which goes beyond handling formatting and quality to provide visualization and basic statistics of the data. This general approach of automating the preparation steps has the important added benefit of enabling use of the data by non-human users (i.e., computer programs), which often make sub-optimal use of the available data due to the need to hard-code data preparation on the client side.

Lynnes, Christopher↗

The Science Discovery Engine: An Open Science Success Story

NASA is committed to building an inclusive open science community over the next decade and is championing the new Open-Source Science Initiative (OSSI) to foster that community. The OSSI is made up of a number of activities including the development of an empowering cyberinfrastructure to accelerate the time to actionable science. One component of the OSSI cyberinfrastructure is the Science Discovery Engine (SDE). The goal of the SDE is to enable the discovery of data, software and documentation across the five SMD divisions including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics and Planetary Science. The SDE increases accessibility to the wealth of NASA’s open science data and information. In this presentation, we will present our collaborative work to date to build the SDE and our vision for empowering open source science in the future.

Kaylin Bugbee↗

Regio- and Stereoselective Lactone Polymerization: Divergent Effect of Catalyst Modification and Monomer Structure

Selective ring-opening polymerization (ROP) of chiral lactones enables access to biodegradable polyesters with precisely controlled microstructures. Here, combined DFT modeling and experimental validation elucidate how fine-tuning of enantiopure SalBinam aluminum catalysts (through introduction of bromine atoms and tert-butyl groups, respectively, in ortho- and para-positions) modulates regio- and stereocontrol in the ROP of methyl glycolide (MeG) and lactide (LA). Computations reveal that regioselectivity in MeG polymerization arises mainly from steric repulsion, with a small contribution from weak stabilizing C-H···Br interactions that favor ring-opening at the glycolic site, consistent with the experimentally enhanced regioselectivity for (R)-MeG. In contrast, the same steric congestion at the ligand’s ortho positions destabilizes the key transition states in rac-LA polymerization, reducing the calculated stereoselectivity. Experiments confirm the predicted loss of stereocontrol, yielding nearly atactic PLA under standard conditions. Extension of the computational framework to rac-MeG polymerization promoted by racemic catalyst identified a low-barrier, stepwise polymer chain exchange pathway that rationalizes the experimentally observed syndiotacticity of poly(lactic-co-glycolic acid).

DFT calculations↗

A standardized workflow for kinetic metabolic model curation and dissemination

Kinetic metabolic models provide invaluable insights into cellular metabolism, supporting applications in synthetic biology, metabolic engineering, and systems biology. However, reproducibility and utility of these models hinge on clear and rigorous documentation, standardized annotation, and accessible visualization. This paper presents a workflow for building, annotating, visualizing, and sharing kinetic metabolic models. Our method integrates community standards and open-source tools to ensure reproducibility, interoperability, and user accessibility. This procedure enables researchers to produce reusable and well-documented kinetic models, advancing their role as powerful tools in metabolic research.

Cook, Margaret [Univ. of Washington, Seattle, WA (↗

AI Curation Methods for NASA Scientific Data

The NASA Open Science Data Repository (OSDR) serves as a central hub for sharing and accessing NASA's vast collection of scientific data, supporting researchers across diverse fields. To enhance the efficiency, accuracy, and accessibility of this data, we are leveraging advanced artificial intelligence (AI) techniques as part of the AI for Curation project. By integrating large language models (LLMs) into our data curation workflow, we aim to streamline the entire process—from data submission to user interaction. This initiative focuses on improving key areas, including data ingestion, curation, and user engagement with curated datasets, impacting multiple domains and a wide user base. First, we are developing tools that can automatically parse data in various formats, using LLMs to convert unstructured data into structured, standardized formats. This reduces the manual effort required for curation, allowing curators to focus on more critical scientific analyses. Additionally, AI and machine learning (ML) models are being implemented to automate data validation and verification, ensuring the highest standards of data quality and reliability. Finally, we are creating a conversational AI agent to interact with the curated scientific studies in OSDR, helping users easily navigate the repository and access relevant data. By enhancing data discoverability and accessibility, these advancements will foster new research opportunities and promote the principles of open science.

Walter Alvarado↗

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

54 ENVIRONMENTAL SCIENCES↗

Miniature Trace Gas Detector Based on Microfabricated Optical Resonators

While a variety of techniques exist to monitor trace gases, methods relying on absorption of laser light are the most commonly used in terrestrial applications. Cavity-enhanced absorption techniques typically use high-reflectivity mirrors to form a resonant cavity, inside of which a sample gas can be analyzed. The effective absorption length is augmented by the cavity's high quality factor, or Q, because the light reflects many times between the mirrors. The sensitivity of such mirror-based sensors scales with size, generally making them somewhat bulky in volume. Also, specialized coatings for the high-reflectivity mirrors have limited bandwidth (typically just a few nanometers), and the delicate mirror surfaces can easily be degraded by dust or chemical films. As a highly sensitive and compact alternative, JPL is developing a novel trace gas sensor based on a monolithic optical resonator structure that has been modified such that a gas sample can be directly injected into the cavity. This device concept combines ultra-high Q optical whispering gallery mode resonators (WGMR) with microfabrication technology used in the semiconductor industry. For direct access to the optical mode inside a resonator, material can be precisely milled from its perimeter, creating an open gap within the WGMR. Within this open notch, the full optical mode of the resonator can be accessed. While this modification may limit the obtainable Q, calculations show that the reduction is not significant enough to outweigh its utility for trace gas detection. The notch can be milled from the high- Q crystalline WGMR with a focused ion beam (FIB) instrument with resolution much finer than an optical wavelength, thereby minimizing scattering losses and preserving the optical quality. Initial experimental demonstrations have shown that these opened cavities still support high-Q whispering gallery modes. This technology could provide ultrasensitive detection of a variety of molecular species in an extremely compact and robust package. With this type of modified WGMR, one can inject a gas sample into the open gap, allowing highly sensitive trace molecule detection within a roughly 1-cm volume. Other critical components of the instrument, such as the detector and a semiconductor laser, could be directly packaged with the resonator so as to not significantly increase the size of the device. Besides its low mass, volume, and power consumption, the monolithic design makes these resonators intrinsically robust devices, capable of handling significant temperature excursions, without moving parts to wear out or delicate coatings that can be easily damaged. A sensor could integrate with microfluidics technology for a chip-scale device. It could be mounted to the end of a deployable arm, or inserted into a borehole. Also, a network of individual sensors could be dispersed to monitor conditions over a wide region

Aveline, David C.↗

Informing Wildfire Needs: The Expanded User Interface of NASA's Fire Information for Resource Management System (Firms)

As the global community continues to experience, and respond to, living in a changing environment, access to tools, technologies, and timely data utilized by an increasingly diverse set of stakeholders is increasing. This year, 2023, has thus far seen an unprecedented number of extreme events, increasingly driven by changes in the climate and a strong 2023 ENSO pattern. In Canada, a record number of wildfires, and associated weather events, evacuations, and infrastructure and habitat destruction has taken place, and is ongoing. Large swaths of Greece have experienced similar wildfire destruction. Most recently, Maui has experienced destructive wildfires, and early 2023 saw massive wildfires in Chile. NASA's Fire Information for Resource Management System, or FIRMS, has a fifteen-year history of providing timely and comprehensive data and information on wildfires to stakeholders. FIRMS was initially developed in 2007 by the University of Maryland, with funds from NASA's Applied Sciences Program and the United Nations Food and Agriculture Organization (UN FAO), to provide near real-time active fire Locations to natural resource managers that faced challenges obtaining timely satellite-derived fire information. FIRMS has consistently evolved to address the needs of stakeholders Living in a changing environment; in 2012 it transitioned to NASA LANCE and in 2021 through a partnership between NASA and the US Forest Service, an updated version of FIRMS was released for the US and Canada. As NASA and other federal agencies continue to accelerate Open Science through integrated efforts such as the Year of Open Science, the provision of readily discoverable, findable, accessible, interoperable, reusable data represents a major focus to facilitate equitable outcomes. FIRMS supports this acceleration in Open Science by continuing to provision data and information for its traditional user base, while addressing the novel user needs of an increasingly diverse set of stakeholders seeking robust, reliable, transparently generated data and information. Increasingly, FIRMS is utilized by citizen scientists and individuals directly affected by wildfires - through evacuations, risks to structures/homes, poor air quality. etc. FIRMS has also been Leveraged to detect and assess the impacts resulting from ongoing conflicts. This further highlights the multi-faceted impacts of wildfires and other events. In the Fall of 2023, FIRMS will release an expanded User Interface (UI). This interface captures and reflects the needs of, and input from, a multitude of users. These users range from federal agency representatives to non-government organizations to the private sector to citizen science entities. To respond to this expansive and diverse user need base, the updated FIRMS UI will capture a range of features to support those beginning to explore the range of data and tools available to inform wildfire awareness and knowledge. These users are supported through a Basic Mode interface, furnishing access to a light set of functionalities that provision straight-forward, readily usable information and data, and ingestible knowledge. The Advanced Mode interface supports those stakeholder groups already proficient in navigating FIRMS. These stakeholders, representing fire managers and others, perform active fire management and tactical wildfire response activities. For these stakeholders, additional datasets have been included which require in-depth knowledge of both the utility as well as the caveats of such datasets. Additional functionalities have also been embedded to aid specific user queries. The expanded UI will introduce a new Experimental Mode. The focus of this UI will be to support the provision of emerging and innovative datasets that are in development for review and comment by the user community Examples include post-fire products generated by NASA's Earth Information System (EIS) Fire. This presentation will provide an overview of the expanded FIRMS UI. We will discuss how this UI is designed to be scalable and support the unique needs of an expanding and diverse user base. We will highlight key features, elements, and datasets, and describe how user needs have informed and guided the design of the UI. We will also share recent use cases to convey, and increase awareness, among conference participants. As the global community faces more extreme wildfires, due to climate variability and change, there is an increased need for reliable data to inform, manage, and mitigate the impacts of these events. Through this work, NASA FIRMS is striving to level the playing field, by making information accessible to all; from policy makers to the private sector to historically marginalized communities. In doing so, NASA is promoting the all-hands-on-deck response needed to minimize the impacts of wildfires and harness the strengths of open science to address the greatest environmental challenge faced.

Jenny Hewson↗

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗

Direct Measurement of Terahertz Conductivity in a Gated Monolayer Semiconductor

Two-dimensional semiconductors and their moiré superlattices have emerged as important platforms for investigating correlated electrons. However, many key properties of these systems, such as the frequency-dependent conductivity, remain experimentally inaccessible because of the mesoscopic sample size. Here we report a technique to directly measure the complex conductivity of electrostatically gated two-dimensional semiconductors in the terahertz frequency range. Applying this technique to a WSe2 monolayer encapsulated in hBN, we observe a clear Drude-like response between 0.1 and 1 THz, in a density range challenging to access even in DC transport. Our work opens a new avenue for studying tunable van der Waals heterostructures using terahertz spectroscopy.

2D semiconductors↗

Unconventional self-similar Hofstadter superconductivity from repulsive interactions

Abstract Fractal Hofstadter bands have become widely accessible with the advent of moiré superlattices, opening the door to studies of the effect of interactions in these systems. In this work we employ a renormalization group (RG) analysis to demonstrate that the combination of repulsive interactions with the presence of a tunable manifold of Van Hove singularities provides a new mechanism for driving unconventional superconductivity in Hofstadter bands. Specifically, the number of Van Hove singularities at the Fermi energy can be controlled by varying the flux per unit cell and the electronic filling, leading to instabilities toward nodal superconductivity and chiral topological superconductivity with Chern number $${{{{{{{\mathcal{C}}}}}}}}=\pm 6$$ C = ± 6 . The latter is characterized by a self-similar fixed trajectory of the RG flow and an emerging self-similarity symmetry of the order parameter. Our results establish Hofstadter quantum materials such as moiré heterostructures as promising platforms for realizing novel reentrant Hofstadter superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗