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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4

Enabling Autonomous Electron Microscopy for Networked Computation and Steering

Advanced electron microscopy workflows require an ecosystem of microscope instruments and computing systems possibly located at different sites to conduct remotely steered and automated experiments. Current workflow executions involve manual operations for steering and measurement tasks, which are typically performed from control workstations co-located with microscopes; consequently, their operational tempo and effectiveness are limited. We propose an approach based on separate data and control channels for such an ecosystem of Scanning Transmission Electron Microscopes (STEM) and computing systems, for which no general solutions presently exist, unlike the neutron and light source instruments. We demonstrate automated measurement transfers and remote steering of Nion STEM physical instruments over site networks. We propose a Virtual Infrastructure Twin (VIT) of this ecosystem, which is used to develop and test our steering software modules without requiring access to the physical instrument infrastructure. Additionally, we develop a VIT for a multiple laboratory scenario, which illustrates the applicability of this approach to ecosystems connected over wide-area networks, for the development and testing of software modules and their later field deployment.

Al Najjar, Anees↗

Do We Really Need All That Data: From Data to Agency in Automated Microscopy

Microscopy is entering an era of automated laboratories and AI-enabled instruments, often justified by a simple narrative of automating experiments to collect more data and train better models. In this work, we argue that, for microscopy, this framing is incomplete and can be counterproductive.

97 MATHEMATICS AND COMPUTING↗

Perspectives for self-driving labs in synthetic biology

Self-driving labs (SDLs) combine fully automated experiments and data collection with artificial intelligence (AI) and control algorithms that decide not only the set of parameters for the next experiment, but also potentially which scientific hypotheses to test. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. Whereas there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single, easily accessible, target for affecting the incredibly wide repertoire of biological cell behavior. Since they can provide large amounts of high-quality data, SDLs can be a platform for AI to develop approaches to systematically convert data into scientific knowledge systems. These knowledge systems can be used both to understand the biological world and to design bioengineered systems to fit a desired specification (inverse design). However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Building Atomic and Plasmonic Devices via Electron Beams: from Desired Structures to Desired Properties

The evolution of the aberration correction in Scanning Transmission Electron Microscopy (STEM) has enabled multiple advances including high-resolution structural imaging, pm-level position detection of atomic columns, and ~3-5 mV resolution electron energy loss spectroscopy of the chemical and physical functionalities. These developments have further enabled the precise manipulation of the atomic structure of materials, including removal and formation of atomic planes in 3D materials, controlled atomic motion, and even direct atomic assembly of homo- and heteroatomic artificial molecules. Here, we will discuss several recent advances in STEM-EELS automated experiments as applied to quantum and nanoplasmonic systems.

42 ENGINEERING↗

Invariant discovery of features across multiple length scales: Applications in microscopy and autonomous materials characterization

Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images encapsulate crucial data regarding atomic bonding, materials microstructures, and dynamic phenomena such as microstructural evolution and turbulence, among other phenomena. The challenge lies in effectively extracting and interpreting this information. Variational Autoencoders (VAEs) have emerged as powerful tools for identifying the underlying factors of variation in image data, providing a systematic approach to distilling meaningful patterns from complex data sets. However, a significant hurdle in their application is the definition and selection of appropriate descriptors reflecting local structures. Here, we introduce the scale-invariant VAE approach (SI-VAE) based on the progressive training of the VAE with the descriptors sampled at different length scales. The SI-VAE allows the discovery of the length scale-dependent factors of variation in the system. Here, we illustrate this approach using the ferroelectric domain images and generalize it to the movies of the electron-beam induced phenomena in graphene and topography evolution across combinatorial libraries. This approach can further be used to initialize the decision making in automated experiments including structure–property discovery and can be applied across a broad range of imaging methods. This approach is universal and can be applied to any spatially resolved data including both experimental imaging studies and simulations, and can be particularly useful for exploration of phenomena such as turbulence and scale-invariant transformation fronts.

36 MATERIALS SCIENCE↗

Building MCP-native hierarchical AI scientist ecosystems: a perspective on scaling multi-agent scientific discovery

Large language models (LLMs) are evolving from chatbots with limited tool-using capabilities to agentic AI systems that can perform deep research, assist in proposing hypotheses, help design experiments, automate data analysis, and draft scientific reports. However, there are currently two bottlenecks limiting LLMs' real-world impact on the broader scientific research community beyond academic demonstrations: lack of interoperability (repetitive manual tool-integration is required across scenarios) and the need for scalable coordination (unstructured communication and memory become brittle as the number of agents grows). In this Perspective, we argue that the next phase of agentic scientific discovery requires the development of an ecosystem of protocol-native agents and tools organized through hierarchies inspired by human society, beyond the current paradigm of a single monolithic “AI scientist”. We use Model Context Protocol (MCP) as a concrete example of an emerging interoperability layer for scientific tool and context exchange, and we propose three complementary pathways to increase the scaling capabilities of an MCP-native scientific ecosystem by addressing the composability issues: (1) MCP servers for high-value scientific tools maintained by domain experts, (2) automated transformation of existing code repositories into MCP services, and (3) autonomous invention and evolution of new agents and workflows. Finally, we provide a practical roadmap for scaling AI-driven scientific discovery by expanding tool supply and coordination in MCP-native scientific ecosystems.

97 MATHEMATICS AND COMPUTING↗

Modern Trends in Neutron Scattering Instrument Technologies

This article reviews some current trends that can be observed in the development of neutron scattering instrument technologies. While the number of neutron scattering facilities worldwide and the number of beam days they offer are largely stable, their scientific impact is increasing through improving instrumental capabilities, new and more versatile instruments, and more efficient data collection protocols. Neutron beams are becoming smaller but more intense, and instruments are being designed to utilize more ‘useful’ neutrons in unit time. This article picks and discusses a few recent developments in the areas of integrated source and instrument design, use of computational tools, new detectors, and experiment automation.

47 OTHER INSTRUMENTATION↗

Application of parallel distributed processing to space based systems

The concept of using Parallel Distributed Processing (PDP) to enhance automated experiment monitoring and control is explored. Recent very large scale integration (VLSI) advances have made such applications an achievable goal. The PDP machine has demonstrated the ability to automatically organize stored information, handle unfamiliar and contradictory input data and perform the actions necessary. The PDP machine has demonstrated that it can perform inference and knowledge operations with greater speed and flexibility and at lower cost than traditional architectures. In applications where the rule set governing an expert system's decisions is difficult to formulate, PDP can be used to extract rules by associating the information an expert receives with the actions taken.

Macdonald, J. R.↗

Measurement Protocols for In situ Analysis of Organic Compounds at Mars and Comets

The determination of the abundance and chemical and isotopic composition of organic molecules in comets and those that might be found in protected environments at Mars is a first step toward understanding prebiotic chemistries on these solar system bodies. While future sample return missions from Mars and comets will enable detailed chemical and isotopic analysis with a wide range of analytical techniques, precursor insitu investigations can complement these missions and facilitate the identification of optimal sites for sample return. Robust automated experiments that make efficient use of limited spacecraft power, mass, and data volume resources are required for use by insitu missions. Within these constraints we continue to explore a range of instrument techniques and measurement protocols that can maximize the return from such insitu investigations.

Mahaffy, P. R.↗

Measurement Protocols for In Situ Analysis of Organic Compounds at Mars and Comets

The determination of the abundance and chemical and isotopic composition of organic molecules in comets and those that might be found in protected environments at Mars is a first step toward understanding prebiotic chemistries on these solar system bodies. While future sample return missions from Mars and comets will enable detailed chemical and isotopic analysis with a wide range of analytical techniques, precursor insitu investigations can complement these missions and facilitate the identification of optimal sites for sample return. Robust automated experiments that make efficient use of limited spacecraft power, mass, and data volume resources are required for use by insitu missions. Within these constraints we continue to explore a range of instrument techniques and measurement protocols that can maximize the return from such insitu investigations.

Mahaffy, P. R.↗

Mechanical Analog Approach to Parameter Estimation of Lateral Spacecraft Fuel Slosh

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. Even with modern computing systems, CFD type simulations are not fast enough to allow for large scale Monte Carlo analyses of spacecraft and launch vehicle dynamic behavior with slosh included. Simplified mechanical analogs for the slosh are preferred during the initial stages of design to reduce computational time and effort to evaluate the Nutation Time Constant (NTC). Analytic determination of the slosh analog parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices such as elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks, these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the hand-derived equations of motion for the mechanical analog are evaluated and their results compared with the experimental results. Of particular interest is the effect of diaphragms and bladders on the slosh dynamics and how best to model these devices. An experimental set-up is designed and built to include a diaphragm in the simulated spacecraft fuel tank subjected to lateral slosh. This research paper focuses on the parameter estimation of a SimMechanics model of the simulated spacecraft propellant tank with and without diaphragms using lateral fuel slosh experiments. Automating the parameter identification process will save time and thus allow earlier identification of potential vehicle problems.

Chatman, Yadira↗

Remotely Controlled Mixers for Light Microscopy Module (LMM) Colloid Samples

Developed by NASA Glenn Research Center, the LMM aboard the International Space Station (ISS) is enabling multiple biomedical science experiments. Techshot, Inc., has developed a series of colloid specialty cell systems (C-SPECS) for use in the colloid science experiment module on the LMM. These low-volume mixing devices will enable uniform particle density and remotely controlled repetition of LMM colloid experiments. By automating the experiment process, C-SPECS allow colloid samples to be processed more quickly. In addition, C-SPECS will minimize the time the crew will need to spend on colloid experiments as well as eliminate the need for multiple and costly colloid samples, which are expended after a single examination. This high-throughput capability will lead to more efficient and productive use of the LMM. As commercial launch vehicles begin routine visits to the ISS, C-SPECS could become a significant means to process larger quantities of high-value materials for commercial customers.

Kurk, Michael A. (Andy)↗

ARC Cell Science Validation (CS-V) Payload Overview

Automated cell biology system for laboratory and International Space Station (ISS) National Laboratory research. Enhanced cell culture platform that provides undisturbed culture maintenance, including feedback temperature control, medical grade gas supply, perfusion nutrient delivery and removal of waste, and automated experiment manipulations. Programmable manipulations include: media feeds change out, injections, fraction collections, fixation, flow rate, and temperature modification within a one-piece sterile barrier flow path. Cassette provides 3 levels of containment and allows Crew access to the bioculture chamber and flow path assembly for experiment initiation, refurbishment, or sample retrieval and preservation.

Space Biology↗

A Comparison of a Brain-Based Adaptive System and a Manual Adaptable System for Invoking Automation

Two experiments are presented that examine alternative methods for invoking automation. In each experiment, participants were asked to perform simultaneously a monitoring task and a resource management task as well as a tracking task that changed between automatic and manual modes. The monitoring task required participants to detect failures of an automated system to correct aberrant conditions under either high or low system reliability. Performance on each task was assessed as well as situation awareness and subjective workload. In the first experiment, half of the participants worked with a brain-based system that used their EEG signals to switch the tracking task between automatic and manual modes. The remaining participants were yoked to participants from the adaptive condition and received the same schedule of mode switches, but their EEG had no effect on the automation. Within each group, half of the participants were assigned to either the low or high reliability monitoring task. In addition, within each combination of automation invocation and system reliability, participants were separated into high and low complacency potential groups. The results revealed no significant effects of automation invocation on the performance measures; however, the high complacency individuals demonstrated better situation awareness when working with the adaptive automation system. The second experiment was the same as the first with one important exception. Automation was invoked manually. Thus, half of the participants pressed a button to invoke automation for 10 s. The remaining participants were yoked to participants from the adaptable condition and received the same schedule of mode switches, but they had no control over the automation. The results showed that participants who could invoke automation performed more poorly on the resource management task and reported higher levels of subjective workload. Further, those who invoked automation more frequently performed more poorly on the tracking task and reported higher levels of subjective workload. and the adaptable condition in the second experiment revealed only one significant difference: the subjective workload was higher in the adaptable condition. Overall, the results show that a brain-based, adaptive automation system may facilitate situation awareness for those individuals who are more complacent toward automation. By contrast, requiring operators to invoke automation manually may have some detrimental impact on performance but does appear to increases subjective workload relative to an adaptive system.

Bailey, Nathan R.↗

APGEN Scheduling: 15 Years of Experience in Planning Automation

In this paper, we discuss the scheduling capability of APGEN (Activity Plan Generator), a multi-mission planning application that is part of the NASA AMMOS (Advanced Multi- Mission Operations System), and how APGEN scheduling evolved over its applications to specific Space Missions. Our analysis identifies two major reasons for the successful application of APGEN scheduling to real problems: an expressive DSL (Domain-Specific Language) for formulating scheduling algorithms, and a well-defined process for enlisting the help of auxiliary modeling tools in providing high-fidelity, system-level simulations of the combined spacecraft and ground support system.

sequencing↗