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DOE OSTI2026

Bioproduction, bioprotection, and biocontainment in multi-kingdom microbial systems with 3D spatial control

Engineered living materials (ELMs) are a class of hybrid materials that include engineered microbes encapsulated by a polymer matrix. The biotic and abiotic components define the ELMs design space and can be altered to improve performance and function. While current synthetic materials in the field display robust biocompatibility with both native and engineered living systems, we have a limited understanding of how to leverage three-dimensional (3D) form factors to spatially organize and control microbial dynamics within the material. Motivated by this knowledge gap, we employed extrusion-based 3D printing to fabricate multi-kingdom hydrogel constructs for the encapsulation of both single and multi-kingdom microbial systems. Core–shell cubic constructs enabled the spatial organization of a constitutive multi-kingdom system of levodopa (L-DOPA)-producing E. coli and betaxanthins (BXN)-producing S. cerevisiae. This spatial organization in 3D materials can introduce precise control over bioproduction, bioprotection, and biocontainment features that are critical to the efficacy of current ELMs. The relative spatial organization of the organisms, as well as the surface area-to-volume ratio were investigated to determine how these design elements impact microbial behavior (metabolite production, growth, expression, and cell distribution) over time. We demonstrated that F127-bis-urethane methacrylate (F127-BUM) core–shell geometries enable the hierarchical 3D printing of multi-kingdom constructs, offering customizable control over bioproduction, bioprotection, and biocontainment. With the optimization of these core–shell structures for continuous bioproduction, these ELMs could be deployed as compact and sustainable bioreactors in remote environments.

additive manufacturing↗

NASA NTRS2001

Case-Based Capture and Reuse of Aerospace Design Rationale

The goal of this project was to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project combined case-based reasoning (CBR) and concept maps (CMaps) to develop methods for capturing, organizing, and interactively accessing records of experiences encapsulating the methods and rationale underlying expert aerospace design, in order to bring the captured knowledge to bear to support future reasoning. The project's results contribute both principles and methods for effective design-aiding systems that aid capture and access of useful design knowledge. The project has been guided by the tenets that design-aiding systems must: (1) Leverage a designer's knowledge, rather than attempting to replace it; (2) Be able to reflect different designers' differing conceptualizations of the design task, and to clarify those conceptualizations to others; (3) Include capabilities to capture information both by interactive knowledge modeling and during normal use; and (4) Integrate into normal designer tasks as naturally and unobtrusive as possible.

Leake, David B.↗

NASA NTRS1994

Collaborative engineering-design support system

Designing engineering objects requires many engineers' knowledge from different domains. There needs to be cooperative work among engineering designers to complete a design. Revisions of a design are time consuming, especially if designers work at a distance and with different design description formats. In order to reduce the design cycle, there needs to be a sharable design describing the engineering community, which can be electronically transportable. Design is a process of integrating that is not easy to define definitively. This paper presents Design Script which is a generic engineering design knowledge representation scheme that can be applied in any engineering domain. The Design Script is developed through encapsulation of common design activities and basic design components based on problem decomposition. It is implemented using CLIPS with a Windows NT graphical user interface. The physical relationships between engineering objects and their subparts can be constructed in a hierarchical manner. The same design process is repeatedly applied at each given level of hierarchy and recursively into lower levels of the hierarchy. Each class of the structure can be represented using the Design Script.

Lee, Dong HO↗

NASA NTRS2007

Systems Modeling to Implement Integrated System Health Management Capability

ISHM capability includes: detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, and user interfaces that enable integrated awareness (past, present, and future) by users. This is achieved by focused management of data, information and knowledge (DIaK) that will likely be distributed across networks. Management of DIaK implies storage, sharing (timely availability), maintaining, evolving, and processing. Processing of DIaK encapsulates strategies, methodologies, algorithms, etc. focused on achieving high ISHM Functional Capability Level (FCL). High FCL means a high degree of success in detecting anomalies, diagnosing causes, predicting future anomalies, and enabling health integrated awareness by the user. A model that enables ISHM capability, and hence, DIaK management, is denominated the ISHM Model of the System (IMS). We describe aspects of the IMS that focus on processing of DIaK. Strategies, methodologies, and algorithms require proper context. We describe an approach to define and use contexts, implementation in an object-oriented software environment (G2), and validation using actual test data from a methane thruster test program at NASA SSC. Context is linked to existence of relationships among elements of a system. For example, the context to use a strategy to detect leak is to identify closed subsystems (e.g. bounded by closed valves and by tanks) that include pressure sensors, and check if the pressure is changing. We call these subsystems Pressurizable Subsystems. If pressure changes are detected, then all members of the closed subsystem become suspect of leakage. In this case, the context is defined by identifying a subsystem that is suitable for applying a strategy. Contexts are defined in many ways. Often, a context is defined by relationships of function (e.g. liquid flow, maintaining pressure, etc.), form (e.g. part of the same component, connected to other components, etc.), or space (e.g. physically close, touching the same common element, etc.). The context might be defined dynamically (if conditions for the context appear and disappear dynamically) or statically. Although this approach is akin to case-based reasoning, we are implementing it using a software environment that embodies tools to define and manage relationships (of any nature) among objects in a very intuitive manner. Context for higher level inferences (that use detected anomalies or events), primarily for diagnosis and prognosis, are related to causal relationships. This is useful to develop root-cause analysis trees showing an event linked to its possible causes and effects. The innovation pertaining to RCA trees encompasses use of previously defined subsystems as well as individual elements in the tree. This approach allows more powerful implementations of RCA capability in object-oriented environments. For example, if a pressurizable subsystem is leaking, its root-cause representation within an RCA tree will show that the cause is that all elements of that subsystem are suspect of leak. Such a tree would apply to all instances of leak-events detected and all elements in all pressurizable subsystems in the system. Example subsystems in our environment to build IMS include: Pressurizable Subsystem, Fluid-Fill Subsystem, Flow-Thru-Valve Subsystem, and Fluid Supply Subsystem. The software environment for IMS is designed to potentially allow definition of any relationship suitable to create a context to achieve ISHM capability.

Figueroa, Jorge F.↗

DOE OSTI2016

Engineering self-assembled bioreactors from protein microcompartments

The goals of this research are to understand how organisms such as bacteria segregate certain metabolic processes inside of specific structures, or “microcompartments,” in the cell and apply this knowledge to develop novel engineered microcompartments for use in nanotechnology and metabolic engineering. For example, in some bacteria, self-assembling protein microcompartments called carboxysomes encapsulate the enzymes involved in carbon fixation, enabling the cell to utilize carbon dioxide more effectively than if the enzymes were free in the cell. The proposed research will determine how structures such as carboxysomes assemble and function in bacteria and develop a means for creating novel, synthetic microcompartments for optimizing production of specific energy-rich compounds.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2015

Industrialization of Space: Microgravity Based Opportunities for Material and Life Science

Microgravity based commercial opportunities are broad, with applications ranging from fiber optics, device-grade semiconductor crystals, space beads, new materials, cell micro encapsulation, 3D tissues and cell cultures, genetic and molecular changes of immune suppression, protein and virus crystal growth, perfume and hair care. To date, primarily the knowledge gained from observing and understanding new end states of systems unraveled in microgravity has been translated into unique technologies and business opportunities on Earth. In some instances existing light qualified hardware is immediately available for commercial RD for small scale in-space manufacturing. Overall products manufactured in microgravity have key properties usually surpassing the best terrestrial counterparts. The talk will address the potential benefits of microgravity research for a variety of terrestrial markets. Our findings originate from discussions with 100+ non-aerospace private companies among the high-tech Silicon Valley ecosystem, show that the opportunities and benefits of using the ISS are largely not considered by experts, primarily due to a lack of awareness of the breadth of terrestrial applications that have been enabled or enhanced by microgravity RD. Based on this dialogue, the concept of microgravity verticals is developed to translate the benefits of the microgravity environment into blue ocean business opportunities for various key US commercial sectors.

technical risk↗

DOE OSTI2022

Degradation of Edge-Defined Film-Fed Silicon Glass–Glass Modules on Florida Rooftop After 22 Years

Thin silicon (< 100 μm) adoption can provide significantly lower cost. Kerfless technologies provide thin wafers while preventing material from being wasted. Understanding how this family of processing influences module reliability is important. A set of four edge-defined film-fed growth (EFG) silicon modules from a ten-module system in Florida is measured after 22 years of exposure. Power loss rates of 0.58–0.78% year -1 are measured for three modules, while a rate of 1.32% is measured for a module with severe delamination and corrosion. Short-circuit current degrades between 10.7% and 13.1% for all modules. Further, the losses are primarily optical and recombination based; however, series and shunt resistance effects play a non-negligible role. Pre-existing recombination losses exist but are exacerbated via degradation. Optical losses in short-circuit current are due in part to encapsulant yellowing. Electroluminescence (EL) images display the effects of processing on bulk quality by clearly showing lines of alternating brightness along the wafer length. To the authors’ knowledge, this is the first article displaying suns–V OC data, effective lifetime versus excess carrier density data, and module EL images for EFG silicon-based modules.

36 MATERIALS SCIENCE↗

NASA NTRS1977

Investigation of test methods, material properties and processes for solar cell encapsulants

The potentially useful encapsulating materials for Task 3 of the Low-Cost Silicon Solar Array project were studied to identify, evaluate, and recommend encapsulant materials and processes for the production of cost-effective, long-life solar cell modules. Materials for study were chosen on the basis of existing knowledge of generic chemical types having high resistance to environmental weathering. The materials varied from rubbers to thermoplastics and presented a broad range of mechanical properties and processing requirements. Basic physical and optical properties were measured on the polymers and were redetermined after exposure to indoor artificial accelerated aging conditions covering four time periods. Strengths and weaknesses of the various materials were revealed and data was accumulated for the development of predictive methodologies. To date, silicone rubbers, fluorocarbons, and acrylic polymers appear to have the most promising combination of characteristics. The fluorocarbons may be used only as films, however, because of their high cost.

Willis, P. B.↗

NASA NTRS1990

Rule induction techniques

Expert System technology is receiving more and more consideration these days when it comes time for selecting an implementation paradigm. As people become educated as to which domains Expert Systems technology can be appropriately utilized and to what extent this capability can be made useful, they will want to extend this ability to encompass greater responsibilities of their everyday routines. Knowledge Acquisition is one of the most time-consuming phases of an Expert System development process. One must extract the essential knowledge from a source by whatever means, and transform this knowledge into a representation that can be demonstrated. Rule Induction is one technique that can be applied to the knowledge acquisition process for certain example-based problems. Spread Sheets and Data Bases for example, may contain columns of information (criteria) to be used in some sort of decision making policy. These criteria could automatically be converted (represented) into production rules that output an appropriate decision dependent upon a given set of criteria. To generalize this concept, we could state that Rule Induction is the process of generating a Knowledge Base from a given set of examples. Through the use of Rule Induction, I will explain how I took information from a database and generated rules encapsulating the information contained within the database.

Young, Gary B.↗

NASA NTRS1999

Synthesis of Graphite Encapsulated Metal Nanoparticles and Metal Catalyzed Nanotubes

This work focuses on the growth and inception of graphite encapsulated metal nanoparticles and metal catalyzed nanotubes using combustion chemistry. Deciphering the inception and growth mechanism(s) for these unique nanostructures is essential for purposeful synthesis. Detailed knowledge of these mechanism(s) may yield insights into alternative synthesis pathways or provide data on unfavorable conditions. Production of these materials is highly desirable given many promising technological applications.

vanderWal, R. L.↗

NASA NTRS2007

Adaptive Modeling of the International Space Station Electrical Power System

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

Thomas, Justin Ray↗

DOE OSTI2021

Guest-Host Interactions in Clathrate Hydrates: Benchmark MP2 and CCSD(T)/CBS Binding Energies of CH4, CO2 and H2S in (H2O)20 Cages

We present benchmark binding energies of naturally occurring gas molecules CH4, CO2, and H2S in the small cage, namely the pentagonal dodecahedron (512) (H2O)20, which is one of the constituent cages of the 3 major lattices (structures I, II and H) of clathrate hydrates. These weak interactions require higher levels of electron correlation and converge slowly with increasing basis set to the Complete Basis Set (CBS) limit, necessitating the use of large basis sets up to the augcc- pV5Z and subsequent correction for Basis Set Superposition Error (BSSE). For the host hollow (H2O)20 cages we have identified a most stable isomer with binding energy of -200.8 ± 2.1 kcal/mol at the CCSD(T)/CBS limit (-199.2 ± 0.5 kcal/mol at the MP2/CBS limit). Additionally, we report converged second order Moller-Plesset (MP2) CBS binding energies for the encapsulation of guests in the (H2O)20 cage of -4.3 ± 0.1 for CH4@(H2O)20, -6.6 ± 0.1 for CO2@(H2O)20 and -8.5 ± 0.1 kcal/mol for H2S@(H2O)20, respectively. For CH4@(H2O)20, exhibiting the weakest encapsulation affinity among the three, we report CCSD(T)/aug-cc-pVTZ binding energies and, based on them, a CCSD(T)/CBS estimate of -4.75 ± 0.1 kcal/mol. To the best of our knowledge, the CCSD(T)/aug-cc-pVTZ calculation for CH4@(H2O)20 is the largest one reported to date (168 valence electrons, 1978 basis functions and the correlation of 84 doubly occupied and 1873 virtual orbitals) and required a scalable implementation of the (T) module on 6144 nodes (350208 cores) of the “Cori” supercomputer at the National Energy Research Supercomputing Center (NERSC) for a total execution time of 195 minutes (for the (T) part). These efficient scalable implementations of highly correlated methods offer the capability to obtain long-lasting benchmarks of intermolecular interactions in complex systems. They also provide a path towards parametrizing classical potentials needed to study the dynamical and transport properties in these complex systems as well as assess the accuracy of lower scaling electronic structure methods such as Density Functional Theory (DFT) and MP2 including its spin-biased variants.

Heindel, Joseph↗

NASA NTRS1998

Formal Modeling of Multi-Agent Systems using the Pi-Calculus and Epistemic Logic

Multi-agent systems have become important recently in computer science, especially in artificial intelligence (AI). We allow a broad sense of agent, but require at least that an agent has some measure of autonomy and interacts with other agents via some kind of agent communication language. We are concerned in this paper with formal modeling of multi-agent systems, with emphasis on communication. We propose for this purpose to use the pi-calculus, an extension of the process algebra CCS. Although the literature on the pi-calculus refers to agents, the term is used there in the sense of a process in general. It is our contention, however, that viewing agents in the AI sense as agents in the pi-calculus sense affords significant formal insight. One formalism that has been applied to agents in the AI sense is epistemic logic, the logic of knowledge. The success of epistemic logic in computer science in general has come in large part from its ability to handle concepts of knowledge that apply to groups. We maintain that the pi-calculus affords a natural yet rigorous means by which groups that are significant to epistemic logic may be identified, encapsulated, structured into hierarchies, and restructured in a principled way. This paper is organized as follows: Section 2 introduces the pi-calculus; Section 3 takes a scenario from the classical paper on agent-oriented programming [Sh93] and translates it into a very simple subset of the n-calculus; Section 4 then shows how more sophisticated features of the pi-calculus may bc brought into play; Section 5 discusses how the pi-calculus may be used to define groups for epistemic logic; and Section 6 is the conclusion.

Rorie, Toinette↗

DOE OSTI2024

Surface Modified Fly Ash for Value Added Products (SuMo Fly Ash)

The objective of this project is to develop a technology to encapsulate coal fly ash particles in sulfurized vegetable oil, enhancing physical and mechanical properties of the fly ash as a filler material when applied in commercial products. This project significantly advances the knowledge base and technology for synthesizing coated fly ash particles for application in different polymer matrices to increase cross-linking, compatibility, air-entrainment and to decrease the leaching potential of metals of concern. Specifically, the project focuses on (a) collection, and characterization of fly ash material from coal power plants; (b) development of Sulfurized Vegetable Oil (SVO) modified (SuMo) fly ash and their detailed characterization; (c) evaluation of the mechanical properties of the SuMo fly ash incorporated plastic and rubber composites for potential replacement of CaCO 3 or carbon black as filler materials with SuMo fly ash in plastic and rubber composites; (d) leaching potential of SuMo fly ash and SuMo fly ash-incorporated plastic and rubber composites to determine the rate of release of trace metals. The major findings of this project are: i) Sulfurized Vegetable Oil coated fly ash (SuMo fly ash) was successfully prepared with a particle size of ≤ 45 micron which exhibited hydrophobicity of contact angle > 90°; ii) the coating reduces leaching of metals (e.g., B, Cr) from fly ash when exposed to water; iii) incorporation of SuMo fly ash increases thermal stability and yield strength of plastics; iv) SuMo coating helps disperse fly ash particles into cured rubbers, natural rubber; (v) SuMo fly ash-incorporated plastic/cured rubbers compounds protects against leaching of toxic elements.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

Getting things done onsite: Heat Source production never ramps down

The COVID-19 pandemic has changed many norms in the world and at LANL. During the rapid transition of sending many to work from home in March, some programs were deemed mission critical, with the expectation to continue driving their missions forward. One of those essential programs is Heat Source Technologies, a group within the Actinide Material Power & Processing (AMPP) Division at TA-55. Within the Associate Laboratory Directorate of Weapons Production (ALDWP), the group responsible for the Pu-238 heat sources continued their work nearly uninterrupted as many others made the mandatory transition to work remotely. This group, known as AMPP-1, Heat Source Technologies, works on the production line producing heat sources from Plutonium (Pu)-238, which is an essential mission for National Security. This group is comprised of nearly 90 employees and operates out of the TA-55 Plutonium Facility (PF-4 and PF-5) producing heat sources. Heat source production includes the operations that purify, process, and weld Pu-238 oxide into encapsulated heat sources that are essential for space and defense missions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2014

SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection

Purpose: To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. Methods: Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept-relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de-identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre-screened for errors and then used by the Hugin implementation of the Estimation-Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD-9 neoplasm categories including lung, brain, lymphoma, and female breast. Results: The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation. Conclusion: The networks developed here support the use of probabilistic models into clinical chart checking for improved detection of potential errors in RT plans.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Open Reproducible Electron Microscopy Data Analysis

Electron microscopy (EM) is a cornerstone technique in the materials and biological sciences capable of imaging structures at nano- to atomic-scale resolution. Advances in technologies mean that one acquires datasets at increasing data rates and sizes. These advancements present enormous opportunities for researchers to understand complex systems. However, processing the resulting large-scale, complex data in a reproducible and shareable way is a real challenge for researchers. The building, managing, and maintaining complex workflows in a reproducible manner requires extensive knowledge in several areas outside the researchers’ core skill sets, such as software engineering, data science, and high-performance computing (HPC). Our work demonstrates an innovative approach to solving these problems, enabling reproducible EM data analysis through container encapsulated pipelines. Using modern container technologies, we encapsulate processing elements and connect them using shared memory. We expose user-friendly, advanced algorithms and tools to allow end users to utilize without expert programming skills. The platform enables reproducible, scalable, shareable pipelines for the analysis and visualization of EM data. Focusing on interoperability, we leverage the DOE and other agencies’ existing investments to provide a powerful software platform for EM data analysis.

Harris, Christopher↗

NASA NTRS2009

Presentation, Analysis, and Simulation of Active Alignment Strategies for the James Webb Space Telescope

This paper presents three characteristics in the simulated active alignment strategy of the James Webb Space Telescope. The first includes the analysis and comparison of a baseline active alignment strategy with a damped least squares strategy. This baseline utilizes prior knowledge by means of direct human operator interaction to engage sets of telescope compensators to target specific aberration signatures. The baseline is compared to a damped least-squares strategy that utilizes simultaneous engagement of all telescope compensators without explicit human operator inter<actiori to achieve a least-squares telescope compensation. Second, we discuss how the active alignment of the JWST is encapsulated in a linear optical model developed at the Space Telescope Science Institute. This linear optical model provides a framework for an efficient and robust description of the optical control properties of the JWST and clearly articulates the necessity for having a multi-instrument multi-field wavefront sensing strategy to overcome control system non independence and the effects of non-common path errors in the main wavefront sensing camera. Finally. we present analytical results that explicitly map the telescope wavefront responses to the telescope control modes, and we present Monte-Carlo optical performance simulation results that demonstrate the efficacy of the damped least-squares active alignment and the prior-knowledge active alignment schemes.

Upton, Robert S.↗