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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Debonding-on-demand reversible adhesives via heat or light with competitive adhesion strength to conventional epoxy adhesives

Stimuli responsive debonding-on-demand (DoD) reversible adhesives are of great interest for the circular economy. However, the reversible adhesives developed so far often lack competitive adhesion strength in a bonding state. In this work, reversible epoxy adhesives based on Diels–Alder (DA) chemistry were developed and exhibited a competitive adhesion strength (e.g., 12 – 16 MPa of a lap shear strength) to commercial non-reversible epoxy adhesives. The reversible epoxy formulation showed superior thermal stability up to 110°C, and transition to a debonding state in the order of 0.1 MPa at 140°C, consequently, an on/off-type debonding behavior. The transition to a debonding state was attributed to crosslinking density control (e.g., decrease by 33% – 49%) through the reversible DA chemistry and the proximity to the glass transition. Next, for debonding by light stimulus, photothermal refractory plasmonic titanium nitride (TiN) nanoparticles were incorporated in the reversible epoxy, which can generate the required heat for debonding upon exposure to visible light. Photothermal debonding allows for precise debonding at target areas and tunable adhesion strength by controlling the exposure area and light intensity. The DA adhesive formulations containing 0.5 wt.% TiN nanoparticles presented a debonding state with zero adhesion under light exposure with intensity of 1670 mW/cm 2 (inducing 140°C). Even after three cycles of reattachment, the DA adhesive formulations retained 96% of the pristine sample’s adhesion strength measured at 110°C. Therefore, the DA adhesives are attractive candidates as reversible DoD systems applicable in higher temperatures.

42 ENGINEERING↗
DOE OSTI2025

A novel peridynamics-based approach to predict pharmaceutical tablet robustness

The pharmaceutical drug product development process can be greatly accelerated through the use of modeling and simulation techniques to predict the manufacturability and performance of a given formulation. The anticipation and possible mitigation of tablet damage due to manufacturing stresses represents a specific area of interest in the pharmaceutical industry for predicting formulation and tableting performance. While the finite element method (FEM) has been extensively used for predicting the mechanical behavior of powder material in the compaction processes, a shortcoming of the approach is the inherent difficulty to predict discontinuities (e.g., damage or cracking) within a tablet as FEM is a continuum-based approach. In this work, we propose a novel method utilizing peridynamics (PD), a numerical method that can capture discontinuities such as tablet fracture, to predict the evolution of damage and breakage in pharmaceutical tablets. The approach links (1) the finite element method – to elucidate the behavior of powders during die compaction – with (2) the peridynamics modeling technique – to model the discontinuous nature of damage and predict tablet breakage during the critical stages of unloading and ejection from the compression die. This short communication presents a proof of concept including a workflow to calibrate the linked FEM-PD simulation models. Further, it demonstrates promising results from a preliminary experimental validation of the approach. Following further development, this approach could be used to guide the optimization of compression processes through targeted changes to formulation material properties, compression process conditions, and/or tooling geometries to deliver improved process efficiency and tablet robustness.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimization problems governed by systems of PDEs with uncertainties

This paper reviews current theoretical and numerical approaches to optimization problems governed by partial differential equations (PDEs) that depend on random variables or random fields. Such problems arise in many engineering, science, economics and societal decision-making tasks. This paper focuses on problems in which the governing PDEs are parametrized by the random variables/fields, and the decisions are made at the beginning and are not revised once uncertainty is revealed. Examples of such problems are presented to motivate the topic of this paper, and to illustrate the impact of different ways to model uncertainty in the formulations of the optimization problem and their impact on the solution. A linear–quadratic elliptic optimal control problem is used to provide a detailed discussion of the set-up for the risk-neutral optimization problem formulation, study the existence and characterization of its solution, and survey numerical methods for computing it. Different ways to model uncertainty in the PDE-constrained optimization problem are surveyed in an abstract setting, including risk measures, distributionally robust optimization formulations, probabilistic functions and chance constraints, and stochastic orders. Furthermore, approximation-based optimization approaches and stochastic methods for the solution of the large-scale PDE-constrained optimization problems under uncertainty are described. Some possible future research directions are outlined.

Heinkenschloss, Matthias [Rice Univ., Houston, TX ↗
DOE OSTI2024

Identification of Suitable Vacuum Gas Oils as Plasticizers Using HT-GC × GC-HRMS

Vacuum gas oils (VGOs) have long been heralded as effective plasticizers due to their high boiling-points and lubricating properties. One of these VGOs, HyVac Oil 93050, is a paraffinic plasticizer that is currently utilized in polymer–plasticizer explosive formulations, while this oil effectively increases the elasticity and decreases the sensitivity for current formulations. We seek to identify alternative VGOs with similar density, viscosity, molecular composition, and impurities for future formulations. In this study, 18 VGOs, including HyVac Oil 93050, were initially evaluated for their density and viscosity. The oils were then ranked based on physical characteristics and analyzed for molecular composition using high-temperature comprehensive two-dimensional gas chromatography with high-resolution time-of-flight mass spectrometry (HT-GC × GC-HRMS). Further, the HT-GC × GC-HRMS chromatograms of the top 10 most similar VGOs to HyVac Oil 93050, according to density, were compared utilizing the Pearson correlation coefficient. Three of the oils with densities similar to those of HyVac Oil 93050 had a Pearson correlation within the lot-to-lot variation of HyVac Oil 93050. For the top 3 candidates, Pearson correlation was then utilized as a feature selection technique to discover significant chemical differences. Positive chemical ionization (PCI) and negative chemical ionization (NCI) HT-GC × GC-HRMS chromatograms were also evaluated and aided in the discovery and identification of several key compounds including additives that acted as stabilizers for the VGOs. After this further chemical analysis, two of the original 17 potential VGOs were determined to be physically and chemically similar to HyVac Oil 93050.

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

Rheology improvement for silicon nitride and resin slurries for vat photopolymerization printing and sintering

This work presents the formulation, rheological characterization, and sintering of silicon nitride (Si₃N₄) slurries for vat photopolymerization (VPP) using digital light processing (DLP). Bimodal Si₃N₄ powder was dispersed into commercial photopolymer resin using two different dispersants with opposing effects on surface charge, resulting in varied slurry stability and flow behavior. Slurries were engineered to exhibit shear-thinning behavior suitable for VPP, and their flow properties were quantified using a power-law fluid model. The formulations achieved cure depths of approximately 40 µm and enabled printing of green bodies. Post-processing included thermal debinding and liquid-phase sintering, yielding primarily β-Si₃N₄ with a minor Y-Si-Al-O-N glass phase. The sintered parts reached ~85% of theoretical density and demonstrated a flexural strength of ~330 MPa. Microstructural analysis revealed closed porosity along with some defects related to powder agglomeration and interlayer adhesion. These findings provide insights into slurry formulation strategies for additive manufacturing of high-performance non-oxide ceramics.

Aerospace engineering↗
DOE OSTI2024

Investigating the origin of the far-field reflection interference fringe (RIF) of microdroplets

We show that the reflection interference fringe (RIF) is formed on a screen far away from the microdroplets placed on a prism-based substrate, which have low contact angles and thin droplet heights, caused by the dual convex–concave profile of the droplet, not a pure convex profile. The geometric formulation shows that the interference fringes are caused by the optical path difference when the reflected rays from the upper convex profile at the droplet–air interface interfere with reflection from the lower concave profile at oblique angles lower than the critical angle. Analytic solutions are obtained for the droplet height and the contact angle out of the fringe number and the fringe radius in RIF from the geometric formulation. Furthermore, the ray tracing simulation is conducted using the custom-designed code. The geometric formulation and the ray tracing show excellent agreement with the experimental observation in the relation between the droplet height and the fringe number and the relation between the contact angle and the fringe radius. This study is remarkable as the droplet's dual profile cannot be easily observed with the existing techniques. However, the RIF technique can effectively verify the existence of a dual profile of the microdroplets in a simple setup. In this work, the RIF technique is successfully developed as a new optical diagnostic technique to determine the microdroplet features, such as the dual profile, the height, the contact angle, the inflection point, and the precursor film thickness, by simply measuring the RIF patterns on the far-field screen.

42 ENGINEERING↗
DOE OSTI2025

Voltage Probability Density Function Shaping Control Strategy Considering Grid Operational Uncertainties

It is well-known that power systems operation always affected by various uncertainties which make the bus voltage a random process that can be characterized by its probability density function (PDF) at any time instant. In this context, this paper presents a novel PDF-based voltage control framework for power systems. By modeling voltage as a stochastic process, we formulate a stochastic differential equationthat captures grid uncertainties. The associated Fokker-Planck-Kolmogorov equation is derived to describe the evolution of the voltage PDF, which enables the formulation of a PDF-shaping control strategy. To simplify the PDF control formulation, a B-spline neural network is introduced for real-time estimation and regulation of the voltage distribution. The proposed PDF control law updates voltage references for energy storage systems and synchronous generators using real-time PDF measurements and feedback signals. The proposed method is validated on a modified Kundur’s two-area system. Simulation results demonstrate that the controller can significantly improve the voltage stability under stochastic conditions, highlighting its effectiveness in modern inverter-rich grids.

Gui, Yonghao [ORNL] (ORCID:0000000250435534)↗
DOE OSTI2025

Robust A-Optimal Experimental Design for Sensor Placement in Bayesian Linear Inverse Problems

Optimal design of experiments for Bayesian inverse problems has recently gained wide popularity and attracted much attention, especially in the computational science and Bayesian inversion communities. An optimal design maximizes a predefined utility function that is formulated in terms of the elements of an inverse problem, an example being optimal sensor placement for parameter identification. The state-of-the-art algorithmic approaches following this simple formulation generally overlook misspecification of the elements of the inverse problem, such as the prior or the measurement uncertainties. This work presents an efficient algorithmic approach for designing optimal experimental design schemes for Bayesian linear inverse problems such that the optimal design is robust to misspecification of elements of the inverse problem. Specifically, we consider a worst-case scenario approach for the uncertain or misspecified parameters, formulate robust objectives, and propose an algorithmic approach for optimizing such objectives. Furthermore, both relaxation and stochastic solution approaches are discussed with detailed analysis and insight into the interpretation of the problem and the proposed algorithmic approach. Extensive numerical experiments to validate and analyze the proposed approach are carried out for sensor placement in a parameter identification problem.

Bayesian inverse problems↗
DOE OSTI2026

Nonlinear optimal recovery in Hilbert spaces

Here, this paper investigates solution strategies for nonlinear problems in Hilbert spaces, such as nonlinear partial differential equations (PDEs) in Sobolev spaces, when only finite measurements are available. We formulate this as a nonlinear optimal recovery problem, establishing its well-posedness and proving its convergence to the true solution as the number of measurements increases. However, the resulting formulation might not have a finite-dimensional solution in general. We thus present a sufficient condition for the finite dimensionality of the solution, applicable to problems with well-defined point evaluation measurements. To address the broader setting, we introduce a relaxed nonlinear optimal recovery and provide a detailed convergence analysis. An illustrative example is given to demonstrate that our formulations and theoretical findings offer a comprehensive framework for solving nonlinear problems in infinite-dimensional spaces with limited data.

convergence↗
DOE OSTI2024

Higher-form symmetry and chiral transport in real-time Abelian lattice gauge theory

We study classical lattice simulations of theories of electrodynamics coupled to charged matter at finite temperature, interpreting them using the higher-form symmetry formulation of magnetohydrodynamics (MHD). We compute transport coefficients using classical Kubo formulas on the lattice and show that the properties of the simulated plasma are in complete agreement with the predictions from effective field theories. In particular, the higher-form formulation allows us to understand from hydrodynamic considerations the relaxation rate of axial charge in the chiral plasma observed in previous simulations. A key point is that the resistivity of the plasma – defined in terms of Kubo formulas for the electric field in the 1-form formulation of MHD – remains a well-defined and predictive quantity at strong electromagnetic coupling. However, the Kubo formulas used to define the conventional conductivity vanish at low frequencies due to electrodynamic fluctuations, and thus the concept of the conductivity of a gauged electric current must be interpreted with care.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Organisation of Diverse Mechanisms of Secondary Ice Production among Basic Convective and Stratiform Cloud-types

This 3-year DoE-funded joint project had the over-arching aim of understanding how ice is initiated in clouds of various types. Focus was given to processes of fragmentation of pre-existing ice, which can occur in positive feedback loops (‘ice multiplication’). A basic question to address was which fragmentation processes prevail in which basic cloud-types. The approach was to use cloud models and field observations, while pioneering our own lab observations of ice initiation to break the deadlock from the past lack of lab observations. Historically, the tendency of the cloud physics community to avoid doing lab observations has allowed a vast gap in knowledge about ice initiation to persist for decades. During the first part of the project, new formulations were created to treat two overlooked types of fragmentation of ice. First, sublimational breakup of ice was treated based on a theoretical formula that we fitted to a pooled dataset of lab observations published previously in the literature. Second, a new mode of fragmentation of freezing raindrops was treated, which involves a supercooled drop being hit by a more massive ice particle. Some of the secondary droplets from the impact freeze. This work was done at Manchester University by Co-I Connolly. Then during the second part, both formulations were implemented in our ‘aerosol-cloud model’ (AC). AC has a hybrid bin/bulk microphysics scheme, and now represents four processes of SIP. The accuracy of AC was evaluated for four cases typifying four basic cloud-types: slightly cold-based stratiform cloud and cold-, warm- and very warm-based convective clouds. We discovered that the warmth of cloud-base, especially in the tropics, promotes SIP processes of raindrop-freezing fragmentation and rime-splintering, and surprisingly, sublimational breakup too. It was found that breakup in ice-ice collisions is ubiquitous. Finally, a portable laboratory chamber was constructed at Lund and deployed in northern Sweden to observe breakup in graupel-snow collisions outdoors. This was seen to be even more prolific than treated in our 2018 formulation. Papers describing results are either published or soon to be published.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Optimal Design Approaches for Cost-Effective Manufacturing & Deployment of Chemical Process Families with Economies of Numbers

This work builds on our optimization formulation for process family design and extends it to explicitly include the benefits of economies of numbers. Economies of numbers (sometimes referred to as economies of learning) is a well-documented cost saving phenomenon. It characterizes the manufacturing cost savings due to standardization; in particular, it is capturing the correlation between cost reduction and the number of times a particular product has been manufactured. Following an approach similar to that in Gazzaneo et al. (2022), we develop a costing expression that captures material costs and manufacturing costs as a function of the number of unit modules produced. If the platform has a small number of unit module designs, we will be manufacturing a large number of each of these designs and gaining increased benefits from economies of numbers. However, increasing the number of unit module designs in the platform gives each process variant more choices to consider (at the cost of reducing economies of numbers). The optimization formulation in Stinchfield et al. (2023) pre-specified the number of unit module designs to be included in the platform. Here, by including the economies of numbers explicitly, we allow the mathematical programming formulation to determine the optimal number of unit module designs to include in the platform. We demonstrate this approach on multiple case studies, including MEA-based carbon capture and water desalination.

Stinchfield, Georgia↗
DOE OSTI2024

Development of Property Composition Models For RPP-WTP LAW Glasses (Final Report)

This report describes the development of property-composition models for low-activity waste (LAW) glasses for the River Protection Project Waste Treatment Plant (RPP-WTP) at the Hanford site. The RPP-WTP will separate Hanford tank wastes into LAW and high-level waste (HLW) streams and each stream will be vitrified separately. The development of LAW and HLW glass formulations for the RPP-WTP has been reported previously and is an ongoing activity. Acceptable formulations must meet a variety of processability, product quality, and waste loading requirements that are dictated either by the RPP-WTP contract or by the characteristics of the particular treatment processes that have been selected. These requirements amount to constraints on the acceptable ranges of certain glass properties. These properties are determined first and foremost by the composition of the glass or glass melt. Thus, while there is no direct way of controlling the glass properties of interest during production, there are simple and extremely effective methods of achieving the same result by instead controlling the glass composition. This basic principle is no different from that used to produce enormous volumes of commercial glass to meet exacting product specifications. An essential difference in waste vitrification, however, is that one of the raw materials (the waste itself) can be subject to considerable compositional uncertainty and variability. Thus, waste vitrification facilities and associated process control systems (of which, the operating envelope in glass formulation space is a key part) must, of course, be designed to be robust with respect to such variations. The determination of quantitative relationships between the glass properties that must be controlled and the glass composition can play an important role in the development of such facilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

DuraMelter 100 Sub-Envelope Changeover Testing Using LAW SubEnvelopes A1 and C1 Feeds in Support of the LAW Pilot Melter (Final Report)

The primary goal of the testing described in this report was to develop and recommend a compliant HLW glass formulation to support the actual waste testing of AZ-101 Envelope D waste (blended with actual pretreatment products including Cs- and Tc-eluates from pretreatment of AP-101 and AZ-101 LAW). Testing of actual waste will be performed at Battelle, Pacific Northwest Division. The test objective was met by the development and recommendation of the glass formulation HLW98-95; the formulation has been transmitted to the WTP to support vitrification of HLW AZ-101 actual waste.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Multi-scale, Multi-disciplinary, and Multi-agent Explainable AI with Koopman-Undergirded Learning, Prediction, and Analysis (M3EA KULPA) (Project Closeout Report)

The goal of this project was to develop and use domain-aware machine learning formulations, based on the Koopman Operator (KO), for modelling multi-scale, multi-disciplinary (e.g., multi-physics), and/or multi-agent systems. The project developed these formulations for the following cases: • Systems with dynamics at two separate time scales, • Systems with a bi-level hierarchical control structure, • Systems with bi-level hierarchical control and dynamics at two separate time scales (the lower level controls operating at the faster time scale), and • Systems with n separate but interacting agents/disciplines (with/without control, respectively); the controls for each agent could include bi-level hierarchical control and dynamics at two separate time scales as described above. The project then defined a set of dynamical systems consisting of different nonlinear oscillators that could be used to test these different formulations and then subsequently learned the KO models for those systems. With the KO models, we were able to do the following: • Quantify system stability, including both long-term and transient behavior, • Quantify the effects of feedbacks between the different time scales and agents/disciplines in terms of those feedbacks’ effects on system stability, • Replace a standard Proportional-Integral (PI) control in the hierarchical control structure with a KO-based Linear-Quadratic Regular (LQR), a form of optimal control, • Calculate optimal supervisory control policies a) with and without time scale separated dynamics at the lower level control levels and b) with both PI and KO-based LQR lower level control policies, and • Calculate dynamic Nash equilibria for multi-agent systems where each agent makes its own control decisions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Foam and Unreacted Material Reduction in Magnesium Oxysulfate for SRPPF Waste Solidification

A magnesium oxysulfate (MOS) grout formulation has been proposed to solidify the liquid effluent from the Savannah River Plutonium Processing Facility (SRPPF) Aqueous Recovery System (ARS). This formulation uses a combination of light-burnt MgO, anhydrous MgSO 4 , and dead-burnt MgO resulting in a grout with good mixability and acceptable density. The setting time for the grout is within the operational limits of the SRPPF facility and the leachate pH is ~9.4, which is within the assumed pH range of the brine from the Waste Isolation Pilot Plant (WIPP). When first tested at the 1-gallon small-scale and 55-gallon full-scale, there was a significant foam layer that raised concerns of a nonhomogeneous final form. A nonhomogeneous mixture could have variable density throughout the waste form and therefore allow for unequal shielding. To reduce the potential for unequal shielding in the final form, a series of foam reduction tests were carried out and a final formulation of 28 wt% light burnt MgO, 10 wt% MgSO 4 , and 62 wt% dead burnt MgO was used to remove the foam in under two hours while still maintaining a mix that has an acceptable density, mix time, peak temperature, and set time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Water Sorption Study of Various Polymers and Polymeric Composites

In the formulations of many composite materials, polymeric materials are often used as binder materials to enhance processability, functionality, and safety during manufacturing. For instance, poly(ester urethane), such as Estane® 5703, is used in the formulation of PBX 9501, and vinyl copolymer elastomer (VCE) is used in the formulation of VCE/filler compos ites. The stability of these binders directly impacts the overall stability and performance of their composites. Estane and VCE are prone to hydrolytic degradation, with water sorption behavior playing a significant role in their long-term stability and aging behavior. Hence, it is critical to study their water sorption behavior under various humidity and tempera ture conditions. To improve the accuracy and reduce labor-intensive work involved in water sorption experiments, an automated Dynamic Vapor Sorption (DVS) system was employed, which can generate large datasets. To efficiently process and analyze these datasets, Python scripts were developed. These scripts not only streamlined data processing, but also accu rately derived the Arrhenius parameters related to water diffusion and sorption properties for the tested materials. This approach offers a robust framework for evaluating water trans port and sorption processes in polymeric materials and adds valuable capabilities to future water sorption testing efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effects of SRPPF ARS Effluent Variations on Magnesium Oxysulfate Solidification

A magnesium oxysulfate (MOS) grout formulation has been identified to solidify the liquid effluent from the Savannah River Plutonium Processing Facility (SRPPF) Aqueous Recovery System (ARS). The formulation uses reactive, light burnt MgO (28 wt%), anhydrous MgSO 4 (10 wt%), and dead burnt MgO (62 wt%), resulting in a grout with good mixability, acceptable density, acceptable setting times, and a leachate pH around 9.4, within the assumed Waste Isolation Pilot Plant (WIPP) brine pH range. A series of tests were then designed to observe how this formula reacted to variations in the liquid effluent. Liquid effluent temperature, the caustic pH level, concentration of NaNO 3 , and the presence of neutralization products, trace metals, and/or sodium sulfate (all potential residuals found in the effluent from upstream processing), were evaluated to see how each impacts the grout mixing time, peak temperature, setting time, presence of bleed water, leachate pH, and density. The standard mix has an average mixing time of 18 minutes, peak temperature of 100.5 °C, and set time of 60 minutes. Increasing the temperature of the liquid effluent increased the reaction rate of the mix and reduced mixing and setting times. Between 30 and 40°C the change was relatively small, raising no more than 6 °C compared to the standard mix maximum temperature. Increasing the pH of the liquid effluent had no significant impact on the mix. The addition of neutralization products and trace metals had an overall impact of decreasing the reactivity of the mix. The addition of more ions in the liquid effluent, such as an increase in the concentration of NaNO 3 and the addition of Na 2 SO 4 , generally decreased the reactivity of the mix. None of the variations to the liquid effluent hindered solidification as indicated by the lack of bleed water found on all the samples. The leachate pH values for all mixes tested did not significantly vary from the expected pH of 9.4 and none of the density values fell below 1.8 g/cm 3 . Overall, changes to the liquid effluent were found to have a minimal impact on the formulation suggesting the grout's ability to properly form despite increased temperatures and the presence of residuals typically found in the liquid effluent from the ARS.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗