Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “critical points”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Scaling of Shear Rheology of Concentrated Charged Colloidal Suspensions across Glass Transition

Electrostatic interparticle interactions are a key component in controlling and designing rheological characteristics of concentrated charged colloidal suspensions. Herein, we investigate electroviscous effects on shear rheology using highly charged silica particles. By fixing the volume fraction but varying the salinity, the system undergoes a glass transition as evidenced by the evolution of the yield stress and zero-shear viscosity. We show that the steady shear viscosities obey a critical scaling relation that scales the flow curves into a super- and a sub-critical branch with glass transition salinity serving as the bifurcation point; we also demonstrate an isoviscosity scaling that collapses all isoviscosity lines into a single master curve that exhibits no singularity. Based on each scaling relation, in conjunction with common modeling equations, the quantitative relationships between the shear viscosity, stress, and salinity are established. This study demonstrates a new framework to model the steady shear rheology of concentrated charged colloids.

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

Revisiting the Effects of Seed Liquid Water Content on Isoprene Secondary Organic Aerosol Growth

Aerosol liquid water content (LWC) has been shown to enhance partitioning of water-soluble oxygenated organic vapors into the aerosol particles and facilitate aqueous chemistry, impact SOA formation, composition, and physicochemical properties. Here, this study examines the effect of aerosol liquid water content (LWC) on isoprene SOA formation using effloresced and deliquesced ammonium sulfate ((NH 4 ) 2 SO 4 ) and sodium chloride (NaCl) seed particles in an environmental chamber with photo-oxidation extending over hours under moderate relative humidity (50%-60%). Our findings indicate that isoprene SOA mass yield is not significantly influenced (p value >> 0.05) by the phase state or the chemical identity of the seed particles within a 3–4-hour reaction time scale. Detailed molecular analysis using advanced high resolution mass spectrometry indicates that while both effloresced and deliquesced seed types produced similar molecular formula distributions, deliquesced (NH 4 ) 2 SO 4 slightly favored the production of less volatile compounds. Depth-profiling analysis by single particle mass spectrometry confirmed that isoprene SOA predominantly located on the surfaces of particles with core-shell morphologies, with partial dissolution of the effloresced inorganic salt observed even below the deliquescence relative humidity (DRH) of salt. This finding suggests that assuming dry salt core particles do not interact with SOA coatings, based on salt deliquescence points, may overlook important aqueous chemistry. These results emphasize the critical role of reaction time scale and mixing state on SOA formation and call for further research to understand LWC effects on SOA from different precursors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Disentangling Electronic Transport and Hysteresis at Individual Grain Boundaries in Hybrid Perovskites via Automated Scanning Probe Microscopy

Underlying the rapidly increasing photovoltaic efficiency and stability of metal halide perovskites (MHPs) is the advancement in the understanding of the microstructure of polycrystalline MHP thin film. Over the past decade, intense efforts have been aimed at understanding the effect of microstructures on MHP properties, including chemical heterogeneity, strain disorder, phase impurity, etc. It has been found that grain and grain boundary (GB) are tightly related to lots of microscale and nanoscale behavior in MHP thin films. Atomic force microscopy (AFM) is widely used to observe grain and boundary structures in topography and subsequently to study the correlative surface potential and conductivity of these structures. For now, most AFM measurements have been performed in imaging mode to study the static behavior; in contrast, AFM spectroscopy mode allows us to investigate the dynamic behavior of materials, e.g., conductivity under sweeping voltage. However, a major limitation of AFM spectroscopy measurements is that they require manual operation by human operators, and as such only limited data can be obtained, hindering systematic investigations of these microstructures. Here, we designed a workflow combining the conductive AFM measurement with a machine learning (ML) algorithm to systematically investigate grain boundaries in MHPs. The trained ML model can extract GBs locations from the topography image, and the workflow drives the AFM probe to each GB location to perform a current–voltage (IV) curve automatically. Then, we are able to have IV curves at all GB locations, allowing us to systematically understand the property of GBs. Using this method, we discovered that the GB junction points are less conductive, potentially more photoactive, and can play critical roles in MHP stability, while most previous works only focused on the difference between GB and grains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Probing single-chain conformation and its impact on the optoelectronic properties of donor–accepter conjugated polymers

The chain conformation of donor–acceptor conjugated polymers (D–A CPs) is critical to their optical and electronic properties. However, probing the conformation of D–A CPs (e.g., persistence length and contour length) at a single-chain level is challenging due to the formation of aggregates in dilute solution, even in a good solvent. In this work, we studied the chain conformation and corresponding optical spectra for high-performance D–A CPs in the single-chain state by multimodal variable-temperature scattering and spectroscopy techniques, as well as by molecular dynamics simulations. Here we found a critical role of the side-chain length and branch point in the persistence length and optical absorption due to steric effects. Hence, it is important to consider both the chain rigidity and coplanarity of the polymer backbone to achieve desirable optoelectronic properties. Our findings bridge the fundamental knowledge gaps to design new CPs with desired optoelectronic properties via molecular engineering for next-generation electronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Mechanism of mixed-linkage glucan biosynthesis by barley cellulose synthase–like CslF6 (1,3;1,4)-β-glucan synthase

Mixed-linkage (1,3;1,4)-β-glucans, which are widely distributed in cell walls of the grasses, are linear glucose polymers containing predominantly (1,4)-β-linked glucosyl units interspersed with single (1,3)-β-linked glucosyl units. Their distribution in cereal grains and unique structures are important determinants of dietary fibers that are beneficial to human health. We demonstrate that the barley cellulose synthase-like CslF6 enzyme is sufficient to synthesize a high–molecular weight (1,3;1,4)-β-glucan in vitro. Biochemical and cryo–electron microscopy analyses suggest that CslF6 functions as a monomer. A conserved “switch motif” at the entrance of the enzyme’s transmembrane channel is critical to generate (1,3)-linkages. There, a single-point mutation markedly reduces (1,3)-linkage formation, resulting in the synthesis of cellulosic polysaccharides. Our results suggest that CslF6 monitors the orientation of the nascent polysaccharide’s second or third glucosyl unit. Register-dependent interactions with these glucosyl residues reposition the polymer’s terminal glucosyl unit to form either a (1,3)- or (1,4)-β-linkage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Anisotropic superconductivity at KTaO 3 (111) interfaces

A two-dimensional, anisotropic superconductivity was recently found at the KTaO 3 (111) interfaces. The nature of the anisotropic superconducting transition remains a subject of debate. To investigate the origins of the observed behavior, we grew epitaxial KTaO 3 (111)-based heterostructures. We show that the superconductivity is robust against the in-plane magnetic field and violates the Pauli limit. We also show that the Cooper pairs are more resilient when the bias is along [11$\bar{2}$] (I ∥ [11$\bar{2}$]) and the magnetic field is along [1$\bar{1}$0] (B ∥ [1$\bar{1}$0]). We discuss the anisotropic nature of superconductivity in the context of electronic structure, orbital character, and spin texture at the KTaO 3 (111) interfaces. The results point to future opportunities to enhance superconducting transition temperatures and critical fields in crystalline, two-dimensional superconductors with strong spin-orbit coupling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Evaluation of Technically-Recoverable Resources in the Marcellus and Utica Shale Gas Plays of the Appalachian Basin

Well production estimates are evaluated to provide estimates of total and remaining technically-recoverable gas resources in the Marcellus and Utica shale gas plays of the Appalachian basin. Domestic gas resources are critical contributors to the United States (U.S.) economy and will be key to enabling the sustainable and carbon-neutral fuel systems of the future. Recent assessments by the Energy Information Administration (EIA) continue to identify resources of the Appalachian region as critical to meeting energy demand, with the Marcellus and Utica- Point Pleasant (“Utica”) shale plays combining for more than 30 percent of projected U.S. domestic natural gas production through 2050.

03 NATURAL GAS↗
DOE OSTI2023

Quantum Computing – Real-Time Data Processing from a Dilution Refrigerator

This poster presents a real-time data visualization system for monitoring and displaying data from a Bluefors control unit connected to a dilution refrigerator. The goal is to provide an aesthetically pleasing and user-friendly web-based interface that continuously updates and displays critical data such as temperature and flow rates at various points within the refrigerator. Leveraging WebSocket technology, the system establishes multiple connections to the dilution refrigerators, enabling simultaneous monitoring of several units. The interactive webpage dynamically updates the data, providing researchers and operators with instant insights into the system's performance. The system's ability to stream and visualize data in real-time enhances the understanding of the dilution refrigerator's behavior, aiding in optimizing its operation and ensuring efficient scientific experiments. The application's web-based nature makes it easily accessible from any device with internet connectivity, promoting seamless collaboration and remote monitoring capabilities. Overall, this poster offers a comprehensive solution for real-time data visualization and analysis of dilution refrigerators, catering to the needs of researchers and scientists working in low-temperature physics and quantum computing fields.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Framework for Addressing Hydropower Modeling Gaps in Electric Grid Planning and Operational Studies [Slides]

Realistic representation of hydropower in power system planning and operation studies is extremely important as it helps in avoiding under/over-estimation of the services the hydro power units can provide. A framework and tools have been developed to account for hydrological conditions and modify power system models accordingly. For example, HyDat – data and AI driven platform, that provides that data required for editing the power system model files Collaborative effort with V&R Energy. Also, development of POM based tools have been performed, a) Tool1: editing .raw files with realistic current and maximum hydrogeneration and redispatch of other units, and b) Tool2: Editing .dyr files to represent water head, current and maximum generation. Finally the framework, HASP framework combines HyDat and V&R energy tools to produce modified power system model files. Key Take-away points from contingency analysis studies include a) the number of critical contingencies increases as the water levels are reduced (70%>75%>80%), and b) both the extent and the quality of dynamic response of the Hydropower unit is different with varying water head levels.

13 HYDRO ENERGY↗
DOE OSTI2022

Soft Actor Critic Based Volt-VAR Co-optimization in Active Distribution Grids

Modern distribution networks are undergoing several technical challenges, such as voltage fluctuations, because of high penetration of distributed energy resources (DERs). This paper proposes a deep reinforcement learning (DRL)-based Volt VAR co-optimization technique for reducing voltage fluctuations as well as power loss under high penetration of DERs. In addition, the proposed approach minimizes the operational cost of the grid. A stochastic policy optimization based soft actor critic (SAC) agent is proposed to configure the optimal set-points of the reactive power outputs of the inverters. The performance of the proposed model is verified on the modified IEEE 34- and 123-bus systems and compared with a base case scenario with no reactive supply by inverters, and a local droop control approach. The results demonstrate that the proposed framework outperforms the conventional droop control method in improving the voltage profile, minimizing the network power loss, and reducing grid operational cost.

—Distribution grids, deep reinforcement learning, ↗
DOE OSTI2021

LxCxD motif of the APC/C coactivator subunit FZR1 is critical for interaction with the retinoblastoma protein

Highlights: • Several oncogenic viral proteins bind to tumor suppressor pRB via LxCxE motif. • LxCxE present in many cellular proteins that interact with pRB. • APC/C interacts with pRB via this motif in its FZR1 subunit. • FZR1 LxCxE-like LxCxD critical for FZR1-pRB direct binding and SKP2 ubiquitylation. • Mutation of FZR1 LxCxD alters cell cycle. Retinoblastoma protein (pRB) regulates cell cycle by utilizing different regions of its pocket domain for interacting with E2F family of transcription factors and with cellular and viral proteins containing an LxCxE motif. An LxCxE-like motif, LxCxD, is present in FZR1, an adaptor protein of the multi-subunit E3 ligase complex anaphase-promoting complex/cyclosome (APC/C). The APC/C{sup FZR1} complex regulates the timely degradation of multiple cell cycle proteins for mitotic exit and maintains G1 state. We report that FZR1 interacts with pRB via its LxCxD motif. By using point mutations, we found that the cysteine residue in the FZR1 LxCxD motif is critical for direct interaction with pRb. The direct binding of the LxCxD motif of FZR1 to the pRB LxCxE binding pocket is confirmed by using human papillomavirus protein E7 as a competitor, both in vitro and in vivo. While mutation of the cysteine residue significantly disrupts FZR1 interaction with pRB, this motif does not affect FZR1 and core APC/C association. Expression of the FZR1 point mutant results in accumulation of S-phase kinase-associated protein 2 (SKP2) and Polo-like kinase 1 (PLK1), while p27{sup Kip1} and p21{sup Cip1} proteins are downregulated, indicating a G1 cell cycle defect. Consistently, cells containing point mutant FZR1 enter the S phase prematurely. Together our results suggest that the LxCxD motif of FZR1 is a critical determinant for the interaction between FZR1 and pRB and is important for G1 restriction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Topology-Informed Design Rules for Deconstructable Thermoset Copolymer Networks

Existing models of thermoset deconstruction facilitated by incorporating cleavable comonomers rely on a mean-field reverse gel point paradigm, which predicts network dissolution once cleavable bonds reach a critical stoichiometric threshold, but does not account for where those bonds reside within the network architecture. Using reactive coarse-grained molecular dynamics simulations coupled with graph-theoretic analysis, we extend this stoichiometric picture to show that deconstructability is governed by the curing-imprinted network topology rather than stoichiometry alone. This topological organization is hierarchical: at the local scale, the elastic effectiveness of cross-link junctions determines which cross-links constitute the load-bearing scaffold; at the mesoscale, the cross-linking rate kinetically templates that scaffold into topologically modular communities─densely cross-linked clusters connected by sparse bridging strands that sustain network connectivity. Using betweenness centrality to identify nodes that disproportionately lie on intercommunity shortest paths, we demonstrate that effective deconstruction of the network into macromolecular fragments requires cleavable comonomers to intercept these high-centrality bridging strands. We further find that under uniform, disassortative comonomer incorporation, this topological requirement provides a mechanistic basis for extending the reverse gel point to incorporate network topology. We also show that modularity imposes a fundamental limit on fragment uniformity that persists even when the centrality requirement is met. Finally, we demonstrate that chain stiffness provides a nearly independent lever to suppress mechanically redundant cross-links and raise the glass transition temperature without significantly altering the deconstruction outcome. Together, these findings reframe the thermoset design space around network topology and provide actionable guidelines for engineering thermoset copolymers with predictable deconstructability and targeted thermomechanical performance.

coarse-grained molecular dynamics↗
DOE OSTI2020

Calculating n-point charge correlations in evolving systems

Background: In dynamic systems such as heavy-ion collisions, charge susceptibilities and local charge correlations change with time. These changes are accompanied by nonlocal correlations, which spread diffusively with time and are constrained by local charge conservation. Such correlations have been measured at the Relativistic Heavy-Ion Collider (RHIC) and have been linked to the chemical evolution of the matter and possible phase separation or critical phenomena. The evolution of such correlations has been modeled for two-point correlators superimposed onto hydrodynamics, but not for three- or four-point correlators. These higher-order correlators represent an essential basis for calculating the kurtosis and skewness of charge distributions measured at RHIC. For short-range correlations, such as those between charges on the same particle, and the associated charge-balance correlations a theoretical formalism was lacking for handling higher-order correlations. In particular, one needed to understand how higher-order charge fluctuations was split onto lower numbers of particles. For example, correlations of order three have contributions with charge all on one particle, split onto two particle, or split onto three. By assuming local chemical equilibrium of short-range correlations, the sources of the various correlators were found to be uniquely determined. The relevant theoretical foundation is presented here, including a diagrammatic technique to correctly account for all the possible terms to higher-order correlations. Here, we found a consistent theoretical treatment and its applicability, viability, and tractability are discussed. The formalism derived here enables realistic and quantitative modeling of the three- and four-point charge correlations necessary for understanding measurements of the kurtosis and skewness of charge distributions at RHIC. These observables have been promoted as signals of phase transitions or measures of chemical evolution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Evaluation of the critical behavior near ferromagnetic to paramagnetic phase transition in CrTe 1-x Se x alloys: An experimental study

For this study, we used the conventional solid-state reaction method to prepare stoichiometric samples of CrTe 1-x Se x , where 0 ≤ x ≤ 0.10, and investigated the structural and critical behavior of the prepared samples. Room temperature powder X-ray diffraction, along with Rietveld refinement, revealed the emergence of the NiAs structure with P6 3 /mmc (194) space group with increasing Se substitution. The high-temperature linear fit to inverse of the dc-susceptibility versus temperature for the mother sample resulted in an effective moment of 3.65μ B Cr with Curie-Weiss temperature near 335K, which is slightly higher than the Tc of ~332K obtained from the inflection point of magnetization versus temperature. Magnetization isotherms were employed to investigate the critical behavior of ferromagnetic CrTe 1-x Se x with 0.0 ≤ x ≤ 0.10 near their Curie temperatures (Tc). The magnetic behavior near Tc was found to follow 3D mean-field critical exponents with a second-order phase transition in all samples investigated. We fine-tuned the critical exponents (β, γ, and δ) using a combination of an iteration technique, the Kouvel-Fisher method, and modified Arrott plots. All samples follow a mean field behavior, with Tc ranging from 298 to 340K. The acquired values exhibit self-consistency, as indicated by the results from the Widom scaling relation. Furthermore, the magnetization isotherms exhibit a universal scaling behavior, providing additional credence to the calculated critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Emerging Rare Earth Element Separation Technologies

Rare earth elements are essential for numerous clean energy applications, yet their mining, separation, and processing pose significant environmental challenges. Traditional separation processes often result in ecological damage, highlighting the critical need for innovative techniques that reduce environmental impacts. This article reviews recent advancements in rare earth separation technologies, with a particular focus on the role of neutral organic compounds. It explores how these compounds change selectivity across the rare earth series, offering promising strategies for designing more effective rare earth element separation systems. Furthermore, the article points out research areas requiring additional investigation to improve the sustainability of these critical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

ObstacleSense: Low-Power Neuromorphic Vision for Corridor Obstacle Awareness in Low-Level ADAS

The automotive industry’s pursuit of Level 5 autonomy is constrained by substantial perception-compute power requirements, often reaching 1, 000 + watts in full autonomy stacks. Reducing this energy burden requires rethinking perception not only at the high-end autonomy level, but also at the foundational Advanced Driver Assistance Systems (ADAS) level where low-power, safety-critical sensing can have broad impact. Neuromorphic vision provides a promising starting point: HD Dynamic Vision Sensors (DVS) can operate below 100 mW at the sensor level by reporting only asynchronous brightness changes. However, low-power sensing alone is insufficient if downstream perception reintroduces dense, energy-intensive computation. In particular, many event-driven object-detection pipelines still rely on CNN backbones, while purely spiking alternatives often trade away accuracy or ignore deployment constraints. We introduce ObstacleSense, a highly compact, CNN-free hybrid ANN–SNN framework for Level 0–1 forward-corridor obstacle awareness. Instead of performing full-scene object detection with a convolutional feature backbone, ObstacleSense targets the safety-critical question of whether the ego corridor is occupied and how far the nearest obstacle is. The architecture combines polarity-conditioned event encoding, lightweight temporal spiking dynamics, axial spatial mixing, and coarse-to-fine range estimation within a regular fixed-grid compute pattern. This design avoids the dense CNN backbone commonly used in event-based detection while maintaining a small state footprint suitable for eventual small-FPGA deployment. Before hardware mapping, we evaluate the software implementation using a model-side power proxy derived from MACs, weight and activation traffic, and spiking state updates under shared FP16 assumptions. On simulated CARLA event corpora, the deployment-oriented model achieves 0.9464 objectness F1, 0.9978 grid-level mAP, and 0.8987 m distance Mean Absolute Error at an estimated 1.92 mW proxy cost, while maintaining performance on unseen generalization test sequences.

Johnson-Scott, Zac [ORNL]↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗