Search NASA⌕ Search

SEARCH · Search NASA

Results for “physical modification”

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 91 records · Page 5

Phases of 2D massless QCD with qubit regularization

We investigate the possibility of reproducing the continuum physics of 2D S U ( N ) gauge theory coupled to a single flavor of massless Dirac fermion using qubit regularization. The continuum theory is described by N free fermions in the ultraviolet (UV) and a coset Wess-Zumino-Witten (WZW) model in the infrared (IR). In this work, we first explore how well these features can be reproduced using the Kogut-Susskind (KS) Hamiltonian with a finite-dimensional link Hilbert space and a generalized Hubbard coupling. We do this by analyzing the renormalization group (RG) flow diagram of the continuum theory and identifying important phases of the theory. Using strong coupling expansions, we show that our lattice model exhibits a gapped dimer phase and a spin-chain phase. Furthermore, for N = 2 , using tensor network methods, we show that there is a second-order phase transition between these two phases, which we identify as the critical surface of the continuum theory that connects the IR and UV fixed points. In the IR, we identify the critical theory at the transition as the expected S U ( 2 ) 1 WZW model. Lastly, we argue that modifications of our model may allow the study of the UV physics of free fermions. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Search for Nuclear Modifications of 𝐵 + Meson Production in 𝑝-Pb Collisions at $\sqrt{𝑠_{NN}}$ = 8.16 TeV

Nuclear medium effects on 𝐵 + meson production are studied using the binary-collision scaled cross section ratio between events of different charged-particle multiplicities from proton-lead collisions. Data, collected by the CMS experiment in 2016 at a nucleon-nucleon center-of-mass energy of $\sqrt{𝑠_{NN}}$ = 8.16 TeV, corresponding to an integrated luminosity of 175 nb −1 , were used. The scaling factors in the ratio are determined using a novel approach based on the 𝑍 → 𝜇 − ⁢𝜇 + cross sections measured in the same events. The scaled ratio for 𝐵 + is consistent with unity for all event multiplicities, putting stringent constraints on nuclear modification for heavy flavor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method

Background: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. Results: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. Conclusion: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

59 BASIC BIOLOGICAL SCIENCES↗

Intercalation-Induced Reversible Electrochromic Behavior of Two-Dimensional Ti 3 C 2 T x MXene in Organic Electrolytes

MXenes, a large family of two-dimensional materials, have attracted tremendous attention due to their unique physical and chemical properties. Reversible ion intercalation between MXene layers allows modification of the optical, thermal, magnetic, and chemical properties. The electrochemical charge/discharge of MXenes in aqueous electrolytes was reported to lead to reversible electrochromic behavior. In this work, the electrochromic effect of semitransparent Ti 3 C 2 T x MXene film was probed by electrochemical intercalation of Li ions. Correspondingly, a peak shift of 100 nm was observed in the UV-vis spectrum. By combining in-situ Raman spectroscopy, in-situ X-ray diffraction, and density functional theory calculations, we show that the electrochromic shift is primarily due to the formation of robust O-Li bonds and the emerging bands induced changes of inter-band excitations. Finally, understanding the mechanism of electrochromic behavior in Ti 3 C 2 T x lays the foundations of designating 2D materials with durable, controllable, and efficient intercalation-induced electrochromic behaviors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tagged Short-Range Correlations for Medium to Heavy Ions at an Electron Ion Collider

Understanding short-range correlations between pairs of nucleons in the nucleus is an important nuclear physics topic that can address longstanding mysteries in nuclear physics such as the behavior of dense nuclear systems and the modification of parton distributions. As a collider and with a large acceptance detector, the Jefferson Lab version of the Electron Ion Collider has unique capabilities that are complementary to previous short-range correlation studies, most notably the ability to more fully reconstruct the final state. Optimization of the collider’s detector to maximally exploit these capabilities called for important extensions of existing simulation tools. For this one year laboratory directed research and development project, we upgraded the benchmark electron-nucleon event generator for lepto-production simulation code Benchmark eA Generator for LEptoproduction (BeAGLE) to be able to handle tagged medium-to-heavy nucleons. This included updating the code to correctly handle Fermi motion of nucleons in the nucleus as well as the large momentum caused by short-range correlations. In addition, we also investigated the possibility of improved kinematic reconstruction methods for electron nucleon collisions and looked at pair-spectator tagging of short-range correlations with the Jefferson Lab electron ion collider design. The project progressed very much as planned.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cocontinuous Nanostructures by Microphase Separation of Statistically Cross-Linked Polystyrene/Poly(2-vinylpyridine) Networks

Cocontinuous polymeric nanostructures have drawn considerable attention due to their ability to combine distinct, percolation-dependent properties of two different polymer domains. Randomly end-linked copolymer networks (RECNs) have previously been shown to support the formation of disordered cocontinuous nanostructures across wide composition windows in a robust way. However, achieving highly efficient linking of telechelic polymers with excellent end-group fidelity often requires complex synthetic routes. As an alternative, we study here statistically cross-linked copolymer networks (SCCNs) composed of polystyrene and poly(2-vinylpyridine) (PS and P2VP) with cross-linkable allyl pendent groups that are conveniently synthesized by controlled radical copolymerization. Via selective extraction of P2VP, coupled with gravimetry, small-angle X-ray scattering, and electron microscopy, we find disordered cocontinuous phases across wide composition ranges (up to ≈ 35 wt %), approaching values previously determined for RECNs. Remarkably, even for samples that appear to exhibit full percolation, a substantial fraction of P2VP (≈ 20–30 wt %) cannot be removed, which we ascribe to short strands between nearby cross-linkers that are physically embedded within PS domains. Here, the resulting PS porous monoliths with residual surface P2VP layers enable facile surface modification to resist protein adsorption and templating of porous gold nanostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modification of ion-temperature-gradient turbulence by impurities in stellarator plasmas

Recent nonlinear gyrokinetic simulations have shown that impurities can strongly modify the turbulent heat flux in stellarator plasmas. Here, the ion-temperature-gradient (ITG) dispersion relation in a plasma containing impurities is analytically solved in certain limits and an expression for the modification of the ITG growth rate by impurities is derived. The analytical expression is the sum of three terms corresponding to three different physical causes (impurity density gradient, impurity temperature gradient and dilution) of the change in the growth rate. The scalings predicted analytically for the modification of the growth rate are shown to be reproduced by linear gyrokinetic simulations. The conditions for reduction or increase of the ITG growth by impurities are also correctly predicted by the analytical solution to the dispersion relation. Finally, a remarkable correlation is found between the analytical expression for the modification of the growth rate and the modification of the turbulent heat flux obtained from nonlinear gyrokinetic simulations.

Calvo, Iván [Research Centre for Energy, Environme↗

Controlling Heterogeneous Catalysis with Organic Monolayers on Metal Oxides

A key theme of heterogeneous catalysis research is achieving control of the environment surrounding the active site to precisely steer the reactivity toward desired reaction products. One method toward this goal has been the use of organic ligands or self-assembled monolayers (SAMs) on metal nanoparticles. Metal-bound SAMs are typically employed to improve catalyst selectivity but often decrease the reaction rate as a result of site blocking from the ligands. Recently, the use of metal oxide-bound organic modifiers such as organophosphonic acid (PA) SAMs has shown promise as an additional method for tuning reactions on metal oxide surfaces as well as modifying oxide-supported metal catalysts. In this Account, we summarize recent approaches to enhance catalyst performance with oxide-bound monolayers. These approaches include (1) modification of metal oxide catalysts to tune surface reactions, (2) formation of SAMs on the oxide component of supported metal catalysts to modify sites at the metal–support interface, and (3) enhancement of catalyst performance (e.g., stability) through modification of sites remote from the active sites. Further, both the headgroups and organic tail groups of PA SAMs or other ligands can influence reactions on metal oxide surfaces. Binding of the headgroup can selectively poison certain active sites, altering the selectivity in a manner analogous to metal-bound ligands (at the expense of active site quantity). Moreover, tail groups can be functionalized to interact favorably with reactants and intermediates, for instance through dipole–dipole interactions. On supported metal catalysts like Pt/Al 2 O 3 , PA SAMs can selectively form on the oxide support. This selective deposition allows for modification of the metal–support interface with minimal blockage of metal sites. PA headgroups were shown to provide tunable acid sites at the interface, dramatically improving hydrodeoxygenation rates of various alcohols. Additionally, organic tail functionality was used to activate or stabilize specific reactants at the interface, such as with the use of amine-functionalized PAs to stabilize chemisorption of CO 2 during the reverse water gas shift reaction. PAs have also been found to affect the electronic properties of bulk metal sites through long-range electron withdrawal via the oxide, providing an additional avenue to tune catalytic behavior. Finally, organic modifiers were shown to enhance catalytic performance without directly modifying the active site. For instance, in biphasic liquid environments the modification of catalyst particles with hydrophobic or hydrophilic SAMs shifts the selectivity of multipath reactions on the basis of the hydrophobicities of different intermediates and products. As another “long-range” effect, the deposition of ligands on oxide supports improved catalyst stability through both improved resistance to sintering and suppression of active site poisoning. The recent contributions discussed in this Account demonstrate the versatility and significant potential for the approach of modifying catalysts with oxide-bound organic monolayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of a New Sea Ice Thermodynamic Formulation in the CESM2 Sea Ice Component

Abstract The sea ice component of the Community Earth System Model version 2 (CESM2) contains new “mushy‐layer” physics that simulates prognostic salinity in the sea ice, with consequent modifications to sea ice thermodynamics and the treatment of melt ponds. The changes to the sea ice model and their influence on coupled model simulations are described here. Two simulations were performed to assess the changes in the vertical thermodynamics formulation with prognostic salinity compared to a constant salinity profile. Inclusion of the mushy layer thermodynamics of Turner et al. (2013, https://doi.org/10.1002/jgrc.20171 ) in a fully coupled Earth system model produces thicker and more extensive sea ice in the Arctic, with relatively unchanged sea ice in the Antarctic compared to simulations using a constant salinity profile. While this is consistent with the findings of uncoupled ice‐ocean model studies, the role of the frazil and congelation growth is more important in fully coupled simulations. Melt pond drainage is also an important contribution to simulated ice thickness differences as also found in the uncoupled simulations of Turner and Hunke (2015; https://doi.org/10.1002/2014JC010358 ). However, it is an interaction of the ponds and the snow fraction that impacts the surface albedo and hence the top melt. The changes in the thermodynamics and resulting ice state modify the ice‐ocean‐atmosphere fluxes with impacts on the atmosphere and ocean states, particularly temperature.

Bailey, David A.↗

Quantitative investigation of surface structure and interatomic potential with impact-collision ion scattering spectroscopy

Helium ion beam interactions with materials have important implications for magnetic confinement fusion, material modification, and helium ion microscopy. These interactions depend on the precise physics of how helium ions channel into the materials, which can vary greatly based on the local crystalline orientation. Here, we performed a dedicated experiment to investigate helium ion channeling in a well-characterized tungsten single crystal. Time-of-flight impact-collision ion scattering spectroscopy was used to obtain multi-angle maps of the backscattering intensity for 3 keV He + → W(111). We found that the backscattering intensity profile arising from helium ion channeling could be well described by a shadow cone analysis. This analysis revealed that subsurface W atoms as deep as the ninth monolayer contributed to the backscattering intensity profile. Binary collision approximation simulations were performed with MARLOWE to model the experimental maps with sufficient accuracy to allow for quantitative comparisons using reliability factors. These quantitative comparisons were applied to investigate how the W lattice structure and He–W interatomic potential affect the multi-angle maps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Impact of impurities on peeling–ballooning modes and turbulence in tokamak plasmas

This study investigates the impact of various impurity species on peeling–ballooning (PB) modes and microturbulence in tokamak plasmas through the extension of traditional two-fluid and gyro-landau-fluid (GLF) models. By incorporating finite Larmor radius (FLR) effects, the analysis provides a comprehensive understanding of impurity-driven impact and its interaction with plasma turbulence. Depending on charge state and local plasma conditions, heavy impurities may exhibit gyro-radii larger than those of main ions, which are captured in the extended GLF model presented. Following the presentation of modified two-fluid equations incorporating impurity effects, we systematically analyze the distinctions between impurity and main ion dynamics and their resultant feedback mechanisms on plasma behavior. Derivation of the linear dispersion relation enables quantification of impurity-mediated modifications to: plasma vorticity, diamagnetic drift and gyroviscous effects, electron Hall physics, and FLR effects. BOUT++ – based linear simulations corroborate this formalism, demonstrating systematic stabilization of PB modes upon impurity seeding. And then operational implications for practical impurity control strategies in tokamak devices are proposed. The results underscore the necessity of impurity management to maintain stability and optimize plasma confinement, with specific focus on how FLR effects contribute to transport dynamics. This work paves the way for enhanced modeling and simulation efforts, supporting the development of strategies to control impurity-induced turbulence and improve overall reactor performance.

BOUT++ simulation↗

Engineered Wood: Sustainable Technologies and Applications

Natural wood has been used for construction, fuel, and furniture for thousands of years because of its versatility, renewability, and aesthetic appeal. However, new opportunities for wood are arising as researchers have developed ways to tune the material's optical, thermal, mechanical, and ionic transport properties by chemically and physically modifying wood's naturally porous structure and chemical composition. Such modifications can be used to produce sustainable, functional materials for various emerging applications such as automobiles, construction, energy storage, and environmental remediation. In this review, we highlight recent advancements in engineered wood for sustainable technologies, including thermal and light management, environmental remediation, nanofluidics, batteries, and structural materials with high strength-to-weight ratios. Additionally, the current challenges, opportunities, and future of wood research are discussed, providing a guideline for the further development of next-generation, sustainable wood-based materials.

36 MATERIALS SCIENCE↗

Cloud Processing of Aerosol during SAIL Field Campaign Report

Globally, on average, the release rate of aerosols from clouds is estimated to be about 6,000 Tg/yr and an aerosol particle is estimated to experience about three cloud cycles. Cloud processing of aerosol produces aerosols that have dramatically different physicochemical properties compared to their original form. Cloud processing may transform particles to efficient cloud condensation nuclei (CCN) or ice nucleating particles (INP) that can further participate in cloud formation. We investigated cloud processing of aerosol during the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign using multi-modal offline analysis techniques available at DOE’s Environmental Molecular Sciences Laboratory (EMSL). The main scientific aim of this project was to understand the processes that transform aerosols (chemically, and physically), and influence aerosol-cloud interactions. Aerosol particles undergo significant modifications due to warm (cloud droplets) and cold cloud (ice crystals) processing. Cloud processing of aerosol has important effects on the atmospheric aerosol number and mass concentration, size distribution, phase separation, and chemical composition.

54 ENVIRONMENTAL SCIENCES↗

Materials Based on Technical Bulk Lignin

Lignin is the second most abundant biopolymer and the main source of aromatic structures on earth. Lignin has long been produced as a byproduct of the pulping process and utilized in low value-added applications like heat. However, lignin has received increased attention in recent years to improve its value through various chemical processes. This Review compiles recent progress in synthesis, properties, and applications of lignin-based materials. The lignin for material applications can often be classified into three categories: technical bulk lignin (TBL), lignin-derived oligomers (LDOs), and lignin-derived phenols (LDPs). Furthermore, this Review focuses on the chemical modifications of TBLs and their applications in novel smart materials like self-healing, stimulus responsive, and shape memory polymers. The conversion of TBL to polymers can be briefly divided into two steps: (1) introduction of polymerizable functional groups into the lignin backbone and (2) polymerization that achieves desired materials. Both lignin functionalization and polymerization approaches are discussed in detail. As such, this work attempts to provide a comprehensive overview that highlights the importance of these approaches for the utilization of the abundant but largely ignored biopolymer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic modification of functionality in disordered elastic networks through free energy surface tailoring

A combined machine learning–physics–based approach is explored for molecular and materials engineering. Specifically, collective variables, akin to those used in enhanced sampled simulations, are constructed using a machine learning model trained on data gathered from a single system. Through the constructed collective variables, it becomes possible to identify critical molecular interactions in the considered system, the modulation of which enables a systematic tailoring of the system’s free energy landscape. To explore the efficacy of the proposed approach, we use it to engineer allosteric regulation and uniaxial strain fluctuations in a complex disordered elastic network. Its successful application in these two cases provides insights regarding how functionality is governed in systems characterized by extensive connectivity and points to its potential for design of complex molecular systems.

42 ENGINEERING↗

Accidental suppression of Wilson coefficients in Higgs coupling

Higgs couplings are essential probes for physics beyond the Standard Model (BSM) since they can be modified by new physics, such as through the Higgs portal interaction |H| 2 Ο. These modifications influence Higgs interactions via dimension-6 operators of the form (∂|H| 2 ) 2 and |H| 6 , which are generally expected to be of comparable size. This paper discusses a phenomenon of accidental suppression, where the |H| 6 coupling is significantly smaller than (∂|H| 2 ) 2 . This suppression, arising from the truncation of the tree-level effective potential, lacks a clear symmetry explanation but persists in portal models. This paper aims to inspire further studies on additional instances of accidental suppression without symmetry explanations or a general framework to characterize such suppression. We also discuss constraints, at the HL-LHC and future colliders, on the Wilson coefficients of the two dimension-6 operators for various benchmark scenarios of the concrete model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Nuclear modification factors for jet fragmentation

Using a recently-developed perturbative-QCD approach for jet evolution in a dense quark-gluon plasma, we study the nuclear modification factor for the jet fragmentation function. The qualitative behaviour that we find is in agreement with the respective experimental observations in Pb+Pb collisions at the LHC: a pronounced nuclear enhancement at both ends of the spectrum. Our Monte Carlo simulations are supplemented with analytic estimates which clarify the physical interpretation of the results. The main source of theoretical uncertainty is the sensitivity of our calculations to a low-momentum cutoff which mimics confinement. To reduce this sensitivity, we propose a new observable, which describes the jet fragmentation into subjets and is infrared-and-collinear safe by construction. We present Monte Carlo predictions for the associated nuclear modification factor together with their physical interpretation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗