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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Needle-Like Ferroelastic Domains in Individual Ferroelectric Nanoparticles

Superior structural, physical and electronic properties make ferroelectric nanocrystals essential in enabling a range of next-generation devices. Ferroelectric responses are determined by crystal structure and domain morphology. The ability to reversibly displace, create and annihilate elastic domains is critical to device applications. Whereas electric-field control has been demonstrated for ferroelectric 180° surface domain walls and vortices, similar control of ferroelastic domains and domain boundaries within individual nanocrystals remains challenging. Using controlled external compressive and tensile axial stress, deterministic and reversible control of highly mobile ferroelastic domains and axial polarization in three dimensions is demonstrated in this study. While many studies exist on ferroelastic domains in thin films and bulk, little is known about ferroelastic interactions at the single nanoparticle level, especially involving domain boundaries. Through combining Bragg coherent X-ray diffractive imaging and Landau theory, strain gradients in individual BaTiO3 nanocrystals are shown to stabilize needle-like ferroelastic twin domains. These domains are highly labile under applied axial stress, producing a locally enhanced electric polarization mediated by a ferroelectric phase transition. The efficacy of Bragg coherent X-ray diffractive imaging in studying in operando domains in three-dimensions is demonstrated, while synergy with theory provides a paradigm for domain boundary engineering and potential for nanoscale functional devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Failure investigation of nuclear grade POCO graphite target in high energy neutrino physics through numerical simulation

In many high energy physics neutrino beamlines, targets are made up of isotropic POCO graphite grade for production of neutrinos for high energy particle physics research and are bombarded with highly energetic pulsed proton beam. The pulsed proton beam with a small beam size creates thermal stress waves as well as radiation damage such as displacement damage, void formation, swelling, and gas formation amongst others. As a result, after a few years of operation one of the longest operated targets appears to have undergone bulk swelling and fractured along the beam centerline. A complex interaction of dynamic loading due to beam, material degradation due to irradiation are thought to have caused such a failure. Here, we present a numerical simulation to capture the combined effects of swelling and the dynamic effect of thermal stress waves due to beam heating, to explain the failure of target. An empirical formula has been developed to take into account swelling as a function of temperature and proton fluence and has been implemented in a commercial finite element code. Extensive X-ray diffraction (XRD) were performed on graphite samples from the failed target to understand the lattice parameter changes due to irradiation and build a valid empirical model. Simulation results show that swelling plays a major role in elevating the stress state in the material exceeding the failure strength while the pulsed beam heating also introduces fatigue loading that would explain brittle fracture emanating from inside of the material and propagating outward. Such empirical formulations will help in identifying the threshold values of critical parameters to extend the service life of future multi-megawatt neutrino targets and targets in other accelerator environments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Method for Evaluating Irradiation Effects on Flow Stress in Fe-9%Cr ODS Using TEM In Situ Cantilevers

Transmission electron microscopic (TEM) in situ mechanical testing has become a widely utilized tool for simultaneously measuring mechanical properties and understanding fundamental deformation mechanisms in irradiated and nuclear materials. Although tensile and compression specimen geometries are amongst the most common, opportunities remain for investigating alternative geometries that could provide unique insights into the plasticity of irradiated materials. This research demonstrates a new TEM in situ cantilever beam configuration. Cantilevers are produced from as-received and proton irradiated (1 dpa, 500°C) Fe-9%Cr oxide dispersion strengthened (ODS) steel. Flow stress is measured using a TEM in situ depth-sensing mechanical testing holder. A 200 MPa increase in flow stress is measured due to irradiation. Size effects arise when the intrinsic (i.e. microstructural) size approaches the extrinsic (i.e. external dimensions) size and can be described using a power law relationship as a function of the material microstructure and cantilever dimensions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optical and electronic functionality arising from controlled defect formation in nanoscale complex oxide lateral epitaxy

Epitaxial crystallization of complex oxides provides the means to create materials with precisely selected composition, strain, and orientation, thereby controlling their functionalities. Extending this control to nanoscale three-dimensional geometries can be accomplished via a three-dimensional analog of oxide solid-phase epitaxy, lateral epitaxial crystallization. The orientation of crystals within laterally crystallized SrTiO 3 systematically changes from the orientation of the SrTiO 3 substrate. This evolution occurs as a function of lateral crystallization distance, with a rate of approximately 50° μm -1 . The mechanism of the rotation is consistent with a steady-state stress of tens of megapascal over a 100–nanometer scale region near the moving amorphous/crystalline interface arising from the amorphous-crystalline density difference. Second harmonic generation and piezoelectric force microscopy reveal that the laterally crystallized SrTiO 3 is noncentrosymmetric and develops a switchable piezoelectric response at room temperature, illustrating the potential to use lateral crystallization to control the functionality of complex oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Stress and Curvature Effects in Layered 2D Ferroelectric CuInP 2 S 6

Nanoscale ferroelectric 2D materials offer the opportunity to investigate curvature and strain effects on materials functionalities. Among these, CuInP 2 S 6 (CIPS) has attracted tremendous research interest in recent years due to combination of room temperature ferroelectricity, scalability to a few layers thickness, and ferrielectric properties due to coexistence of 2 polar sublattices. Here, we explore the local curvature and strain effect on polarization in CIPS via piezoresponse force microscopy and spectroscopy. To explain the observed behaviors and decouple the curvature and strain effects in 2D CIPS, we introduce the finite element Landau–Ginzburg–Devonshire model, revealing strong changes in hysteresis characteristics in regions subjected to tensile and compressive strain. The piezoresponse force microscopy (PFM) results show that bending induces ferrielectric domains in CIPS, and the polarization-voltage hysteresis loops differ in bending and nonbending regions. Furthermore, these studies offer insights into the fabrication of curvature-engineered nanoelectronic devices.

2D materials↗
DOE OSTI2024

Halophytes and heavy metals: A multi‐omics approach to understand the role of gene and genome duplication in the abiotic stress tolerance of Cakile maritima

Abstract Premise The origin of diversity is a fundamental biological question. Gene duplications are one mechanism that provides raw material for the emergence of novel traits, but evolutionary outcomes depend on which genes are retained and how they become functionalized. Yet, following different duplication types (polyploidy and tandem duplication), the events driving gene retention and functionalization remain poorly understood. Here we usedCakile maritima, a species that is tolerant to salt and heavy metals and shares an ancient whole‐genome triplication with closely related salt‐sensitive mustard crops (Brassica), as a model to explore the evolution of abiotic stress tolerance following polyploidy. Methods Using a combination of ionomics, free amino acid profiling, and comparative genomics, we characterize aspects of salt stress response inC. maritimaand identify retained duplicate genes that have likely enabled adaptation to salt and mild levels of cadmium. Results Cakile maritimais tolerant to both cadmium and salt treatments through uptake of cadmium in the roots. Proline constitutes greater than 30% of the free amino acid pool inC. maritimaand likely contributes to abiotic stress tolerance. We find duplicated gene families are enriched in metabolic and transport processes and identify key transport genes that may be involved inC. maritimaabiotic stress tolerance. Conclusions These findings identify pathways and genes that could be used to enhance plant resilience and provide a putative understanding of the roles of duplication types and retention on the evolution of abiotic stress response.

Plant Sciences↗
DOE OSTI2021

SIRT3 mediates mitofusin 2 ubiquitination and degradation to suppress ischemia reperfusion-induced acute kidney injury

Ischemia reperfusion-induced acute kidney injury (IR-induced AKI) is a life-threatening disease with many complications. Mitofusin 2 (Mfn2) ubiquitination is related to AKI. But the underlying molecular mechanisms remain unknown. This study aimed to probe the mechanism of Mfn2 ubiquitination in IR-induced AKI development. In IR-induced AKI mouse models, orbital blood and urine were collected for assessing kidney function. The kidney injury, ultrastructure of mitochondria, and histopathology in mice were evaluated after injection of G5, an ubiquitination inhibitor. Oxygen glucose deprivation/reoxygenation (OGD/R) models were established in HK-2 cells, and the mitochondria were extracted. Cell viability, apoptosis, oxidative stress, inflammatory reaction, mitochondrial membrane potential, and ATP production were measured. Mfn2 ubiquitination in mouse and cell models was evaluated. si-SIRT3 and pcDNA3.1-SIRT3 were transfected into cell models. Consequently, kidney function in mice was impaired by IR-induced AKI. Mfn2 ubiquitination and degradation promoted IR-induced AKI. OGD/R induced renal tubular epithelial cell injury and disrupted mitochondrial dynamics and functions through promoting Mfn2 ubiquitination. SIRT3 knockdown led to Mfn2 ubiquitination by binding to UBC; while its overexpression alleviated tubular epithelial cell injury. Briefly, SIRT3 mediates Mfn2 ubiquitination to relieve IR-induced AKI. This investigation may offer new insights for the treatment of IR-induced AKI injury.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A behavior and physiology-based decision support tool to predict thermal comfort and stress in non-pregnant, mid-gestation, and late-gestation sows

Background: Although thermal indices have been proposed for swine, none to our knowledge differentiate by reproductive stage or predict thermal comfort using behavioral and physiological data. The study objective was to develop a behavior and physiology-based decision support tool to predict thermal comfort and stress in multiparous (3.28 ± 0.81) non-pregnant (n = 11), mid-gestation (n = 13), and late-gestation (n = 12) sows. Results: Regression analyses were performed using PROC MIXED in SAS 9.4 to determine the optimal environmental indicator [dry bulb temperature (T DB ) and dew point] of heat stress (HS) in non-pregnant, mid-gestation, and late-gestation sows with respiration rate (RR) and body temperature (T B ) successively used as the dependent variable in a cubic function. A linear relationship was observed for skin temperature (T S ) indicating that TDB rather than the sow HS response impacted TS and so TS was excluded from further analyses. Reproductive stage was significant for all analyses (P < 0.05). Heat stress thresholds for each reproductive stage were calculated using the inflections points of RR for mild HS and T B for moderate and severe HS. Mild HS inflection points differed for non-pregnant, mid-gestation, and late gestation sows and occurred at 25.5, 25.1, and 24.0 °C, respectively. Moderate HS inflection points differed for non-pregnant, mid-gestation, and late gestation sows and occurred at 28.1, 27.8, and 25.5 °C, respectively. Severe HS inflection points were similar for non-pregnant and mid-gestation sows (32.9 °C) but differed for late-gestation sows (30.8 °C). These data were integrated with previously collected behavioral thermal preference data to estimate the T DB that non-pregnant, mid-gestation, and late-gestation sows found to be cool (T DB < T DB preference range), comfortable (T DB = T DB preference range), and warm (T DB preference range < T DB < mild HS). Conclusions: The results of this study provide valuable information about thermal comfort and thermal stress thresholds in sows at three reproductive stages. The development of a behavior and physiology-based decision support tool to predict thermal comfort and stress in non-pregnant, mid-gestation, and late-gestation sows is expected to provide swine producers with a more accurate means of managing sow environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Lectin Receptor-Like Kinases: The Sensor and Mediator at the Plant Cell Surface

Lectin receptor-like kinases (LecRLKs), a plant-specific receptor-like kinase (RLK) sub-family, have been recently found to play crucial roles in plant development and responses to abiotic and biotic stresses. In this review, we first describe the classification and structures of Lectin RLKs. Then we focus on the analysis of functions of LecRLKs in various biological processes and discuss the status of LecRLKs from the ligands they recognize, substrate they target, signaling pathways they are involved in, to the overall regulation of growth-defense tradeoffs. LecRLKs and the signaling components they interact with constitute recognition and protection systems at the plant cell surface contributing to the detection of environmental changes monitoring plant fitness.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Eulerian and Lagrangian second-order statistics of superfluid 4 He grid turbulence

Here, we use particle-tracking velocimetry to study Eulerian and Lagrangian second-order statistics of superfluid 4 He grid turbulence. The Eulerian energy spectra at scales larger than the mean distance between quantum vortex lines behave classically with close to Kolmogorov-1941 scaling and are almost isotropic. The Lagrangian second-order structure functions and frequency power spectra, measured at scales comparable with the intervortex distance, demonstrate a sharp transition from nearly classical behavior to a regime dominated by the motion of quantum vortex lines. Employing the homogeneity of the flow, we verify a set of relations that connect various second-order statistical objects that stress different aspects of turbulent behavior, allowing a multifaceted analysis. We use the two-way bridge relations between Eulerian energy spectra and second-order structure functions to reconstruct the energy spectrum from the known second-order velocity structure function and vice versa. The Lagrangian frequency spectrum reconstructed from the measured Eulerian spectrum using the Eulerian-Lagrangian bridge differs from the measured Lagrangian spectrum in the quasiclassical range, which calls for further investigation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence

In the present study, we investigate different data-driven parameterizations for large eddy simulation of two-dimensional turbulence in the a priori settings. These models utilize resolved flow field variables on the coarser grid to estimate the subgrid-scale stresses. We use data-driven closure models based on localized learning that employs a multilayer feedforward artificial neural network with point-to-point mapping and neighboring stencil data mapping, and convolutional neural network fed by data snapshots of the whole domain. The performance of these data-driven closure models is measured through a probability density function and is compared with the dynamic Smagorinksy model (DSM). The quantitative performance is evaluated using the cross-correlation coefficient between the true and predicted stresses. We analyze different frameworks in terms of the amount of training data, selection of input and output features, their characteristics in modeling with accuracy, and training and deployment computational time. We also demonstrate computational gain that can be achieved using the intelligent eddy viscosity model that learns eddy viscosity computed by the DSM instead of subgrid-scale stresses. Here, we detail the hyperparameters optimization of these models using the grid search algorithm.

42 ENGINEERING↗
DOE OSTI2021

Surface Sampling Techniques for the Canister Deposition Field Demonstration

This report describes plans for dust sampling and analysis for the multi-year Canister Deposition Field Demonstration. The demonstration will use three commercial 32PTH2 NUHOMS welded stainless steel storage canisters, which will be stored at an ISFSI site in Advanced Horizontal Storage Modules. One canister will be unheated; the other two will have heaters to achieve canister surface temperatures that match, to the degree possible, spent nuclear fuel (SNF) loaded canisters with heat loads of 10 kW and 40 kW. Surface sampling campaigns will take place on a yearly or bi-yearly basis. The goal of the planned dust sampling and analysis is to determine important environmental parameters that impact the potential occurrence of stress corrosion cracking on SNF dry storage canisters. Specifically, the size, morphology, and composition of the deposited dust and salt particles will be quantified, as well as the soluble salt load per unit area and the rate of deposition, as a function of canister surface temperature, location, time, and orientation. Sampling locations on the canister surface will nominally include 25 locations, corresponding to 5 circumferential locations at each of the 5 longitudinal locations. At each sampling location, a 2x2 sampling grid (containing 4 sample cells) will be painted onto the metal surface. During each sampling campaign, two samples at each sampling location will be collected, in a specific routine to measure both periodic (yearly or bi-yearly) and cumulative deposition rates. For each sample, a wet and a dry sample will be collected. Wet samples will be analyzed to determine the composition of the soluble salt fraction and to estimate salt loading per unit area. Dry samples will be analyzed to assess particle size, morphology, mineralogy, and identity (e.g. for floral/faunal fragments). The data generated by this proposed sampling plan will provide detailed information on dust and salt aerosol deposits on spent nuclear fuel canister surfaces. The anticipated results include information regarding particle compositions, size distributions, and morphologies, in addition to particle deposition rates as a function of canister surface location, orientation, time, and temperature. The information gathered during the Canister Deposition Field Demonstration is critical for ongoing efforts to develop a detailed understanding of the potential for stress corrosion cracking on SNF dry storage canisters

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

A probabilistic creep model incorporating test condition, initial damage, and material property uncertainty

Uncertainty is prevalent in the creep resistance of alloys, where at elevated temperature and low pressure, rupture can range across logarithmic decades. In this study, a probabilistic continuum-damage-mechanics (CDM)-based model is derived to capture the uncertainty of creep resistance. To meet this objective, creep data for alloy 304 Stainless Steel is gathered. A constitutive model, “Sinh”, is calibrated deterministically to determine the statistical variability of the material properties. Three sources of uncertainty are injected into the model: test condition (stress and temperature), initial damage, and material properties. Probabilistic simulations are carried out by (a) calibrating probability distribution functions (pdfs) for each source of uncertainty (b) randomly sampling the pdfs using Monte Carlo methods and (c) executing simulations to replicate the uncertain creep behavior. A sensitivity analysis is performed to evaluate the relative effect of each source of uncertainty. In full probabilistic simulations, the cumulative uncertainty of creep behavior is evaluated. The probabilistic model accurately predicts the creep deformation and rupture of the available experiments. The probabilistic model is validated for interpolation but lacks extrapolation ability. Several future works are proposed to further improve the model.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Computer-controlled finishing via dynamically constraint position-velocity-time scheduler

In a Computer Numerical Controlled (CNC) finishing process, the target material removal from an optical surface is guided by the convolution between the influence function of a machine tool and its dwell time at certain points over the surface. To reduce dynamics stressing and increase machining efficiency, the dwell time must be converted to varying velocities, which are the actual inputs to the machine tool controller. Conventionally, the conversion assumed constant acceleration and relied on linear motion interpolation, which caused discontinuities in velocities. This unsmooth motion affects the material removal distribution, and, thus, the accuracy of the finished surface shape. Many modern CNC machines support the smoother, cubic-polynomial interpolated Position-Velocity-Time (PVT) motion mode; however, the conventional scheduler may fail to provide suitable velocities for the PVT. Here in this study answers this challenge by proposing a novel PVT-based velocity scheduler that achieves smooth motion while considering CNC dynamic limits. Firstly, the principle of the PVT is explained, and the PVT-based velocity scheduler is formulated. Secondly, a quadratic programming is used to optimize the velocities by imposing the CNC dynamic constraints and the C 1 continuities (zeroth and first derivatives are continuous) simultaneously. Thirdly, the smoothness and accuracy of the scheduled velocities are studied on different kinds of tool paths via simulation. Finally, a sub-0.3 nm level surface finishing experiment using ion beam figuring is demonstrated to verify the feasibility of the proposed method. The PVT-based scheduler and simulator code is open-sourced.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chlorophyllase from Arabidopsis thaliana Reveals an Emerging Model for Controlling Chlorophyll Hydrolysis

Chlorophyll (Chl) is one of Nature’s most complex pigments to biosynthesize and derivatize. This pigment is vital for survival and also paradoxically toxic if overproduced or released from a protective protein scaffold. Therefore, along with the mass production of Chl, organisms also invest in mechanisms to control its degradation and recycling. One important enzyme that is involved in these latter processes is chlorophyllase. This enzyme is employed by numerous photosynthetic organisms to hydrolyze the phytol tail of Chl. Although traditionally thought to catalyze the first step of Chl degradation, recent work suggests that chlorophyllase is instead employed during times of abiotic stress or conditions that produce reactive oxygen species. However, the molecular details regarding how chlorophyllases are regulated to function under such conditions remain enigmatic. Here, we investigate the Arabidopsis thaliana chlorophyllase isoform AtCLH2 using site-directed mutagenesis, mass spectrometry, dynamic light scattering, size-exclusion multiangle light scattering, and both steady-state enzyme kinetic and thermal stability measurements. Through these experiments, we show that AtCLH2 exists as a monomer in solution and contains two disulfide bonds. One disulfide bond putatively maps to the active site, whereas the other links two N-terminal Cys residues together. These disulfide bonds are cleaved by chemical or chemical and protein-based reductants, respectively, and are integral to maintaining the activity, stability, and substrate scope of the enzyme. This work suggests that Cys residue oxidation in chlorophyllases is an emerging regulatory strategy for controlling the hydrolysis of Chl pigments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Urban Forests as Main Regulator of the Evaporative Cooling Effect in Cities

Abstract Higher temperatures in urban areas expose a large fraction of the human population to potentially dangerous heat stress. Green spaces are promoted worldwide as local and city‐scale cooling strategies but the amount, type, and functioning of vegetation in cities lack quantification and their interaction with urban climate in different settings remains a matter of debate. Here we use state‐of‐the‐art remote sensing data from 145 city clusters to disentangle the drivers of surface urban heat islands (SUHI) intensity and quantify urban‐rural differences in vegetation cover, species composition, and evaporative cooling. We show that nighttime SUHIs are affected mostly by abiotic factors, while daytime SUHIs are highly correlated with vegetation characteristics and the wetness of the background climate. Magnitude and seasonality of daytime SUHIs are controlled by urban‐rural differences in plant transpiration and leaf area, which explain the dependence of SUHIs on wetness conditions. Leaf area differences are caused primarily by changes in vegetation type and a loss of in‐city forested areas, highlighting the importance of maintaining “natural reserves” as a sustainable heat mitigation policy.

Paschalis, Athanasios↗
DOE OSTI2021

A Modified Vegetation Photosynthesis and Respiration Model (VPRM) for the Eastern USA and Canada, Evaluated With Comparison to Atmospheric Observations and Other Biospheric Models

Atmospheric CO 2 measurements from a dense surface network can help to evaluate terrestrial biosphere model (TBM) simulations of Net Ecosystem Exchange (NEE) with two key benefits. First, gridded CO 2 flux estimates can be evaluated over regional scales, not possible using flux tower observations at discrete locations for model evaluation. Second, TBM ability to explain atmospheric CO 2 fluctuations due to the biosphere can be directly tested, an important objective for anthropogenic emissions monitoring using atmospheric observations. Here, we customize the Vegetation Photosynthesis and Respiration Model (VPRM) for an eastern North American domain with strong biological activity upwind of urban areas. Parameters are optimized using flux tower observations from a historical database with sites in (and near) the domain. In addition, the respiration model (originally a linear function of temperature) is modified to account for impacts of changing foliage, non-linear temperature, and water stress. Flux estimates from VPRM, the Carnegie-Ames-Stanford Approach (CASA) model and the Simple Biosphere Model v4 (SiB4), are convolved with footprints from atmospheric transport models for evaluation with CO 2 observations at 21 towers in the domain, with roughly half of the towers used here for the first time. Results show that the new respiration model in VPRM helps to correct a growing season sink bias in the atmosphere associated with underestimated summertime respiration using the original model with annual parameters. The new VPRM also better explains fine-scale atmospheric CO 2 variability compared to other TBMs, due to higher resolution diagnostic phenology, the new respiration model, domain-specific parameters, and high-quality input data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Inverse design of cellular structures with the targeted nonlinear mechanical response

Advanced additive manufacturing capabilities have enabled a transformational ability to create sophisticated cellular structures using diverse materials. By altering the topology of the unit cell, the mechanical behavior, such as the stress-strain response during compression, can be modulated. Nevertheless, identifying a printable topology within an enormous design space that would precisely deliver the targeted nonlinear material response is challenging. We propose a data-driven generative framework based on a conditional variational autoencoder (cVAE) architecture that can inverse design the cellular structure based on the intended nonlinear stress-strain response. Trained on a dataset of structure-property pairs, the cVAE learns a compact and expressive latent space that enables efficient mapping from targets to feasible geometries. Two inference modes are explored: (1) decoder-only generation, which enables the exploration of diverse designs conditioned solely on the desired mechanical response, and (2) encoder-decoder generation, which further allows for the incorporation of desired topologies, ensuring the generated structure conforms to both mechanical properties and to desired-topology constraints. The results demonstrate that the model can generate structurally plausible and mechanically accurate designs, with the predicted stress-strain curves closely matching the targets. Even under joint conditioning, the model effectively balances geometric fidelity and functional performance.

36 MATERIALS SCIENCE↗