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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Five-Year Outcomes, Cosmesis, and Toxicity With 3-Dimensional Conformal External Beam Radiation Therapy to Deliver Accelerated Partial Breast Irradiation

Purpose: To report the interim results from a study comparing the efficacy, toxicity, and cosmesis of breast-conserving treatment with accelerated partial breast irradiation (APBI) or whole breast irradiation (WBI) using 3-dimensional conformal external beam radiation therapy (3D-CRT). Methods and Materials: 102 patients with early-stage breast cancer who underwent breast-conserving surgery were randomized to receive either WBI (n=51) or APBI (n=51). In the WBI arm, 48 Gy was delivered to the whole breast in daily fractions of 2 Gy, with or without additional 10 Gy to the tumor bed. In the APBI arm, patients received 37.5 Gy in 3.75 Gy per fraction delivered twice daily. Toxicity results were scored according to the Radiation Therapy Oncology Group Common Toxicity Criteria. Skin elasticity was measured using a dedicated device (Multi-Skin-Test-Center MC-750-B2, CKelectronic-GmbH). Cosmetic results were assessed by the physician and the patients as good/excellent, regular, or poor. Results: The median follow-up time was 5 years. No local recurrences were observed. No significant differences in survival rates were found. APBI reduced acute side effects and radiation doses to healthy tissues compared with WBI (P<.01). Late skin toxicity was no worse than grade 2 in either group, without significant differences between the 2 groups. In the ipsilateral breast, the areas that received the highest doses (ie, the boost or quadrant) showed the greatest loss of elasticity. WBI resulted in a greater loss of elasticity in the high-dose area compared with APBI (P<.05). Physician assessment showed that >75% of patients in the APBI arm had excellent or good cosmesis, and these outcomes appear to be stable over time. The percentage of patients with excellent/good cosmetic results was similar in both groups. Conclusions: APBI delivered by 3D-CRT to the tumor bed for a selected group of early-stage breast cancer patients produces 5-year results similar to those achieved with conventional WBI.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

The influence of preexisting host rock damage on fault network localization

The transition from stable to unstable fracture propagation occurs when fractures begin to interact and link. Thus, fracture network coalescence controls how rocks and engineered structures fail. Here, to constrain the factors that influence localization in shear zones under brittle conditions, we build discrete element method models with a rough fault embedded in a shear zone. We add varying numbers of diffuse, randomly-placed weaknesses to examine the influence of diffuse damage on fracture network localization. The number of weaknesses controls the localization behavior of the fault network and the final fault geometry. We quantify localization using the Gini coefficient of the fracture volume, which measures the nonuniformity in a population. Each model generally increases in localization toward failure. However, models with more diffuse damage experience delocalization phases that are superimposed on the overall trend of increasing localization. The observed link between delocalization and host rock damage may help explain the varying localization of low magnitude seismicity in southern California. Models with more diffuse damage produce more complex fault geometries comprised of several parallel strands of wing cracks. The propagation of these wing cracks reduces the shear stress acting on the model boundaries, indicating that this fracture development increases the mechanical efficiency of the system.

58 GEOSCIENCES↗
DOE OSTI2017

A low-temperature synthetic route to ternary iron-manganese metal fluorides nanoparticles

Ternary metal fluoride Fe{sub x}Mn{sub 1−x}F{sub 2} (x = 0.00, 0.25, 0.50, 0.75, and 1.00), which is a potential cathode material for next-generation Li-ion batteries, were synthesized via a convenient, low-temperature, bottom-up solution-phase method. The lattice dimensions deduced from X-ray diffraction suggested formation of homogeneous solid solutions. With increasing Fe content, the morphology of the solid changed from cubic particles to dendritic, with an average particle size of 20–40 nm. The results suggested that this synthetic method constitutes a translatable route to large-scale production of ternary metal fluoride nanoparticles. - Graphical abstract: Homogeneous random solid solutions of ternary metal fluoride Fe{sub x}Mn{sub 1−x}F{sub 2} can be prepared by room temperature coprecipitation of precursors followed by drying and calcination at 350 °C. Display Omitted - Highlights: • Homogeneous ternary mixed metal iron-manganese fluoride Fe{sub x}Mn{sub 1−x}F{sub 2} nanoparticles prepared by room temperature coprecipitation and calcination. • Fe{sub x}Mn{sub 1−x}F{sub 2} nanoparticles form different morphology aggregates depending on the composition. • Lattice dimensions from X-ray diffraction suggested formation of homogeneous solid solutions.

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

Long-term thermal stability and calibration of Type-II fiber Bragg grating array inscribed in radiation-hardened fibers

This paper investigates the long-term thermal stability of Type-II fiber Bragg grating (FBG) arrays, inscribed by femtosecond laser in radiation-hardened fiber, for potential applications as multiplexed sensors in high-temperature energy systems. The thermal stability of FBG sensors was assessed through 16 thermal cycles from room temperature (RT) to 750 ℃ about two months, involving 100 FBG sensors. The results show that the absolute temperature drift of FBG sensors can be reduced to less than 0.4 pm/day after 54 h thermal annealing process at a constant temperature of 800 ℃. As temperature sensors, the FBGs demonstrated stable performance, achieving a standard deviation (STD) of 1.8 pm (corresponding to a temperature resolution of 0.118 ℃) post-annealing. Repeated thermal cycles revealed a random drift of 2.3 pm in the FBG wavelength at RT. Polynomial fitting was explored as a calibration method to convert FBG wavelength shifts into absolute temperature measurements. By optimizing calibration temperature points (RT, 200 ℃, 400 ℃, and 750 ℃), the study shows that cubic polynomial calibration using four points yields an average R2 of 0.9997 and an RMSE of 3.58 ℃ across the entire temperature range (RT to 750 ℃). This approach represents an 11.53-fold improvement over empirical slope calibration and a 1.34-fold improvement over four-point piecewise fitting. The findings indicate that Type-II FBGs inscribed in radiation-hardened fibers can function as accurate temperature sensors, with performance on par with or exceeding that of thermocouples. With their multiplexing capability, robust signal transmission over long lead cables, and immunity to electromagnetic interference, FBG sensors offer a promising alternative to traditional electronic sensors for energy system monitoring.

Dominguez-Ontiveros, Elvis [ORNL] (ORCID:000000018↗
DOE OSTI2022

Sensitivity and uncertainty of the IFR-1 BISON benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered for adoption by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This paper summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment.For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. Here, the resulting variations in benchmark predictions were normalized to calculate sensitivities. These sensitivities were then used to inform input selections for the UQ.The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of the benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because the confidence intervals associated with benchmark predictions were wide. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

MAXIMUM LIKELIHOOD FITTING OF X-RAY POWER DENSITY SPECTRA: APPLICATION TO HIGH-FREQUENCY QUASI-PERIODIC OSCILLATIONS FROM THE NEUTRON STAR X-RAY BINARY 4U1608-522

High-frequency quasi-periodic oscillations (QPOs) from weakly magnetized neutron stars display rapid frequency variability (second timescales) and high coherence with quality factors up to at least 200 at frequencies about 800-850 Hz. Their parameters have been estimated so far from standard min({chi}{sup 2}) fitting techniques, after combining a large number of power density spectra (PDS), to have the powers normally distributed (the so-called Gaussian regime). Before combining PDS, different methods to minimize the effects of the frequency drift to the estimates of the QPO parameters have been proposed, but none of them relied on fitting the individual PDS. Accounting for the statistical properties of PDS, we apply a maximum likelihood method to derive the QPO parameters in the non-Gaussian regime. The method presented is general, easy to implement, and can be applied to fitting individual PDS, several PDS simultaneously, or their average, and is obviously not specific to the analysis of kHz QPO data. It applies to the analysis of any PDS optimized in frequency resolution and for low-frequency variability or PDS containing features whose parameters vary on short timescales, as is the case for kHz QPOs. It is equivalent to the standard {chi}{sup 2} minimization fitting when the number of PDS fitted is large. The accuracy, reliability, and superiority of the method is demonstrated with simulations of synthetic PDS, containing Lorentzian QPOs of known parameters. Accounting for the broadening of the QPO profile, due to the leakage of power inherent to windowed Fourier transforms, the maximum likelihood estimates of the QPO parameters are asymptotically unbiased and have negligible bias when the QPO is reasonably well detected. By contrast, we show that the standard min({chi}{sup 2}) fitting method gives biased parameters with larger uncertainties. The maximum likelihood fitting method is applied to a subset of archival Rossi X-ray Timing Explorer data of the neutron star X-ray binary 4U1608-522, for which we show that the lower kHz QPO parameters can be measured on timescales as short as 8 s. To demonstrate the potential use of the results of the maximum likelihood method, we show that in the observation analyzed the time evolution of the frequency is consistent with a random walk. We then show that the broadening of the QPO due to the frequency drift scales as {radical}T, as expected from a random walk (T is the integration time of the PDS). This enables us to estimate the intrinsic quality factor of the QPO to be {approx}260, whereas previous analysis indicated a maximum value around 200.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Rapid estimation of earthquake locations using waveform traveltimes

SUMMARY We introduce a new approach for locating earthquakes using arrival times derived from waveforms. The most costly computational step of the algorithm scales as the number of stations in the active seismographic network. In this approach, a variation on existing grid search methods, a series of full waveform simulations are conducted for all receiver locations, with sources positioned successively at each station. The traveltime field over the region of interest is calculated by applying a phase picking algorithm to the numerical wavefields produced from each simulation. An event is located by subtracting the stored traveltime field from the arrival time at each station. This provides a shifted and time-reversed traveltime field for each station. The shifted and time-reversed fields all approach the origin time of the event at the source location. The mean or median value at the source location thus approximates the event origin time. Measures of dispersion about this mean or median time at each grid point, such as the sample standard error and the average deviation, are minimized at the correct source position. Uncertainty in the event position is provided by the contours of standard error defined over the grid. An application of this technique to a synthetic data set indicates that the approach provides stable locations even when the traveltimes are contaminated by additive random noise containing a significant number of outliers and velocity model errors. It is found that the waveform-based method out-performs one based upon the eikonal equation for a velocity model with rapid spatial variations in properties due to layering. A comparison with conventional location algorithms in both a laboratory and field setting demonstrates that the technique performs at least as well as existing techniques.

58 GEOSCIENCES↗
DOE OSTI2023

Operator Relaxation and the Optimal Depth of Classical Shadows

Classical shadows are a powerful method for learning many properties of quantum states in a sample-efficient manner, by making use of randomized measurements. Here we study the sample complexity of learning the expectation value of Pauli operators via “shallow shadows,” a recently proposed version of classical shadows in which the randomization step is effected by a local unitary circuit of variable depth t. Here we show that the shadow norm (the quantity controlling the sample complexity) is expressed in terms of properties of the Heisenberg time evolution of operators under the randomizing (“twirling”) circuit—namely the evolution of the weight distribution characterizing the number of sites on which an operator acts nontrivially. For spatially contiguous Pauli operators of weight k, this entails a competition between two processes: operator spreading (whereby the support of an operator grows over time, increasing its weight) and operator relaxation (whereby the bulk of the operator develops an equilibrium density of identity operators, decreasing its weight). From this simple picture we derive (i) an upper bound on the shadow norm which, for depth t~log⁡(k), guarantees an exponential gain in sample complexity over the t=0 protocol in any spatial dimension, and (ii) quantitative results in one dimension within a mean-field approximation, including a universal subleading correction to the optimal depth, found to be in excellent agreement with infinite matrix product state numerical simulations. Our Letter connects fundamental ideas in quantum many-body dynamics to applications in quantum information science, and paves the way to highly optimized protocols for learning different properties of quantum states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Surrogate models for linear response

Linear response theory is a well-established method in physics and chemistry for exploring excitations of many-body systems. In particular, the quasiparticle random-phase approximation (QRPA) provides a powerful microscopic framework by building excitations on top of the mean-field vacuum; however, its high computational cost limits model calibration and uncertainty quantification studies. Here, we present two complementary QRPA surrogate models and apply them to study response functions of finite nuclei. One is a reduced-order model that exploits the underlying QRPA structure, while the other utilizes the recently developed parametric matrix model algorithm to construct a map between the system’s Hamiltonian and observables. Our benchmark applications, the calculation of the electric dipole polarizability of 180 Yb and the 𝛽-decay half-life of 80 Ni, show that both emulators can achieve 0.1%–1% accuracy while offering a 6–7 orders of magnitude speedup compared to state-of-the-art QRPA solvers. These results demonstrate that the developed QRPA emulators are well positioned to enable Bayesian calibration and large-scale studies of computationally expensive physics models describing the properties of many-body systems.

Beta decay↗
DOE OSTI2026

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Boundary-Aware Adversarial Learning Domain Adaption and Active Learning for Cross-Sensor Building Extraction

The use of convolutional neural networks (CNNs) for building extraction from remote sensing images has been widely studied and many public datasets have been made available for accelerating development of these CNN models. Yet adapting pretrained models at scale in real-world scenarios remains a challenging task. The main barrier is that certain new labels are still needed to compensate for domain shifting between the labeled data and new images that potentially cover new geographic locations or that are from a different sensor. In this article, we propose to add informatively labeled samples from a new image pool under the paradigm of active learning. To select the most useful samples based on model uncertainty, we first tackle the problem of uncalibrated uncertainty estimation due to distribution shifting by adapting feature extractors with boundary-based adversarial learning. Calibrated uncertainty is used as the query criterion in the active learning process, where the most uncertain samples are selected for annotation and included for model retraining. The proposed workflow was tested with three data pairs in which each workflow represents a scenario often encountered in real-world applications, including adapting pretrained models to new images collected with different sensors or to new geographic areas where appearances and types of buildings are very different. Compared to several baselines, including random sampling, temperature scaling (a well-known uncertainty calibration technique), different query strategies, and active domain adaptation methods, the proposed workflow shows that strategically querying a smaller set of samples for labeling achieves comparable or better building extraction performance. The proposed method reduces the number of labeled samples required to achieve sufficient model accuracy, thus significantly reducing hundreds of person-hours for labeled data creation. In addition, we include a few considerations when deploying this workflow in a GPU cluster that can be easily adapted to achieve operational building extraction model retraining.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The Dominant Influencer of Voltage Fluctuation (DIVF) for Power Distribution System

Variability in power generation at multiple consumer owned renewable energy sources can cause random voltage fluctuations, which may result in voltage violations at multiple nodes in a power distribution system. Traditional methods of voltage control are ineffective to address fast voltage variations. New dynamic methods of voltage control using end user devices can significantly benefit from the knowledge of the dominant influencer of voltage fluctuation (DIVF). This paper introduces information theoretic metrics to identify DIVF for every node in the power distribution system. A node can be DIVF due to its location in the distribution system and its capacity to generate and change its power. Use of traditional power flow algorithms to identify the DIVF is computationally complex which limits their use in real-time applications. In this work, information theoretic indicators of the DIVF are computed analytically in a computationally efficient manner, and their effectiveness to identify the DIVF is tested using the IEEE 69 node test system. From simulations, it is illustrated that differential entropy, Kullback-Leibler distance and Frechet distance are effective indicators of the DIVF and can successfully identify the most influential nodes providing the foundation for intelligent voltage control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

SU-E-J-245: Is Off-Line Adaptive Radiotherapy Sufficient for Head and Neck Cancer with IGRT?

Purpose: Radiation doses delivered to patients with head and neck cancer (HN) may deviate from the planned doses because of variations in patient setup and anatomy. This study was to evaluate whether off-line Adaptive Radiotherapy (ART) is sufficient. Methods: Ten HN patients, who received IMRT under daily imaging guidance using CT-on-rail/KV-CBCT, were randomly selected for this study. For each patient, the daily treatment setup was corrected with translational only directions. Sixty weekly verification CTs were retrospectively analyzed. On these weekly verification CTs, the tumor volumes and OAR contours were manually delineated by a physician. With the treatment iso-center placed on the verification CTs, according to the recorded clinical shifts, the treatment beams from the original IMRT plans were then applied to these CTs to calculate the delivered doses. The electron density of the planning CTs and weekly CTs were overridden to 1 g/cm3. Results: Among 60 fractions, D99 of the CTVs in 4 fractions decreased more than 5% of the planned doses. The maximum dose of the spinal cord exceeded 10% of the planned values in 2 fractions. A close examination indicated that the dose discrepancy in these 6 fractions was due to patient rotations, especially shoulder rotations. After registering these 6 CTs with the planning CT allowing six degree of freedoms, the maximum rotations around 3 axes were > 1.5° for these fractions. With rotation setup errors removed, 4 out of 10 patients still required off-line ART to accommodate anatomical changes. Conclusion: A significant shoulder rotations were observed in 10% fractions, requiring patient re-setup. Off-line ART alone is not sufficient to correct for random variations of patient position, although ART is effective to adapt to patients' gradual anatomic changes. Re-setup or on-line ART may be considered for patients with large deviations detected early by daily IGRT images. The study is supported in part by Siemens Medical Solutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-351: Establishing a Workflow for IMRT Pre-Treatment Reviews for NRG-GY006 Clinical Trial

Purpose: To establish a workflow for NRG-GY006 IMRT pre-treatment reviews, incorporating advanced radiotherapy technologies being evaluated as part of the clinical trial. Methods: Pre-Treatment reviews are required for every IMRT case as part of NRG-GY006 (a randomized phase II trial of radiation therapy and cisplatin alone or in combination with intravenous triapine in women with newly diagnosed bulky stage I B2, stage II, IIIB, or IVA cancer of the uterine cervix or stage II-IVA vaginal cancer. The pretreatment review process includes structures review and generating an active bone marrow(ABM)- to be used as an avoidance structure during IMRT optimization- and evaluating initial IMRT plan quality using knowledgeengineering based planning (KBP). Institutions will initially submit their simulation CT scan, structures file and PET/CT to IROC QA center for generating ABM. The ABM will be returned to the institution for use in planning. Institutions will then submit an initial IMRT plan for review and will receive information back following implementation of a KBP algorithm, for use in re-optimization, before submitting the final IMRT used for treatment. Results: ABM structure is generated using MIM vista software (Version 6.5, MIM corporation, Inc.). Here, the planning CT and the diagnostic PET/CT are fused and a sub threshold structure is auto segmented above the mean value of the SUV of the bone marrow. The generated ABM were compared with those generated with other software system (e.g. Velocity, Varian) and Dice coefficient (reflects the overlap of structures) ranged between 80 – 90% was achieved. A KBP model was built in Varian Eclipse TPS using the RapidPlan KBP software to perform plan quality assurance. Conclusion: The workflow for IMRT pretreatment reviews has been established. It represents a major improvement of NRG Oncology clinical trial quality assurance and incorporates the latest radiotherapy technologies as part of NCI clinical trials. This project was supported by grants U24CA180803 (IROC), UG1CA189867 (NCORP), U10CA180868 (NRG Oncology Operations), U10CA180822 (NRG Oncology SDMC) from the National Cancer Institute (NCI) and PA CURE grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The phonon-coupling model for Skyrme forces

A short review on the self-consistent RPA based on the energy-density functional of the Skyrme type is given. We also present an extension of the RPA where the coupling of phonons to the single-particle states is considered. Within this approach we present numerical results which are compared with data. The self-consistent approach is compared with the Landau–Migdal theory. Here we derive from the self-consistent ph interaction, the Landau–Migdal parameters as well as their density dependence. In the Appendix a new derivation of the reduced matrix elements of the ph interaction is presented.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

OR14-V-Uncertainty-PD2La Uncertainty Quantification for Nuclear Safeguards and Nondestructive Assay Final Report

The various methods of nondestructive assay (NDA) of special nuclear material (SNM) have applications in nuclear nonproliferation, including detection and identification of illicit SNM at border crossings and quantifying SNM at nuclear facilities for safeguards. No assay method is complete without “error bars,” which provide one way of expressing confidence in the assay result. Consequently, NDA specialists typically provide error bars and also partition total uncertainty into “random” and “systematic” components so that, for example, an error bar can be developed for the total mass estimate in multiple items. Uncertainty Quantification (UQ) for NDA has always been important, but it is recognized that greater rigor is needed and achievable using modern statistical methods.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Thermodynamic, Kinetic, and Physical Properties of Nb-U (Niobium-Uranium)

Based on an improved coupling between ab initio energetics output, phenomenological thermodynamics based on the CALPHAD (CALculation of Phase Diagrams) approach, and the use of the Thermo-Calc software, together with experimental data (whenever available), a thermodynamic assessment of the Nb-U alloy system was carried out. We made use of the full array of modern electronic-structure techniques based on density functional theory, including ab initio fully relativistic full-potential linear-muffin orbital method (FR-FP-LMTO), methods, the Scalar Relativistic Korringa-Kohn-Rostoker Atomic-Sphere Approximation (SR-KKR-ASA), and the fully relativistic or scalar relativistic Exact muffin-orbital (SR- or FR-EMTO) method, both based on the Green function formalism that has the advantage of being able to treat chemically random configuration (i.e., solid solution) with the so-called coherent potential approximation (CPA). All electronic structure calculations were performed within the Generalized Gradient Approximation (GGA) for the treatment of electron correlations. The results from this technology serve as input for CALPHAD assessment of phase diagrams

36 MATERIALS SCIENCE↗