Search NASA⌕ Search

SEARCH · Search NASA

Results for “Direct Drive”

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 109 records · Page 6

Reversible to irreversible transitions for ac driven skyrmions on periodic substrates

Abstract Using atomistic simulations, we investigate the dynamical behavior of magnetic skyrmions in dimer and trimer molecular crystal arrangements, as well as bipartite lattices at 3/2 and 5/2 fillings, under ac driving over a square array of anisotropy defects. For low ac amplitudes, at all fillings reversible motion appears in which the skyrmions return to their original positions at the end of each ac drive cycle and the diffusion is zero. We also identify two distinct irreversible regimes. The first is a translating regime in which the skyrmions form channels of flow in opposing directions and translate by one substrate lattice constant per ac drive cycle. The translating state appears in the dimer and trimer arrangements, and produces pronounced peaks in the diffusivity in the direction perpendicular to the external drive. For larger ac amplitudes, we find chaotic irreversible motion in which the skyrmions can randomly exchange places with each other over time, producing long-time diffusive behavior both parallel and perpendicular to the ac driving direction.

36 MATERIALS SCIENCE↗

Directional locking and hysteresis in stripe- and bubble-forming systems on one-dimensional periodic substrates with a rotating drive

We examine the dynamics of a two-dimensional stripe, bubble, and crystal forming system interacting with a periodic one-dimensional substrate under an applied drive that is rotated with respect to the substrate periodicity direction 𝑥. We find that the stripes remain strongly directionally locked to the 𝑥 direction for an extended range of drives before undergoing motion parallel to the drive. In some cases, the stripes break apart at the unlocking transition, but they can dynamically reform into stripes aligned perpendicular to the 𝑥 direction, producing hysteresis in the directional locking and unlocking transitions. In contrast, moving anisotropic crystal and bubble phases exhibit weaker directional locking and reduced or no hysteresis. The hysteresis occurs in regimes where the particle rearrangements occur and is most pronounced near the stripe phase. In conclusion, we also show that for varied substrate strength, substrate spacing, and particle density, a number of novel dynamical patterns can form that include a combination of stripe, bubble, and crystal morphologies.

36 MATERIALS SCIENCE↗

TiO 2 Nanoparticles Enabling Photocatalytic Desulfurization for C–C Coupling Reaction Using Visible Light

We uncover a surface-mediated mechanism for visible-light-driven photocatalytic desulfurization of thiols on titanium dioxide (TiO 2 ) nanoparticles under LED illumination (>420 nm). Combined diffuse reflectance, infrared, and cryogenic electron paramagnetic resonance spectroscopy verify the formation of a surface thiol–Ti charge-transfer complex that introduces visible-light absorption into an otherwise UV-active reaction system. Selective photoexcitation of this surface complex drives interfacial charge transfer, directly activating the adsorbed thiol and inducing C–S bond scission without the band gap excitation of TiO 2 . The resulting carbon-centered radical intermediates are intercepted by styrene to form C–C coupling products. These results uncover a distinct surface-mediated photocatalytic mechanism in which charge-transfer complex formation governs both light absorption and chemical activation, providing a mechanistic framework for extending visible-light reactivity to wide-bandgap metal oxide photocatalysts.

addition of carbon radical to vinyl groups↗

Morphogenesis of spin cycloids in a noncollinear antiferromagnet

Pattern formation in spin systems with continuous-rotational symmetry (CRS) provides a powerful platform to study emergent complex magnetic phases and topological defects in condensed-matter physics. However, its understanding and correlation with unconventional magnetic order along with high-resolution nanoscale imaging are challenging. Here, we employ scanning nitrogen vacancy (NV) magnetometry to unveil the morphogenesis of spin cycloids at both the local and global scales within a single ferroelectric domain of (111)-oriented BiFeO 3 , which is a noncollinear antiferromagnet, resulting in formation of a glassy labyrinthine pattern. We find that the domains of locally oriented cycloids are interconnected by an array of topological defects and exhibit isotropic energy landscape predicted by first-principles calculations. We propose that the CRS of spin-cycloid propagation directions within the (111) drives the formation of the labyrinthine pattern and the associated topological defects such as antiferromagnetic skyrmions. Unexpectedly, reversing the as-grown ferroelectric polarization from [$\overline{1}$ $\overline{1}$ $\overline{1}$] to [111] produces a noncycloidal NV image contrast which ¯ could be attributed to either the emergence of a uniformly magnetized state or a reversal of the cycloid polarity. These findings highlight that (111)-oriented BiFeO 3 is not only important for studying the fascinating subject of pattern formation but could also be utilized as an ideal platform for integrating novel topological defects in the field of antiferromagnetic spintronics.

magnetoelectric↗

Adaptive Cybersecurity for Distributed Energy Resources (AdCyDER): Online Reinforcement Learning with Stackelberg-Optimized Defenses — Pipeline Architecture, Evaluation Methodology, and Findings from a Synthetic-Data Evaluation

This report documents the design and evaluation of an integrated online-learning pipeline developed within the AdCyDER project for Distributed Energy Resource (DER) cybersecurity. The pipeline couples a Reinforcement Learning (RL) attack classifier — which produces an attack-type probability distribution — with a Stackelberg game-theoretic (GT) defense selector that consumes those distributions alongside SME-encoded priors over (defense, attack) effectiveness pairings and perdefense costs to choose grid-health-preserving defenses. The objective is not attack classification per se but production of distributions that drive effective defense selection through the Stackelberg layer, learned from delayed grid-health feedback rather than labeled attack data. AdCyDER as a whole is broader than the work presented here; this report covers the specific RL/GT loop integration and its evaluation. We present the integrated pipeline (SCADA telemetry with Fronius inverter physics, Suricata IDS, time-windowed aggregation, per-facility LSTM classifier, Stackelberg optimizer, OpenC2 actuators), an experimental campaign of 28 eight-hour iterations across three baseline modes, and a pipeline-ordered diagnostic protocol. The protocol identifies two distinct failure modes within the loop: paired supervised ceilings on the same features establish that the deployed online RL classifier (macro F1 ≈ 0.07) sits at least 4.7× below a same-architecture supervised LSTM (≈ 0.34) and 10–11× below a linear feature-signal ceiling (≈ 0.70–0.79 depending on per-facility isolation), localizing the dominant failure to the training procedure; and the reward signal driving online updates carries weak directional coupling with classifier correctness in the methodology-expected direction (multi-lens convergent: top-decile P(true) records produce more frequent state changes and slightly larger improvements, top-vs-bot Cohen’s 𝑑 ≈ −0.19), but at effect magnitudes too small to drive gradient-based learning at the campaign sample size. The original learning hypothesis is not supported by the data. The primary contributions are the diagnostic methodology — proposed as a transferable falsification protocol for online RL/GT defense pipelines learning from delayed environmental reward — and the open, reproducible experimental infrastructure. We outline reward reformulation as the highest-priority aspirational next step given the underpowered-but-aligned Q6 reading, with hardware-in-the-loop evaluation as the broadest scope-expansion option.

Blakely, Benjamin [Argonne National Laboratory (AN↗

p-Type BiVO 4 for Solar O 2 Reduction to H 2 O 2

Photoelectrochemical cells (PECs) can directly utilize solar energy to drive chemical reactions to produce fuels and chemicals. Oxide-based photoelectrodes in general exhibit enhanced stability against photocorrosion, which is a critical advantage for building a sustainable PEC. However, most oxide-based semiconductors are n-type, and p-type oxides that can be used as photocathodes are limited. In this study, we report the synthesis, characterization, and application of p-type BiVO 4 with a monoclinic scheelite (ms) structure. ms-BiVO 4 is inherently n-type, and it has been investigated only as a photoanode to date. In this study, we prepared p-type ms-BiVO 4 (bandgap of 2.4 eV) via atomic doping of Ca 2+ at the Bi 3+ site under an O 2 -rich environment and examined its performance as a photocathode. We then demonstrated that the Ca-doped ms-BiVO 4 photocathode can be used for solar O 2 reduction to H 2 O 2 when coupled with appropriate catalysts. Our computational investigation using hybrid density functional theory revealed that holes are stable as polarons in ms-BiVO 4 and have a low self-trapping energy, that may lead to free carriers in the valence band at finite temperature. Our calculations also show that Ca is an effective shallow acceptor dopant with low formation energy and thermal ionization energy leading to p-type conductivity. In conclusion, our joint experimental and computational results provide critical insights into the design of p-type ms-BiVO 4 , enabling its use as a polaronic oxide photocathode.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scalings of laser-driven MeV electron sources with relativistic multi-picosecond laser pulses

We investigate the generation of MeV electrons in relativistic multi-picosecond laser–solid interactions, using two-dimensional particle-in-cell simulations. Scanning a parameter space of intensities from 10 18 to 10 20 W/cm 2 and pulse durations between 100 fs and 10 ps, we discuss scalings of the effective hot electron temperature and MeV electron dose relevant to applications, as well as the direct laser acceleration mechanism that drives electrons to energies much higher than the ponderomotive potential of the laser pulse.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding and controlling the fundamental photochemistry of protonic solar energy conversion (Final Scientific/Technical Report)

The selectivity and activity of most fuel-forming reactions are tunable by the concentration of electrons, holes, protons, and/or hydroxides. That is one reason why traditional solar energy conversion processes are used to drive these reactions, where light directly increases the concentration of electrons and holes. We, instead, took a different approach, using light to increase the concentration of protons and/or hydroxides. For this, we leveraged photophysical and solid-state physics theories, techniques, and design strategies previously developed for the study of traditional solar energy conversion processes. We designed and fabricated several materials platforms based on molecular photoacid and photobase dyes coupled with ion-exchange polymer membranes and assessed their fundamental photoelectrochemistry. We demonstrated control over built-in electric potentials, photovoltages, proton-transfer kinetics, and efficiency limits to our approach. Understanding the basic science of these dye-sensitized protonic membranes and their photochemical mechanisms is of use to the DOE-relevant processes of solar photochemical fuel formation, solar photodialytic desalination, and solar cells. Moreover, functional materials that we developed from this project may be of use to several broad-reaching fields and may provide the foundation for a completely new, inexpensive, and robust solar energy conversion technology.

14 SOLAR ENERGY↗

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗

Validation of the NLR Pumped Storage Hydropower Cost Model

The National Laboratory of the Rockies (NLR) first released its pumped storage hydropower (PSH) cost model in 2023 as the most detailed bottom-up PSH cost model available to the public. It is available both as a spreadsheet and an interactive web tool, enabling users with a variety of PSH interests to transparently characterize costs of alternative PSH sites and designs. The PSH cost model cannot replace detailed site-level studies and design, but it is important to validate it against other industry PSH cost estimates. The initial model methodology report validated the cost model for a single proposed site, the Eagle Mountain Project in California. This slide deck documents an expanded validation exercise using cost data from six other sites: Goldendale (Washington), Seminoe (Wyoming), Gordon Butte (Montana), Swan Lake (Oregon), White Pine (Oregon), and Lewis Ridge (Kentucky). It compares itemized costs from Federal Energy Regulatory Commission (FERC) applications and other reported costs with NLR PSH cost model outputs after customizing inputs for each site. The validation exercise finds that the NLR model's conservative indirect cost assumptions often drive overall cost overestimation, with direct cost comparisons typically agreeing more closely. All cost model estimates are well within an Association for the Advancement of Cost Engineering (AACE) Class 5 estimation range (-50% to +100%), with five within the AACE Class 4 range (-30% to +50%) and four being within 15%. This result is considered reasonable performance for a parametric model applied at a preliminary design stage.

13 HYDRO ENERGY↗

Integrated simulations of premagnetized and self-magnetizing dynamic screw pinch-driven MagLIF

Magnetically driven implosions such as in magnetized liner inertial fusion (MagLIF) on the Z accelerator suffer from magneto-Rayleigh–Taylor instabilities (MRTI) that dynamically redistribute liner mass during implosion, limiting fusion fuel compression and confinement, which ultimately degrades performance. Driving the implosion with an initially helical drive field that dynamically shifts the direction of the magnetic field surrounding the liner (i.e., a dynamic screw pinch, DSP) is a method proposed to mitigate MRTI in-flight and improve target performance. In DSPs, the axial drive magnetic field component implodes the liner and diffuses through the shocked, melted liner material into the fuel throughout the implosion. Liners can be designed to enable enough axial magnetic flux to diffuse through the liner material to effectively magnetize the fuel region without the need of an initial axial magnetic field (i.e., from external field coils). We present results from three-dimensional radiation-magnetohydrodynamic simulations of MagLIF implosions employing drive magnetic fields composed of axial and azimuthal components (a helical drive field). These simulated DSP-driven MagLIF targets demonstrate improved fuel conditions and thermonuclear yield compared to a traditional MagLIF target implosion. Synthetic x-ray radiography of the imploding liner material and x-ray emission images of the fuel region at the time of peak neutron yield rate indicate superior implosion morphology for DSP-MagLIF implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Magnus force induced magnetic diode effect in skyrmion systems

We show that skyrmions can exhibit a “magnetic diode effect,” where there is a nonreciprocal response in the transport when the magnetic field is reversed. This effect can be achieved for skyrmions moving in channels with a sawtooth potential on one side and a reversed sawtooth potential on the other side. We consider the cases of both spin-transfer torque (STT) and spin–orbit torque (SOT). When the magnetic field is held fixed, the velocity response of the skyrmion is the same for current applied in either direction for both torques, so there is no current diode effect. When the magnetic field is reversed, under STT driving the velocity of the skyrmion reverses and its absolute value changes. Under SOT driving, the velocity remains in the same direction but drops to a much lower value, resulting in negative differential conductivity. For a fixed current, we find a nonreciprocal skyrmion velocity as a function of the applied field’s sign, in analogy to the velocity–current curves observed in the usual diode effect. The nonreciprocity is generated by the Magnus force, which causes skyrmions to interact preferentially with one side of the channel. Since the channel sides have opposite asymmetry, a positive magnetic field can cause the skyrmion to interact with the “hard” asymmetry side of the channel, while a negative magnetic field causes the skyrmion to interact with the “easy” asymmetry side. This geometry could be used to create new kinds of magnetic-field-induced diode effects that can be harnessed in new types of skyrmion-based devices.

36 MATERIALS SCIENCE↗

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fast physics-based launcher optimization for electron cyclotron current drive

With the increased urgency to design fusion pilot plants, fast optimization of electron cyclotron current drive (ECCD) launchers is paramount. Traditionally, this is done by coarsely sampling the 4D parameter space of possible launch conditions consisting of (1) the launch location (constrained to lie along the reactor vessel), (2) the launch frequency, (3) the toroidal launch angle, and (4) the poloidal launch angle. For each initial condition, a ray-tracing simulation is performed to evaluate the ECCD efficiency. Unfortunately, this approach often requires a large number of simulations (sometimes millions in extreme cases) to build up a dataset that adequately covers the plasma volume, which must then be repeated every time the design point changes. Here we adopt a different approach. Rather than launching rays from the plasma periphery and hoping for the best, we instead directly reconstruct the optimal ray for driving current at a given flux surface using a reduced physics model coupled with a commercial ray-tracing code. Repeating this throughout the plasma volume requires only hundreds of simulations, constituting a significant speedup. The new method is validated on two separate example tokamak profiles, and is shown to reliably drive localized current at the specified flux surface with the same optimal efficiency as obtained from the traditional approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Heliostats with Adjustable Shape for High Concentration throughout the Day

Our motivation is to develop more efficient heliostats that can provide commercially viable solar thermal power at temperatures > 800°C. Such high temperatures will enable high-temperature industrial processes, as well as electrical generation after sunset with high efficiency. The importance of this research is that such heliostats have the potential to substantially expand the global use of solar energy, by adding solar thermal power as a major component. Thermal solar currently accounts for only 1% of all solar power (with PV being the rest), with heliostat fields providing just 0.25%. Our goals have been 1) to demonstrate a technical improvement for heliostats that can enable fields of them to more efficiently power receivers and reactors, and 2) to show a path to low-cost mass production. Our solution uses new opto-mechanical technology to correct a fundamental deficiency of present heliostats that limits their concentration, namely that they have fixed shape. Most of today’s heliostat research does not address this, but is directed simply toward cost reduction in an effort to make heliostats commercially viable. We are motivated to explore also improving heliostat efficiency, which can be done by continually changing their shape to maximize the concentration of sunlight throughout the day. This is not a new concept, but it has never been implemented in a practical, cost-effective way that approaches the theoretical limit to concentration while also improving mechanical performance; this is our goal. Our major accomplishments have been: 1) We have realized the planned design, construction, and test of a prototype heliostat that achieves the required shape changes in an 8 m2 single-piece glass mirror. The mirror is attached to a steel support frame that is automatically mechanically twisted by the heliostat drives that orient the mirror to direct sunlight to the tower-mounted receiver. Closed-loop tracking is done using a new beamsplitter camera that exploits the target-oriented mount configuration. Field tests of the heliostat show that the light is reflected through the day to always form a disc image of the sun, as needed to obtain the highest concentration. 2) We have developed the design for a field of 431 heliostats to deliver annual average of 1 MW of thermal power at 3,000 sun concentration, matched to a high-temperature ≥ 1000°C chemical reactor. 3) We have also developed, beyond the original stated goals of the project, a new concept for closed-loop tracking and shape-sensing for all the heliostats in the above field, using just 6 cameras around the concentrated reactor focus. Our research adds to the understanding of solar thermal energy by its demonstration of the technical effectiveness of a higher performing heliostat, and by its concept for a new powerful method for real-time tracking and shape sensing in the field, as described above. We have studied the economic feasibility of fields of our twisting heliostats to provide high- temperature heat at a price competitive with that of burning gas, to satisfy the DOE’s studied zero-emissions scenario, where the gas price has to include the cost of carbon capture. The project has the potential to greatly benefit the public if it helps limit global warming by 1) reducing carbon emission from industrial heating, which is currently a major contributor to the 40-billion-ton annual increase in atmospheric CO 2 . 2) Ultimately, the technology could prove to be the least expensive method to power direct air capture of CO 2 on the very large scale needed to remove the 1 trillion-ton excess of CO 2 already in the atmosphere.

14 SOLAR ENERGY↗

Low Cost High-Performance HRE-Free 3-in-1 Electric Drive Unit

The project team completed work to expand upon American Axle & Manufacturing’s (AAM) baseline technology and develop a high-speed, AC induction electric drive unit (EDU) with total direct-oil-cooling and integrated power electronics. The project accelerated advancements in EDU technology by allowing AAM to build upon the progress made in developing the underlying baseline technologies. The following seven improvements to AAM’s baseline technology were implemented in this research and development program: 1) Increased speed (30k RPM) AC induction motor, 2) Silver-sintering of discrete silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFET) to heat sinks, 3) Electrically insulated rotor bars, 4) Optimized lamination steel, 5) EDU-integrated 650VDC inverter package, 6) Over-molded stator with molded liners, and 7) 650VDC power-dense stator design. The successful development of the technology resulted in a meaningful cost reduction for EDU systems in the market. Coupled with falling battery system costs, lower EDU costs will likely accelerate the market acceptance and related production scaling of battery electric vehicles. The objective of this project was to research, develop, and test a Heavy Rare Earth (HRE)-free 3-In-1 electric drive unit (EDU) that has class leading power density and cost. The key technologies to be developed were anticipated to meet or exceed the Department of Energy (DOE) targets of a cost ≤ $\$$7/kilowatt (kW), power density ≥ 12 kW/liter, and operating voltage ≥ 600 VDC.

33 ADVANCED PROPULSION SYSTEMS↗

Self‐Propelling Macroscale Sheets Powered by Enzyme Pumps

Nanoscale enzymes anchored to surfaces act as chemical pumps by converting chemical energy released from enzymatic reactions into spontaneous fluid flow that propels entrained nano‐ and microparticles. Enzymatic pumps are biocompatible, highly selective, and display unique substrate specificity. Utilizing these pumps to trigger self‐propelled motion on the macroscale has, however, constituted a significant challenge and thus prevented their adaptation in macroscopic fluidic devices and soft robotics. Using experiments and simulations, we herein show that enzymatic pumps can drive centimeter‐scale polymer sheets along directed linear paths and rotational trajectories. In these studies, the sheets are confined to the air/water interface. With the addition of appropriate substrate, the asymmetric enzymatic coating on the sheets induces chemically driven, buoyancy flows that controllably propel the sheet's motion on the air/water interface. The directionality and speed of the motion can be tailored by changing the pattern of the enzymatic coating, type of enzyme, and nature and concentration of the substrate. This work highlights the utility of biocompatible enzymes for generating motion in macroscale fluidic devices and robotics and indicates their potential utility for in vivo applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analytically differentiable metrics for phase stability

Here, in this work, a long-established but sparsely documented method of obtaining semi-analytic derivatives of thermodynamic properties with respect to equilibrium conditions is briefly reviewed and rigorously derived. This procedure is then leveraged to construct general forms of derivatives of the residual driving force, a metric for measuring phase stability used in CALPHAD model optimization, with respect to overall system and individual phase compositions. Applied examples – calculating heat capacity in the Al-Fe system, thermodynamic factors in the Nb-V-W system, and residual driving force derivatives in the Ni-Ti system – demonstrate the versatility, accuracy, and extensibility of this method. Using the developed method, residual driving force gradients can be applied directly in CALPHAD model optimizers, as well as in materials design frameworks, to identify regions of phase stability with an efficient, gradient-based approach.

36 MATERIALS SCIENCE↗