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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Voltage and temperature effects on low cobalt lithium-ion battery cathode degradation

Degradation of low cobalt lithium-ion cathodes was tested using a full factorial combination of upper cut-off voltage (4.0 V and 4.3 V vs. Li/Li + ) and operating temperature (25 °C and 60 °C). Half-cell batteries were analyzed with electrochemical and microstructural characterization methods. Electrochemical performance was assessed with galvanostatic cycling, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) supported by distribution of relaxation times (DRT) analysis. Electrode microstructure was characterized with scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray absorption near edge structure (XANES) imaging. Higher cut-off voltage cycling shows presence of NiO x formation, a low diffusivity rock-salt phase, in both CV and XRD data. XRD patterns confirmed that the rock-salt phase was beginning to form at the low cut-off voltage at high temperature, but in much lower intensity than at the high cut-off voltage. Higher temperature accelerates degradation processes at both voltages. Degradation factors at high temperature include NiO x formation, cathode material dissolution, and electrolyte decomposition. SEM analysis suggests that supporting phases may isolate and disconnect active material particles reducing capacity retention and battery life cycle. DRT analysis and XANES imaging show that both high temperature samples revealed a NiO x phase based on an increased diffusive impedance and a visible shift in the XANES spectra. The low cut-off voltage, high temperature sample showed a split peak and shift to lower energies indicating early formation of the NiO x phase. The diffusive impedance, which hinders intercalation and deintercalation, is driven by the formation of the NiO x phase. While primarily driven by cut-off voltage, elevated temperature also contributes to this degradation mechanism.

electrochemical impedance spectroscopy↗
DOE OSTI2026

Recent efforts of vapour-phase strategies for EUV resist toward high- and hyper-NA extreme ultraviolet lithography

Extreme ultraviolet lithography (EUVL, λ = 13.5 nm) is critical for sub-1 nm technology nodes but remains constrained by inherent trade-offs among resolution, line-edge roughness (LER), and sensitivity. Stochastic effects originating from photon shot noise, low-energy secondary electron blur, and the random distribution of resist components further limit its advancement toward high numerical-aperture (NA, NA = 0.55) and hyper-NA (NA ≥0.75) EUVL. While the optimization of spin-on chemically amplified resists (CARs) continues, metal-oxide resists (MORs) have emerged as strong candidates for next-generation EUVL by incorporating metals with high EUV absorption coefficients, which enhances both resist sensitivity and etch resistance during pattern transfer. Besides spin-coating, recent advances in vapour-phase techniques, such as vapour-phase infiltration (VPI), chemical vapour deposition (CVD), and molecular atomic layer deposition (MALD), offer promising pathways to achieve new resist platforms, such as dry resists, that satisfy the stringent thickness and uniformity requirements of next-generation EUVL. These methods enable the direct incorporation of metal species into existing resist matrices or the formation of hybrid inorganic–organic resist platforms, thereby improving film uniformity, etch durability, and pattern fidelity while mitigating stochastic defects. This review highlights the latest advancements in vapour-phase-synthesized EUV resists, emphasizing material design, lithographic performance, and the underlying exposure mechanisms. Although still emerging, vapour-phase strategies are paving the way for an all-dry integration framework that could improve EUV patterning workflows and meet the demands of future technology nodes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Reversible Electron-Beam Patterning of Colloidal Nanoparticles at Fluid Interfaces

The directed self-assembly of colloidal nanoparticles (NPs) using external fields guides the formation of sophisticated hierarchical materials but becomes less effective with decreasing particle size. As an alternative, electron-beam-driven assembly offers a potential avenue for targeted nanoscale manipulation, yet remains poorly controlled due to the variety and complexity of beam interaction mechanisms. Here, we investigate the beam–particle interaction of silica NPs pinned to the fluid–vacuum interface of ionic liquid droplets. In these experiments, scanning electron microscopy of the droplet surface resolves NP trajectories over space and time while simultaneously driving their reorganization. With this platform, we demonstrate the ability to direct particle transport and create transient, reversible colloidal patterns on the droplet surface. By tuning the beam voltage, we achieve precise control over both the strength and sign of the beam–particle interaction, with low voltages repelling particles and high voltages attracting them. This response stems from the formation of well-defined solvent flow fields generated from trace radiolysis of the ionic liquid, as determined through statistical analysis of single-particle trajectories under varying solvent composition. Altogether, electron-beam-guided assembly introduces a versatile strategy for nanoscale colloidal manipulation, offering new possibilities for the design of dynamic, reconfigurable systems with applications in adaptive photonics and catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Lignin structural changes and high p -coumaroylation in incipient lignification in moso bamboo

Lignification is a crucial process for strengthening plant tissues, facilitating water transport, and providing defense against pathogens. In the Poaceae family, p-hydroxycinnamic acids are commonly incorporated into lignin, with acylation by p-coumarate (pCA) occurring during lignification. In this study, we performed DFRC and 2D HSQC-NMR analyses to investigate changes in lignin substructures and the degree of lignin pCA-acylation throughout bamboo stem development. Furthermore, immunohistochemical analysis was conducted to elucidate the spatial distribution of lignin substructures within different cell types. Our results revealed that, in young tissues, β–O–4-linked lignin units are predominantly derived from monolignol-pCA conjugates, specifically coniferyl- and sinapyl-pCA. Both lignin structure and the pattern of pCA acylation varied depending on the stage of cell wall formation and the cell type, particularly between vascular fiber cells and parenchyma cells. Based on our results, moso bamboo culms exhibit a distinctive feature during incipient lignification, in which monolignols are predominantly acylated with pCA. As a result, this feature has not been reported in other grasses, suggesting that extensive p-coumaroylation of monolignols plays an important role in the rapid elongation of bamboo culms.

Munekata, Noriaki [Kyoto University (Japan); Unive↗
DOE OSTI2025

Strain release through hydrogen bond–mediated layer twisting

Strain engineering, enabling the precise control over structure and functional properties, is a key strategy for the design of advanced materials. However, the mechanisms governing strain evolution and release at the nanoscale remain largely unexplored. In this study, we leverage in situ heating transmission electron microscopy and synchrotron x-ray spectroscopy to investigate the strain relaxation pathways of boehmite (γ-AlOOH) at 575 kelvin by revealing real-time structural dynamics. Through tracking the moiré pattern evolution, we identify distinct strain release mechanisms, including layer twisting, defect formation, and domain restructuring. Our neural network potential calculations reveal that energy fluctuations at small twist angles are dominated by an interference-like interaction modulation of hydrogen bonds between boehmite interlayers, with metastable twisted structures corresponding to local minima of the potential energy landscape. This work establishes a previously unidentified paradigm of two-dimensional layer twisting mediated by hydrogen bonding, offering insights into strain-driven transformation mechanisms, and thus may have broad implications for strain in material and earth sciences.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Field-Driven Out-of-Equilibrium Collective Patterns for Swarm Micro-Robotics

Soft robotics has been rapidly advancing, offering significant improvements over traditional rigid robotic systems through the use of compliant materials that enhance adaptability and interaction with the environment. However, current approaches face critical challenges, including the reliance on complex “top-down” fabrication techniques and the difficulty of wireless powering and control at the microscale. Swarm robotics introduces a paradigm shift, leveraging collective dynamics to achieve cooperative and adaptable behaviors among multiple robotic units. Inspired by nature, this “bottom-up” approach enables swarm robots to execute task-specific reconfigurations, enhancing flexibility and robustness. Field-driven active colloids emerge as a promising platform for swarm microrobotics, capable of self-propulsion and self-organization into dynamic collective patterns under external field excitation and manipulation. These systems mimic biologically inspired swarm behaviors, such as flocking and vortex formation, providing a versatile foundation for designing innovative swarm microrobots. Here, this review discusses the principles of electric and magnetic field-driven collective self-organization, focusing on the particle dynamics, the emergence of collective swarm patterns, and illustrative examples of functional swarm microrobots. It concludes with future perspectives on harnessing these systems for adaptive, scalable, and multifunctional microrobotic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Low-stress creep behavior of multiple salt caverns under cyclic operations

Here, the use of multiple salt caverns for large-scale underground hydrogen storage offers a strategic solution to the growing demand for efficient and flexible energy storage, due to the inherent low permeability, high mechanical strength, and self-healing properties of the salt formation. Despite these advantages, the long-term geomechanical response of salt caverns under cyclic injection and withdrawal remains a significant challenge for ensuring operational stability. This mechanistic study highlights the critical role of low-stress creep, also known as pressure solution creep, in governing deformation of salt caverns during cyclic operations. Unlike conventional creep mechanisms that dominate under high-stress conditions, low-stress creep becomes particularly relevant under the moderate stress changes induced by repeated injection and withdrawal, which provides a previously underexplored control on cavern closure. Our three-dimensional computational model integrates the low-stress creep mechanism into the Munson–Dawson creep equation across a spectrum of operational scenarios including variations in cavern pressure cycles, injection-withdrawal frequencies, and caprock mechanical property. The low-stress creep components accelerate the cavern creep closure, which is amplified with shorter cycle frequency and larger pressure difference. Sensitivity analyses capture the complex interactions between multiple caverns and surround formations at the field scale that allows for a quantitative assessment of deformation patterns and closure rates over time and thereby informs the design and operation of sustainable underground hydrogen storage system.

Cyclic operation↗
DOE OSTI2025

Flux-Closure Domain Structures in Ferroelectric K 0.5 Na 0.5 NbO 3 Thin Films

Topological domain structures in ferroelectric materials have garnered increasing attention due to their intriguing physical properties and promising applications. While most existing topological structures in ferroelectric perovskite oxides originate from tetragonal or rhombohedral bulk phases, much less is understood about their counterparts in orthorhombic ferroelectrics. Here, in this work, we employ ferroelectric K 0.5 Na 0.5 NbO 3 (KNN) thin films as a model system and leverage phase-field simulations to theoretically predict the static structures and dynamic behaviors of three types of flux-closure domain configurations: in-plane (Type-I), out-of-plane (Type-II), and superdomain (Type-III) flux-closure structures. We systematically investigate the effects of finite size, misfit strains, and electrical boundary conditions on the formation and switching of these topological structures. For the Type-I structure, size reduction or small misfit strain facilitates a transition of the flux-closure pattern to polar vortices. Type-II structures emerge under open-circuit electrical boundary conditions of the film, forming at the junctions of specific domain walls with the film surface or the film–substrate interface. The formation mechanisms of these two flux-closure structures are rationalized from an energy perspective. We demonstrated switching capabilities of Type-II and Type-III structures by obtaining polarization–electric field hysteresis loops. Our simulations also reveal a reversible electric-field-induced transition between the orthorhombic and rhombohedral ferroelectric phases with a checkerboard domain pattern, during which the integrity of the flux-closure structure is preserved. These findings provide theoretical insights and practical guidance for identifying and manipulating topological structures in low-symmetry ferroelectrics, paving the way for developing energy-efficient microelectronic devices based on topological structures.

P-E loop↗
DOE OSTI2026

Antarctic Meltwater Accelerates Southern Ocean Evolution Under Projected Atmospheric Warming

Increasing basal meltwater from Antarctic ice shelves may impact the Southern Ocean properties that feed back on the rate of melting. We investigate this feedback in a high‐emissions scenario using an Earth‐system model with interactive ice‐shelf basal melting, an improvement on previous studies that did not have the capability to evolve melt rates and the ocean state self‐consistently. We find that when interactive melt increases, it primarily accelerates the evolution of a spatial pattern of continental shelf warming and cooling that is initiated by freshening and sea‐ice formation decline due to projected atmospheric warming. The competition between enhanced warming at depth from reduced ventilation and enhanced continental shelf cooling from reduced dense water export leads to net ~35% reduction in ice‐shelf meltwater input into the Southern Ocean over the 21st century. Omitting this feedback introduces a bias in the timing of projected ocean‐melt‐driven ice loss from Antarctica.

58 GEOSCIENCES↗
DOE OSTI2025

Magnetic devil's staircaselike behavior in quasiperiodic qubit lattices

The devil's staircase (DS) phenomenon is a fractal response of magnetization to external fields, traditionally observed in periodic ferromagnetic systems, where the commensurability between spin arrangements, lattice parameters, and external magnetic fields governs abrupt changes in magnetization. Its occurrence in aperiodic, fractal-type systems has remained largely unexplored, despite their natural compatibility with such phenomena. Using a quantum annealing device, we uncover a wealth of abrupt magnetic transitions between spin manifolds driven by increasing external magnetic fields within a simple yet effective Ising-model framework. In contrast to periodic systems, where DS arises from long-range competing interactions, our findings reveal that short-range, purely antiferromagnetic couplings in aperiodic geometries produce equally rich ground-state magnetization patterns. Here, we demonstrate that while magnetic textures are determined by the lattice size, their formation remains remarkably robust and independent of scale, with commensurability emerging locally. Our results challenge the prevailing view that DS behavior is limited to periodic systems and establish quasiperiodic geometries as a natural host for this phenomenon.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Data for "Event Horizon Telescope Pattern Speeds in the Visibility Domain”

Visibility Amplitude Pattern Speeds from the v3 Sgr A* Library. Data for "Event Horizon Telescope Pattern Speeds in the Visibility Domain” (Conroy et al.). Data are provided in 2 file formats: a TXT table which is a standard format for the Astrophysical Journal (ApJ) where the paper is submitted and the original NPY format.

Conroy, Nicholas S. [University of Illinois] (ORCI↗
DOE OSTI2024

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

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

A microfluidic spore chamber for long-term imaging of single-spore hyphal development.

Understanding the life cycle of fungal spores is essential for elucidating their roles in pathogenesis, dispersal, and survival. However, studying spore development under controlled, spatially defined conditions remains challenging. Here, we present the Spore Chamber, a custom-built microfluidic platform engineered for parallel trapping and long-term imaging of individual spores under defined media conditions, enabling real-time visualization of hyphal development. Using Aspergillus fumigatus as a model organism, we demonstrate that sparse trapping of individual spores within size-matched trap geometries enables long-term time-lapse imaging of key developmental stages, including germination, polarized hyphal elongation, branching, and conidiophore formation. To assess the device's capacity to resolve morphogenetic responses to exogenous signals, we introduced lipochitooligosaccharides (LCOs) and short-chain chitooligosaccharides (COs). Rhizobium-derived, non-sulfated LCO (nsLCO) mixtures induced enhanced secondary branching (hyperbranching), a response not previously reported in A. fumigatus under these signal conditions, to our knowledge, whereas sulfated LCOs and CO4 did not significantly alter branching patterns. In addition, long-term confinement and imaging revealed rare developmental morphologies previously described primarily in mutant strains, including split conidiophore formation, elongated phialides, and stress-associated phenomena such as microcyclic conidiation, and chlamydospore development. Together, these results establish the Spore Chamber as a targeted microfluidic platform for single-spore phenotyping and long-term developmental analysis, with applications in fungal biology, chemical signaling studies, and host–microbe interaction research.

Antifungal screening↗
DOE OSTI2025

Dataset for "A Microfluidic Spore Chamber for Long-Term Imaging of Single-Spore Hyphal Development"

Understanding the life cycle of fungal spores is essential for elucidating their roles in pathogenesis, dispersal, and survival. However, studying spore development under controlled, spatially defined conditions remains challenging. Here, we present the Spore Chamber, a custom-built microfluidic platform engineered for parallel trapping and long-term imaging of individual spores under defined media conditions, enabling real-time visualization of hyphal development. Using Aspergillus fumigatus as a model organism, we demonstrate that sparse trapping of individual spores within size-matched trap geometries enables long-term time-lapse imaging of key developmental stages, including germination, polarized hyphal elongation, branching, and conidiophore formation. To assess the device’s capacity to resolve morphogenetic responses to exogenous signals, we introduced lipochitooligosaccharides (LCOs) and short-chain chitooligosaccharides (COs). Rhizobium-derived, non-sulfated LCO (nsLCO) mixtures induced enhanced secondary branching (hyperbranching), a response not previously reported in A. fumigatus under these signal conditions, to our knowledge, whereas sulfated LCOs and CO4 did not significantly alter branching patterns. In addition, long-term confinement and imaging revealed rare developmental morphologies previously described primarily in mutant strains, including split conidiophore formation, elongated phialides, microcyclic conidiation, and chlamydospore development. Together, these results establish the Spore Chamber as a targeted microfluidic platform for single-spore phenotyping and long-term developmental analysis, with applications in fungal biology, chemical signaling studies, and host–microbe interaction research. Videos of the observed phenomena are included in this data set.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Decoding α-MoC 1− x Nanoparticle Formation in Continuous Flow via Machine Learning

Molybdenum carbide nanoparticles (α-MoC 1−x NPs) are promising catalysts that offer noble-metal-like performance at lower cost. We report a mild continuous-flow synthesis of α-MoC 1−x NPs from Mo(CO) 6 , coupled with in-line spectroscopic monitoring and machine learning (ML)-based analysis to quantify precursor conversion and product formation in real time. A multilayer perceptron ML model was found to accurately deconvolute complex, nonlinear spectral patterns, enabling identification of a two-step reaction pathway, involving precursor conversion to an amorphous intermediate followed by intraparticle crystallization to α-MoC 1−x NPs, with the first step being rate limiting. Ex situ small angle X-ray scattering (SAXS) and X-ray diffraction (XRD) validation confirm the predicted concentration profiles and crystallization behavior. This integrated approach showcases how ML can empower insights into NP nucleation and growth, paving the way for self-driving, flow-based platforms for NP synthesis.

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

Carrier Localization and Spontaneous Formation of Two-Dimensional Polarization Domain in Halide Perovskites

Halide perovskites are known for their rich phase diagram and superior performance in diverse optoelectronics applications. The latter property is often attributed to the long electron-hole recombination time, whose underlying physical mechanism has been a long-standing controversy. In this Letter, we investigate the transport and localization properties of electron and hole carriers in a prototypical halide perovskite (CsPbBr 3 ), through ab initio tight-binding nonadiabatic dynamics approach for large-scale (tens of nm size) supercell calculations, to simulate electron and ion dynamics on the same footing. Here, we found distinct structural, lattice polarization, and electron-phonon coupling properties at low (below 100 K) and high temperatures, consistent with experimental observations. In particular, at low temperature we find spontaneous formation of polar grain boundaries in the nonpolar bulk systems, which result in two-dimensional polarization patterns that serve to localize and separate electrons and holes. We reveal phonon-assisted variable-range hopping mostly responsible for low-temperature transport, and their characteristic frequency correlates with temperature-dependent phonon power spectrum and energy oscillation frequency in nonadiabatic dynamics. We answer the critical questions of long electron-hole recombination lifetime at low temperature and offer the correlation among polarization domains, electron-phonon couplings, and photocarrier dynamics.

Carrier generation & recombination↗
DOE OSTI2025

𝐷 0 -meson-tagged jet axes difference in proton-proton collisions at $\sqrt{s}$ = 5.02 TeV

Heavy-flavor quarks produced in proton-proton (pp) collisions provide a unique opportunity to investigate the evolution of quark-initiated parton showers from initial hard scatterings to final-state hadrons. By examining jets that contain heavy-flavor hadrons, this study explores the effects of both perturbative and nonperturbative QCD on jet formation and structure. The angular differences between various jet axes, Δ⁢𝑅 axis , offer insight into the radiation patterns and fragmentation of charm quarks. The first measurement of 𝐷 0 -tagged jet axes differences in pp collisions at $\sqrt{s}$ =5.02 TeV by the ALICE experiment at the LHC is presented for jets with transverse momentum 𝑝$^{ch jet}_{T}$ ≥ 10 GeV/𝑐 and 𝐷 0 mesons with 𝑝$^{D^0}_{T}$ ≥ 5 GeV/𝑐. In this 𝐷 0 -meson-tagged jet measurement, three jet axis definitions, each with different sensitivities to soft, wide-angle radiation, are used: the standard axis, soft drop groomed axis, and winner-takes-all axis. Measurements of the radial distributions of 𝐷 0 mesons with respect to the jet axes, Δ⁢𝑅 axis−D 0 , are reported, along with the angle, Δ⁢𝑅 axis , between the three jet axes. The 𝐷 0 meson emerges as the leading particle in these jets, closely aligning with the winner-takes-all axis and diverging from the standard jet axis. The results also examine how varying the sensitivity to soft radiation with grooming influences the orientation of the soft drop jet axis and uncover that charm-jet structure is more likely to survive grooming when the soft drop axis is further from the 𝐷 0 direction, providing further evidence of the dead-cone effect recently measured by ALICE.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗