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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The nanoscale distribution of copper and its influence on charge collection in CdTe solar cells

For decades, Cu has been the primary dopant in CdTe photovoltaic absorbers. Typically, Cu acceptor concentrations in these devices are on the order of 1 1014 cm-3, which has made it notoriously difficult to directly correlate nanoscale Cu distributions to the local charge transport properties of these devices. To measure and correlate these properties, measurement techniques require high sensitivity to elemental concentration, large penetration depth, and operando compatibility. Techniques such as secondary-ion mass spectroscopy and X-ray energy dispersive spectroscopy are widely adopted to measure Cu concentrations, but they are limited by penetration depth, sensitivity, or spatial resolution. Additionally, they lack the operando capabilities required to correlate one-to-one Cu concentrations to electrical performance. In this work, correlative X-ray microscopy is used to investigate the spatial distribution of Cu and its impact on charge collection through the depth and breadth of CdTe photovoltaic devices. Plan-view, nanoscale X-ray fluorescence maps clearly demonstrate the spatial segregation of copper around regions thought to be CdTe grain boundaries. Complementary cross-section imaging unveils the transition of the maximum charge-collection efficiency from the ZnTe-CdTe interface to the CdS-CdTe interface as a function of Cu incorporation. The copper concentration through the depth of the CdTe layer is characterized by slow and fast diffusion components, and cross-section charge-transport modeling shows that the experimentally obtained charge collection can be explained by the modeled acceptor distribution through the depth of the CdTe layer.

14 SOLAR ENERGY↗
DOE OSTI2025

Multiscale, mechanistic modeling of cesium transport in silicon carbide for TRISO fuel performance prediction

Understanding cesium (Cs) transport in TRistructural ISOtropic (TRISO) particle fuel is crucial for predicting fission product release in high-temperature reactors. However, current challenges include significant scatter in diffusivity data and unexplained temperature-dependent diffusion regimes in the silicon carbide layer. This study addresses these challenges by developing a multiscale, mechanistic Cs transport model integrating atomistic simulations and phase field modeling. Our model quantifies temperature and grain size effects on Cs diffusivity, attributing experimentally observed regimes to a transition from bulk-dominated diffusivity at high temperatures to grain boundary-dominated diffusivity at lower temperatures. The model, validated against diffusion measurements and advanced gas reactor (AGR)-1 and AGR-2 post-irradiation fission product release data, enhances the predictive capability of the BISON fuel performance code. This study advances our understanding of Cs release from TRISO particles and its dependence on temperature and silicon carbide grain size, with implications for the safety and efficiency of high-temperature nuclear reactors.

BISON↗
DOE OSTI2023

Time dependent chlorination of CeO 2 , La 2 O 3 and Nd 2 O 3 by ZrCl 4 dissolved in eutectic LiCl–KCl

Partial chlorination of CeO 2 , La 2 O 3 , and Nd 2 O 3 was achieved using ZrCl 4 dissolved in molten LiCl-KCl at 450°C over a period of 4-5 hr. ZrCl 4 was pre-volatilized into an argon stream to maintain a constant vapor pressure for equilibration with the salt. This approach was effective at maintaining the ZrCl 4 concentration at the solubility limit of 1.3 mol% in the molten salt throughout the duration of two of the chlorination experiments and within about 60% of the solubility limit in the third experiment. Based on the analysis of salt samples, fractional conversion after four hours of reaction for CeO 2 , and five hours for La 2 O 3 , and Nd 2 O 3 were calculated to be 0.97, 0.28, and 0.65 respectively. Assuming a shrinking core diffusion-limited model, the diffusivity of ZrCl 4 through the hypothesized ZrO 2 layer was calculated for the chlorination of CeO 2 , La 2 O 3 , and Nd 2 O 3 were 1.76 x 10 -10 cm 2 /sec, 7.85 x 10 -12 cm 2 /sec, and 7.42 x 10 -12 cm 2 /sec, respectively. Given the extremely low values calculated for diffusivity, it was concluded that the process is chemical reaction rate limited and that a complete reaction of each rare earth oxide could be achieved. Furthermore, a chemically controlled shrinking core model was shown to also fit the experimental data closely.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Control of Two Solid Electrolyte Interphases at the Negative Electrode of an Anode‐Free All Solid‐State Battery based on Argyrodite Electrolyte

Abstract Anode‐free all solid‐state batteries (AF‐ASSBs) employ “empty” current collector with three active interfaces that determine electrochemical stability; lithium metal – Solid electrolyte (SE) interphase (SEI‐1), lithium – current collector interface, and collector – SE interphase (SEI‐2). Argyrodite Li 6 PS 5 Cl (LPSCl) solid electrolyte (SE) displays SEI‐2 containing copper sulfides, formed even at open circuit. Bilayer of 140 nm magnesium/30 nm tungsten (Mg/W‐Cu) controls the three interfaces and allows for state‐of‐the‐art electrochemical performance in half‐cells and fullcells. AF‐ASSB with NMC811 cathode achieves 150 cycles with Coulombic efficiency (CE) above 99.8%. With high mass‐loading cathode (8.6 mAh cm −2 ), AF‐ASSB retains 86.5% capacity after 45 cycles at 0.2C. During electrodeposition of Li, gradient Li‐Mg solid solution is formed, which reverses upon electrodissolution. This promotes conformal wetting/dewetting by Li and stabilizes SEI‐1 by lowering thermodynamic driving force for SE reduction. Inert refractory W underlayer is required to prevent ongoing formation of SEI‐2 that also drives electrochemical degradation. Inert Mo and Nb layers likewise protect Cu from corroding, while Li‐alloying layers (Mg, Sn) are less effective due to ongoing volume changes and associated pulverization. Mechanistic explanation for observed Li segregation within alloying Li x Mg layer is provided through mesoscale modelling, considering opposing roles of diffusivity differences and interfacial stresses.

Wang, Yixian [Materials Science and Engineering Pr↗
DOE OSTI2023

Disorder and hydrogenation in graphene nanopowder revealed by complementary X-ray and neutron scattering

Functionalization of graphene's two-dimensional sheets can be used to modify the physical properties of graphene, such as changing its conductivity or inducing ferromagnetism, which is of broad interest for a myriad of applications. However, functionalized graphene can possess significant structural disorder that is often overlooked and is difficult to characterize quantitatively. Here we investigate hydrogenated graphene nanopowder (H-Gr) produced by Birch reduction of graphene oxide. By combining complementary x-ray and neutron diffraction, we show how to quantitatively characterize the H-Gr nanostructure, including the hydrogen content. Further, we show that the majority of the H-Gr consists of highly disordered molecular-scale carbon while a small portion of the sample contains few-layered graphene having an expanded interlayer spacing. Modeling the coherent diffuse scattering for both x-ray and neutron diffraction, and comparing it with the incoherent neutron scattering, the hydrogen to carbon ratio was measured and it was determined that most of the hydrogen resides within the disordered carbon rather than in the graphene. Evidence is presented for hydrogen clustering as well as for hydrogen bonded perpendicular to the plane of molecular-carbon bonds. Our quantitative approach to characterizing carbon nanopowders has broad relevance to understanding disorder and bonding of hydrogen in graphitic carbons and other nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Surrogate Model Development of Spent Fuel Degradation for Repository Performance Assessment

In model simulations of deep geologic repositories, UO 2 fuel matrix degradation typically begins as soon as the waste package breaches and groundwater contacts the fuel surface. The initial degradation rate depends on the timing of these events, burnup of the fuel, temperature, and concentrations of dissolved reactants. Estimating the initial rate of degradation is fairly straightforward, but as UO 2 corrosion products precipitate on the fuel surface and the movement of dissolved species between the fuel surface and environment is impeded by the precipitated solids, the rate is more difficult to quantify. At that point, calculating the degradation rate becomes a reactive-transport problem in which a large number of equations must be solved by iteration for a large number of grid cells at each time step. The consequence is that repository simulations, which are already expensive, become much more expensive, especially when hundreds or thousands of waste packages breach. The Fuel Matrix Degradation (FMD) model is the process model of the Spent Fuel and Waste Science and Technology (SFWST) campaign of the US Department of Energy (DOE). It calculates spent fuel degradation rates as a function of radiolysis, redox reactions, electrochemical reactions, alteration layer growth, and diffusion of reactants through the alteration layer. Like other similar fuel degradation process models, it is a complicated model requiring a large number of calculations and iterations at each time step.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Electric Field Effects on Water and Ion Structure and Diffusion at the Orthoclase (001)–Water Interface

Understanding the electrochemical properties of mineral–water interfaces tends to rely upon electrical double layer (EDL) models, but these models are based on the assumption that electrostatic equilibrium is constantly maintained. In reality, interfacial reactions, ion diffusion, and their electrochemical signatures are based in nonequilibrium conditions of locally or globally imbalanced electrical fields where current EDL models have limited purview. In this work, we performed molecular dynamics (MD) simulations of the orthoclase (001) surface in contact with a 1 M NaCl aqueous solution under various electric fields, to explore the interplay between EDL structure and dynamics when perturbed by electric fields of different direction and strength, by confinement, and by different distributions of structural surface charge. The simulations showed that confinement between two opposing (001) surfaces led to the development of an induced field when the applied field was perpendicular to the surfaces and, as a result, to ionic diffusion coefficients that were independent of electric field strength. In contrast, when the applied field was parallel to the surfaces, confinement resulted in ionic diffusion coefficients that were more strongly dependent on the magnitude of the electric field than in bulk water. Differences in the density and distribution of aluminol groups on the two surfaces had a significant impact on how the interfacial structure and dynamics varied in the presence of an electric field. Notably, these differences resulted in an electro-osmotic flow with opposite directions at the two surfaces under parallel applied electric field. Overall, the MD simulations highlighted the importance of considering atomic-level structure and heterogeneities when developing models of the electrochemical properties of mineral–water interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Assessment and Improvement of Fission Product Transport Predictions of Particle Fuel in BISON

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. This study was motivated by the need to incorporate more physics-based models in BISON in order to foster tri-structural isotropic (TRISO) applications. This document details the integration of new modeling capabilities in BISON, including (1) development of pyrolytic carbon (PyC) and silicon carbide (SiC) layer anisotropic thermal and mass transport capabilities, (2) verification of the mass diffusion solution in TRISO modeling, (3) calibration of fission product diffusivity using Advanced Gas Reactor (AGR) experiments, (4) improved fission product release modeling by developing compact diffusion modeling capabilities, and (5) documentation of accelerated failure analysis on the BISON website. Improvements made to the diffusion models and parameters were documented and validated against AGR-1 and -2 experiment data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Understanding Carbon Dioxide Transfer in Direct Methanol Fuel Cells Using a Pore-Scale Model

Abstract The gas flow of carbon dioxide from the catalyst layer (CL) through the microporous layer (MPL) and gas diffusion layer (GDL) has great impacts on the water and fuel management in direct methanol fuel cells (DMFCs). This work has developed a liquid–vapor two-phase model considering the counter flow of carbon dioxide gas, methanol, and water liquid solution in porous electrodes of DMFC. The model simulation includes the capillary pressure as well as the pressure drop due to flow resistance through the fuel cell components. The pressure drop of carbon dioxide flow is found to be about two to three orders of magnitude higher than the pressure drop of the liquid flow. The big difference between liquid and gas pressure drops can be explained by two reasons: volume flowrate of gas is three orders of magnitude higher than that of liquid; only a small fraction of pores (<5%) in hydrophilic fuel cell components are available for gas flow. Model results indicate that the gas pressure and the mass transfer resistance of liquid and gas are more sensitive to the pore size distribution than the thickness of porous components. To buildup high gas pressure and high mass transfer resistance of liquid, the MPL and CL should avoid micro-cracks during manufacture. Distributions of pore size and wettability of the GDL and MPL have been designed to reduce the methanol crossover and improve fuel efficiency. The model results provide design guidance to obtain superior DMFC performance using highly concentrated methanol solutions or even pure methanol.

Electrochemistry↗
DOE OSTI2022

Understanding the E balance for water management in hydroxide exchange membrane fuel cells

As a key challenge for hydroxide exchange membrane fuel cells (HEMFCs), understanding water management deeply is critical for performance and durability improvement. Here, in this work, we show that the balance between water generation and phase-change-induced (PCI) flow is the main factor controlling cell voltage over a wide range of conditions where the cells are vulnerable to severe flooding. The regulation of flooding by heat generation can be reflected by a stable voltage with increase of current density in the polarization curve. This PCI balance voltage (E balance ), which determines the shape of polarization curve, is modeled as a function of cell operating conditions and gas diffusion layer (GDL) properties. Temperature, pressure, and thermal conductivity of GDL were found important for tuning the level of E balance , both in HEMFCs and proton exchange membrane fuel cells. The understanding of E balance will help to generate strategies for resolving flooding in HEMFCs, and it offers a new perspective for polarization curve interpretation.

25 ENERGY STORAGE↗
DOE OSTI2022

Improved Representation of Horizontal Variability and Turbulence in Mesoscale Simulations of an Extended Cold-Air Pool Event

Abstract Cold-air pools (CAPs), or stable atmospheric boundary layers that form within topographic basins, are associated with poor air quality, hazardous weather, and low wind energy output. Accurate prediction of CAP dynamics presents a challenge for mesoscale forecast models in part because CAPs occur in regions of complex terrain, where traditional turbulence parameterizations may not be appropriate. This study examines the effects of the planetary boundary layer (PBL) scheme and horizontal diffusion treatment on CAP prediction in the Weather Research and Forecasting (WRF) Model. Model runs with a one-dimensional (1D) PBL scheme and Smagorinsky-like horizontal diffusion are compared with runs that use a new three-dimensional (3D) PBL scheme to calculate turbulent fluxes. Simulations are completed in a nested configuration with 3-km/750-m horizontal grid spacing over a 10-day case study in the Columbia River basin, and results are compared with observations from the Second Wind Forecast Improvement Project. Using event-averaged error metrics, potential temperature and wind speed errors are shown to decrease both with increased horizontal grid resolution and with improved treatment of horizontal diffusion over steep terrain. The 3D PBL scheme further reduces errors relative to a standard 1D PBL approach. Error reduction is accentuated during CAP erosion, when turbulent mixing plays a more dominant role in the dynamics. Last, the 3D PBL scheme is shown to reduce near-surface overestimates of turbulence kinetic energy during the CAP event. The sensitivity of turbulence predictions to the master length-scale formulation in the 3D PBL parameterization is also explored. Significance Statement In this article, we demonstrate how a new framework for modeling atmospheric turbulence improves cold pool predictions, using a case study from January 2017 in the Columbia River basin (U.S. Pacific Northwest). Cold pools are regions of cold, stagnant air that form within valleys or basins, and improved forecasts could help to mitigate the risks they pose to air quality, transportation, and wind energy production. For the chosen case study, our tests show a reduction in temperature and wind speed errors by up to a factor of 2–3 relative to standard model options. These results strongly motivate continued development of the framework as well as its application to other complex weather events.

17 WIND ENERGY↗
DOE OSTI2025

Ab Initio Design of High-Entropy Thermal/ Environmental Barrier Coatings

Next generation thermal/environmental barrier coatings (TEBC) require carefully balancing various properties including phase stability, thermal conductivity, coefficient of thermal expansion (CTE), mechanical properties, and resistance against hot corrosion and water vapor recession. This work mainly focuses on rapid design of cost-effective high entropy rare-earth disilicates and aluminum garnets to protect SiC-based ceramic matrix composites and nickel-based superalloys in the hot section of gas turbine engines using density functional theory methods. Our calculations identify several low-cost high entropy TEBC exhibiting ultralow thermal conductivity at 1500 K and desirable CTE while maintaining good mechanical properties, including Er1/2Y3/4Yb3/4Si2O7, Gd1/4Er1/4Y3/4Yb3/4Si2O7, Eu1/4Er1/4Y3/4Yb3/4Si2O7, and (Y1/4Gd1/4Er1/4Yb1/4)3Al5O12. This work also aims to gain fundamental understanding of oxygen diffusion in model disilicates. Minimizing oxidizer (such as water vapor and oxygen) permeability through the EBC layer can significantly decrease the growth rate of thermally grown oxide and extend the service life of the coating system. Oxygen diffusion mechanisms including formation energy of defects under varying oxygen conditions and defect migration energy barriers will be presented.

coefficient of thermal expansion↗
DOE OSTI2022

Analysis of Compressibility Effects and Nonlinear Property Variations in a Supercritical CO2 Mixing Layer

Calculations are performed using the large eddy simulation technique to qualitatively assess the effects of fluid compressibility and thermodynamic nonlinearities on the dynamics of a supercritical flow field. Resulting data are also used to interrogate instantaneous subfilter-scale fields, as modeled by the mixed-dynamic Smagorinsky closure and gradient diffusion model. A three-dimensional wall-resolved calculation of a spatially evolving mixing layer composed solely of carbon dioxide is performed. This is followed by a coarse grid calculation to examine model performance as a function of resolution. Theoretical analysis indicates that the partial derivatives of density with respect to pressure and temperature are important modulators of the temperature and pressure field evolution, respectively. Results pertaining to subfilter velocity-velocity and velocity-temperature fields indicate that the models are most stressed in the regions where compressibility and thermo-fluid nonlinearities dominate the physics.

42 ENGINEERING↗
DOE OSTI2024

Multiscale, mechanistic modeling of irradiation-enhanced silver diffusion in TRISO particles

Tristructural isotropic (TRISO) particles are under consideration for use in several proposed advanced nuclear reactor concepts. The silicon carbide (SiC) layer in TRISO acts as a barrier to prevent the release of the fission products. However, despite remarkable retention, silver (Ag) release has been observed from intact particles, which requires investigation since the Ag isotope ( 110m Ag) has a long half-life. Previous work focused on developing a multiscale, mechanistic model for Ag diffusion accounting for temperature and microstructure effect and has been successfully validated. In this work, we expand the previous model to account for irradiation-enhanced Ag diffusivity in SiC and improve its accuracy over a wider grain size and temperature ranges relevant for advanced reactor conditions. A temperature, grain size, and flux dependent diffusivity is therefore derived using the mesoscale code MARMOT and implemented in the fuel performance code BISON. The irradiation-enhanced Ag diffusivity in SiC is compared against experimental data and validated using BISON against Ag release measurements from the Advanced Gas Reactor Fuel Development and Qualification Program (AGR-1 and AGR-2). Herein, we quantify the impact of SiC grain size, irradiation, and temperature on Ag release. In agreement with previous studies, we find accounting for SiC grain size improves agreement between BISON predictions and experimental observations for most cases. In conclusion, we also find that accounting for irradiation improves agreement for cases where Ag release was underestimated, but the impact was less significant than accounting for microstructure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Intrinsic rotation modulation by diffusive neutral particles in tokamaks

Abstract The modulated transport model, a model kinetic ion transport equation for the pedestal and scrape-off layer (SOL), is generalized to self-consistently include effects of a single neutral particle species. The neutrals contribute additional transport terms, modifying the v ∥ -dependent orbit-averaged ion diffusivities of the original work and the resulting predicted intrinsic rotation of the ions. After making simplifying assumptions of the neutral transport, in particular taking the continuous transport limit via a short charge-exchange step expansion, we derive relatively simple analytic expressions that capture the diffusive neutral physics. Within the scope of the model’s validity, the neutral-driven intrinsic rotation can compete with the turbulence-driven intrinsic rotation. However, for physically motivated parameters, the neutral-driven intrinsic rotation appears negligible, either on a term-by-term basis or due to a strong cancellation between the neutral-driven momentum diffusion and pinch terms. It appears that a treatment containing finite charge-exchange steps is necessary to capture neutral transport of strong flow momentum into the confined region from the SOL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Deconvolution of Water-Splitting on the Triple-Conducting Ruddlesden–Popper-Phase Anode for Protonic Ceramic Electrolysis Cells

Triple-conducting materials have been proved to improve the performance of popular protonic ceramic electrolysis cells. However, partially because of the complexity of the water splitting reaction involving three charge carriers, that is, oxygen (O 2– ), proton (H + ), and electron (e – ), the triple-conducting reaction mechanism was not clear, and the reaction conducting pathways have seldom been addressed. In this study, the triple conducting Ruddlesden–Popper phase Pr 1.75 Ba 0.25 NiO 4+δ as an anode on the BaCe 0.7 Zr 0.1 Y 0.1 Yb 0.1 O 3–δ electrolyte was fabricated and its electroresponses were characterized by electrochemical impedance spectroscopy with various atmospheres and temperatures. The impedance spectra are deconvoluted by means of the distribution of the relaxation time method. The surface exchange rate and chemical diffusivity of H + and O 2– are characterized by electrical conductivity relaxation. The physical locations of electrochemical processes are also identified by atomic layer deposition with a surface inhibitor. A microkinetics model is proposed toward conductivities, triple-conducting pathways, reactant dependency, surface exchange and bulk diffusion capabilities, and other relevant properties. Lastly, the rate-limiting steps and suggestions for further improvement of electrode performance are presented.

25 ENERGY STORAGE↗
DOE OSTI2022

Developing novel electrodes with ultralow catalyst loading for high-efficiency hydrogen production in proton exchange membrane electrolyzer cells

Hydrogen plays more crucial roles for decarbonizing the planets and meeting the climate challenges because of its high energy density and zero-emission. It can be produced with proton exchange membrane electrolyzer cells (PEMECs) driven by sustainable and renewable energy resources. Although PEMECs have a number of advantages, including high purity production, quick response, and the ability to operate at high pressure facilitating the gas delivering, their performance and cost greatly hinder their commercial-scale applications. To achieve high-efficiency and cost-reduced hydrogen production in PEMECs, we proposed thin engineered liquid/gas diffusion layers (LGDLs) and associated electrodes, i.e., catalyst-coated LGDLs (CCLGDLs), over conventional porous transport layers (PTLs) and catalyst-coated membranes (CCMs). The research approaches in this project are based on material synthesis, in-situ and ex-situ characterizations, component design and treatment, numerical modeling, and cost analysis. The thin and tunable LGDLs (TT-LGDLs) and CCLGDLs were successfully developed with great performance improvement as demonstrated in lab-scale, bench-scale, and system-scale electrolyzer tests. The electrode thickness was reduced from 370 µm to less than 100 µm with simplified fabrication processes. With the catalytically enhanced Ir-based catalyst coating, the as-developed CCLGDLs with a catalyst loading of 0.34 mg Ir /cm 2 achieved a cell performance of 1.77 V at 2 A cm -2 , exhibiting the catalyst mass activity enhanced by >20 times with significant catalyst saving over conventional catalyst cell design. In-situ PEMEC characterizations, including the current distribution mapping and high-speed and multiscale visualizations, were conducted for a deeper understanding of mass transport and electrochemical reactions within an electrolyzer with LGDLs and CCLGDLs. A 2D cell model was developed and validated for the enhanced performance on TT-LGDL through reducing ohmic losses due to nonuniform hydration and water transport. Further, the cost analysis results have shown a path to move beyond equivalency and surpass costs associated with the project baseline. In this project, the design and fabrication of TT-LGDLs and CCLGDLs will contribute to the performance enhancement, manufacturing simplification, and cost reduction for PEMECs and other energy conversion devices, thus shortening their pathways towards commercialization. This project also provides a good foundation for furthering the in-situ reaction interface research.

08 HYDROGEN↗
DOE OSTI2025

Structural differences between human and mouse neurons and their implementation in generative AIs

Mouse and human brains have different functions that depend on their neuronal networks. We analyzed nanometer-scale three-dimensional structures of brain tissues of the mouse medial prefrontal cortex and compared them with structures of the human anterior cingulate cortex. The obtained results indicated that mouse neuronal somata are smaller and neurites are thinner than those of human neurons. We implemented these characteristics of mouse neurons in convolutional layers of a generative adversarial network (GAN) and a denoising diffusion implicit model (DDIM), which were then subjected to image generation tasks using photo datasets of cat faces, cheese, human faces, birds, and automobiles. The mouse-mimetic GAN outperformed a standard GAN in the image generation task using the cat faces and cheese photo datasets, but underperformed for human faces and birds. The mouse-mimetic DDIM gave similar results, suggesting that the nature of the datasets affected the results. Analyses of the five datasets indicated differences in their image entropy, which should influence the number of parameters required for image generation. The preferences of the mouse-mimetic AIs coincided with the impressions commonly associated with mice. The relationship between the neuronal network and brain function should be investigated by implementing other biological findings in artificial neural networks.

generative AI↗