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At least 631 records · Page 35

Understanding Gas Absorption in Multivalent Ionic Liquids via Solute-Solvent Interaction Analyses

Solute-solvent interactions are often evaluated to understand and explain gas solubilities. This information is regularly used to interpret gas solubility and separation within ionic liquids (ILs). Here, we use several different quantum chemical and previous molecular dynamics simulation results to show that strong solute-solvent interactions neither lead to high solubility nor to high selectivity, with respect to other solutes. Instead, the solute-solvent interaction strength with different isolated IL ions is affected by the electrostatic extremes. Also, the solute-solvent interaction with different IL molecules is strongly correlated to the molecular volumes or polarizabilities (within a series of same-anion based ILs).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the long-term influence of EIA on organisational learning and transformation

This research is an attempt to verify the notion postulated by Robert Bartlett and Lynton Caldwell that the full benefits of environmental impact assessment (EIA) would take decades to be realized. While EIA is intended to directly influence decision-making regarding new development proposals, the process is also expected to lead to organisational learning and transformation over time. Our aim was to examine the influence of EIA on a single Western Australian proponent with sustained experience in the process to understand how EIA is used within the organisation and to seek evidence of transformation of the organisation's purpose and mission. The research reviewed literature in order to identify key influences of EIA on organisations, along with semi-structured staff interviews and document analysis for the case study organisation. Ascertaining causality that involvement in EIA processes influences or effects organisational learning and transformation is a challenge in the face of other societal events. Document analysis and interviewee data indicates that the action-forcing nature of EIA did influence proponent behavior through the creation of internal processes seeking to ensure robust design of new projects that would satisfy environmental protection expectations, without the need to trigger formal EIA. Evidence of EIA values and thinking were apparent within internal documentation, including the evolving mission statement. Our research indicates that participation in the EIA process can positively influence organisational learning and transformation by guiding internal change for decision-making. - Highlights: • The long-term influence of EIA on a proponent organisation is investigated. • EIA promotes internal organisational learning and transformation. • Analysis of mission statements can indicate the influence of EIA on organisations. • Organisations aligned with EIA values can reduce the need to engage in formal EIA.

54 ENVIRONMENTAL SCIENCES↗

Understanding the role of water-soluble guar gum binder in reducing capacity fading and voltage decay of Li-rich cathode for Li-ion batteries

The practical application of high-capacity Li-rich cathode materials is hindered by capacity fading and voltage decay. The capacity fading and voltage decay could be effectively overcome by using water-soluble guar gum (GG) binder instead of traditional polyvinylidene fluoride (PVDF). However, the specific role of the GG binder is not clear yet, though the GG binder can significantly improve the electrochemical performance of Li-rich cathode. To understand the effect of GG binder on the morphology, microstructure of electrode and electrode/electrolyte interfaces, ex-situ scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray adsorption near edge spectroscopy (XANES), in-situ electrochemical impedance spectroscopy (EIS) were applied to comparatively study the charge-discharge processes of Li-rich Li 1.2 Ni 0.2 Mn 0.6 O 2 cathode when using GG and PVDF as binders. The results indicate that the GG binder can prevent electrode crack and active material loss, ascribing to the strong mechanical adhesion of GG binder with active material particles and current collector. It has found that the GG binder can also induce the formation of a uniform layer on Li 1.2 Ni 0.2 Mn 0.6 O 2 particles’ surface. As a consequence, both the electrolyte decomposition and the electrode corrosion were significantly inhibited. The strong chelation between Mn 2+ and polar OH group restrain Mn ion dissolution, which contributes to surface structural transformation mitigation. Here, our study reveals the role of water-soluble GG binder in reducing capacity fading and voltage decay of Li-rich material and is of great importance in design functional binders for high-performance Li-rich electrodes.

25 ENERGY STORAGE↗

Understanding and improving anode performance in an alkaline membrane electrolyzer using statistical design of experiments

The behavior of the oxygen-evolving positive electrode (i.e. anode) in the anion exchange membrane water electrolyzer (AEMEL) is complex and influenced by several factors. Very few studies have been performed to understand oxygen evolution reaction (OER) behavior by optimizing the individual factors that influence performance. Here, this study highlights the effects of catalyst loading, catalyst selection, porous transport layer (PTL) type and conductive additive content. The influence of each factor is elucidated through a design of experiments (DoE) approach with a full statistical analysis. Electrochemical data, alongside Pareto charts, parametric trends and their mutual interactions are discussed. This DoE approach is also helpful in making useful predictions and discovering new combinations to be tested. The end result was a high-performance AEMEL able to operate at a current density of 1.0 A/cm 2 at 1.80 V with IrOx OER and PtNi hydrogen evolution reaction (HER) catalysts using 0.3 M KOH fed to the anode. Even lower operating voltage was observed with PbRuOx catalyst at the anode, 1.64 V @ 1.0 A/cm 2 , though the cell decay rate was higher. Lastly, a IrOx/PtNi cell was stably operated continuously for 30 days (720 h) at 1.0 A/cm 2 . This study can serve as a guide for optimal electrode design with insights into component-performance compromises, which can aid in making design choices and performing techno-economic analyses.

08 HYDROGEN↗

Using occupant interaction with advanced lighting systems to understand opportunities for energy optimization: Control data from a hospital NICU

For this study, lighting system control data from five patient rooms in a neonatal intensive care unit (NICU) over a 25-week monitoring period were analyzed to better understand how the NICU staff and families interacted with an automatic tunable lighting system (variable spectrum and intensity) with manual override options. The data were analyzed to determine the amount of time spent in available lighting modes, estimate energy consumption, and to observe any patterns in how the lighting system was being used by occupants. Further analysis revealed opportunities for optimizing the system for occupant needs and energy savings. The patient room occupants were clearly engaged in using the lighting system throughout the 24-hour day to meet needs and preferences. Giving occupants control over the lighting system did not result in a considerable increase in energy use. Implementing a time-out would minimize the extended periods of time when the lights were left on without need at the highest brightness level, further decreasing energy use. This analysis reveals the potential of lighting control data to contribute to energy savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Understanding the impacts of inorganic species in woody biomass for preprocessing and pyrolysis–A review

Woody biomass represents an abundant resource for sustainable biofuels, biochemicals, and bioproducts. Technologies for converting woody biomass have been established for decades, and research consistently highlights the critical role of inorganic species and ash plays in feedstock handling and conversion processes, including equipment plugging, corrosion, and catalyst deactivation. A thorough understanding of the variability, transport behavior, and downstream impact of inorganic species in woody biomass is essential for defining feedstock quality specifications and developing effective management strategies for conversion processes. This review compiles critical information in five main sections: 1) inorganic species concentration in woody biomass, based on anatomical fractions and their sources of variability; 2) technique features for quantifying inorganic elemental chemical analysis; 3) impacts of inorganic species on biomass preprocessing; 4) impacts of inorganic species on pyrolysis, and 5) mitigation strategies. Additionally, this review explores future challenges and opportunities in addressing the impacts of inorganic species on biomass quality. These insights aim to support the sustainable development of the biomass-to-bioenergy pipeline and ensure high-quality lignocellulosic feedstocks for efficient downstream conversions. The findings offer valuable guidance to policy makers, industry stakeholders, and researchers in developing effective strategies for managing inorganic species in woody biomass and fostering the sustainable processes for lignocellulosic biorefineries.

09 BIOMASS FUELS↗

Non-mercury methylating microbial taxa are integral to understanding links between mercury methylation and elemental cycles in marine and freshwater sediments

The goal of this study was to explore the role of non-mercury (Hg) methylating taxa in mercury methylation and to identify potential links between elemental cycles and Hg methylation. Statistical approaches were utilized to investigate the microbial community and biochemical functions in relation to methylmercury (MeHg) concentrations in marine and freshwater sediments. Sediments were collected from the methylation zone (top 15 cm) in four Hg-contaminated sites. Both abiotic (e.g., sulfate, sulfide, iron, salinity, total organic matter, etc.) and biotic factors (e.g., hgcA, abundances of methylating and non-methylating taxa) were quantified. Random forest and stepwise regression were performed to assess whether non-methylating taxa were significantly associated with MeHg concentration. Co-occurrence and functional network analyses were constructed to explore associations between taxa by examining microbial community structure, composition, and biochemical functions across sites. Regression analysis showed that approximately 80% of the variability in sediment MeHg concentration was predicted by total mercury concentration, the abundances of Hg methylating taxa, and the abundances of the non-Hg methylating taxa. The co-occurrence networks identified Paludibacteraceae and Syntrophorhabdaceae as keystone non Hg methylating taxa in multiple sites, indicating the potential for syntrophic interactions with Hg methylators. Strong associations were also observed between methanogens and sulfate-reducing bacteria, which were likely symbiotic associations. The functional network results suggested that non-Hg methylating taxa play important roles in sulfur respiration, nitrogen respiration, and the carbon metabolism-related functions methylotrophy, methanotrophy, and chemoheterotrophy. Interestingly, keystone functions varied by site and did not involve carbon- and sulfur-related functions only. In conclusion, our findings highlight associations between methylating and non-methylating taxa and sulfur, carbon, and nitrogen cycles in sediment methylation zones, with implications for predicting and understanding the impact of climate and land/sea use changes on Hg methylation.

54 ENVIRONMENTAL SCIENCES↗

Winds of fortune? Understanding the geographic, sociodemographic, and temporal distribution of benefit mechanisms from land-based wind projects in the United States

Despite decades of research on factors shaping local responses to wind development, there is relatively little known about benefit mechanisms (e.g., agreements, funds, donations) used by developers in the U.S. land-based wind sector. To address this gap, we collected benefit mechanism data across all current utility-scale land-based wind projects installed between 1982 and 2024 (n = 1047), finding that just under one-third of projects had a benefit mechanism attached to them. We find the use of benefit mechanisms has become more common over time, is associated with larger projects, and varies by region. In terms of host community characteristics, the use of benefit mechanisms is associated with characteristics like higher education level, higher percent white, higher percent Republican, higher decision-making capacity, lower unemployment rate, and higher poverty rate. Building on a theoretical framework of purposes, we discuss what these findings could suggest about the motivations driving developers' use of these mechanisms, such as increasing local acceptance of a wind project or supporting distributive fairness. This first-of-its-kind study builds a comprehensive understanding of how benefit mechanisms have been used in the U.S. wind industry throughout its history, which can inform future approaches to benefit-sharing across sectors.

17 WIND ENERGY↗

Understanding particle size effect on fast-charging behavior of graphite anode using ultra-thin-layer electrodes

Extreme fast charging (≤ 15 min) of lithium-ion batteries is highly desirable to accelerate mass-market adoption of electric vehicles. However, significant capacity fading, as well as safety issues due to the lithium plating caused by the fast charging rate, limit its implementation. In this study, we investigated the fast-charging capability of graphite materials with various particle sizes. To eliminate the Li + ion concentration gradient effect across the thickness of the electrode, ultra-thin-layer graphite electrodes were developed to investigate the "real" fast-charging capability of graphite at the particle level. Electrochemical assessments as well as microscopic characterizations revealed that smaller particles exhibited superior fast-charging performance, featuring enhanced capacity reversibility, faster charging rate, and less lithium plating under the same fast-charging conditions. It is shown that small-particle graphite (mean radius of 3.3 μm) could withstand a 4C charge (to 80 % state-of-charge) without plating, with minimal plating occurring at 6C. Thicker particles exhibited plating at lower C-rates. Since the experimental data could not directly explain whether intra-particle diffusion limitations or interfacial reaction limitations dominated the plating mechanism, the pseudo-2-dimensional model was used to evaluate the most likely plating mechanism. The model suggested that particle-level diffusion is the dominant mechanism contributing to plating at high rates. Finally, this work provides comprehensive insights into the particle size effects on fast-charging capability, offering a better understanding of fast-charging behavior and valuable guidance for designing optimal electrode architecture for high-rate lithium-ion batteries.

25 ENERGY STORAGE↗

Toward an Understanding of Surface Layer Formation, Growth, and Transformation at the Glass–Fluid Interface

Silicate glass is a metastable and durable solid that has application to a number of energy and environmental challenges (e.g., microelectronics, fiber optics, and nuclear waste storage). If allowed to react with water over time silicate glass develops an altered layer at the solid-fluid interface. In this study, we used borosilicate glass (LAWB45) as model material to develop a robust understanding of altered layer formation (i.e., amorphous hydrated surface layer and crystalline reaction products). Experiments were conducted at high surface area-to-volume ratio (~200,000 m-1) and 90 °C in the pressurized unsaturated flow (PUF) apparatus for 1.5-years to facilitate the formation of thick altered layers and allow for the effluent solution chemistry to be monitored continuously. A variety of microscopy techniques were used to characterized reacted grains and suggest the average altered layer thickness is 13.2 ± 8.3 μm with the hydrated and clay layer representing 74.8% and 25.2% of the total altered layer, respectively. This estimate is within the experimental error of the value estimated from the B release rate data (~10 ±1 μm/yr) over the 1.5-year duration. PeakForce® quantitative nanomechanical mapping results suggest the hydrated layer has a modulus that ranges between ~20 to 40 GPa, which is in the range of porous silica that contains from ~20 to ~50% porosity, yet significantly lower than dense silica (~70 to 80 GPa). Scanning transmission electron microscopy (STEM) images confirm the presence of pores and an analysis of a higher resolution image of a region provides a qualitative estimate of ≥ 22% porosity in this layer with variations in the hydrated layer in void volume with increasing distance from the unaltered glass. Chemical composition analyses, based on a combination of time-of-flight secondary-ion mass spectrometry (ToF-SIMS) and scanning electron microscopy with X-ray energy dispersive spectroscopy (EDS) and STEM-EDS, clearly show that the altered layer is mainly composed of Al, H, Si, and O with the clay layer being enriched in Li, Zn, Fe, and Mg. The amorphous hydrated layer is enriched in Ca, H, and Zr with a minor amount of K. Furthermore, ToF-SIMS results also suggest the B profile is anti-correlated with the H profile in the hydrated layer. Our selected-area electron diffraction results suggest the structure of the hydrated layer closely resembles opal-AG (amorphous gel-like) with an average crystallite size of ~0.7 nm which is smaller than the critical nucleus for silica nanoparticles (i.e., 1.4 to 3 nm). These results suggest the hydrated layer is more consistent with a polymeric gel rather than a colloidal gel and is comprised of molecular units (<1 nm in size) that result from the difficult to hydrolyze bonds, such as Si—O—Zr units, during the glass corrosion process. The size of individual particles or molecular units is a function of formation conditions (e.g., pH, ionic strength, nano-confinement, solute composition) in the hydrated layer.

36 MATERIALS SCIENCE↗

Understanding drivers of oil and gas well integrity issues in the greater wattenberg area of Colorado

Well integrity is critically important to maintain to minimize the environmental impacts of oil and gas development and other subsurface energy operations. The Wattenberg Field of Colorado—a top producing field with >40,000 wells—has one of the most robust publicly reported well integrity programs in the country. Here, in this study, we analyzed annular pressure and annular-fluid geochemical test results collected from Wattenberg wells through the end of 2019 to characterize the frequency and spatial variability of integrity issues in the field and understand their drivers. Estimated frequencies of integrity issues among tested wells were 8.2-17.1% between 1955 and 2019 and 6.1-11.4% in 2019 alone. The frequency of integrity issues was nearly four times greater in wells located above the Longmont Wrench Fault Zone. Potential drivers of integrity issues were identified using ensemble decision tree models trained with a broad set of relevant information. Models show that well integrity issues are spatially clustered on regional and sub-regional scales and suggest the relatively high frequency of integrity issues observed is likely attributed to geologic factors. These findings are valuable for regulatory agencies and operators seeking to inform well integrity monitoring, plugging, and emissions reduction efforts and design future subsurface energy projects.

03 NATURAL GAS↗

Visualization, understanding, and mitigation of process-induced-membrane irregularities in gas diffusion electrode-based polymer electrolyte membrane fuel cells

Polymer electrolyte membrane fuel cells (PEMFC) show substantial promise for their application in electric vehicles. For large-scale manufacturing of PEMFCs, roll-to-roll coated gas-diffusion-electrodes (GDE) offer certain advantages over other production pathways. Procedures including hot pressing and coating an ionomer overlayer may be necessary for this manufacturing pathway to enable a suitable catalyst layer/membrane interface. The same procedures may potentially introduce membrane irregularities, especially when thin membranes are used. Limited understanding exists regarding if and to what extent such irregularities impact PEMFC performance and lifetime, and therefore be considered defects. In this study, NREL's customized fuel cell hardware that enables quasi in-situ infrared (IR) thermography studies was utilized to visualize spatial hydrogen crossover and identify membrane irregularities that originated from the GDE-based MEA fabrication process. The structure of these membrane irregularities was investigated by scanning electron microscopy (SEM) and its impact on initial H2/air performance was determined. Accelerated stress testing (AST) revealed that these irregularities develop into failure point locations. These results were validated across many MEAs with identified process-induced membrane irregularities. By selecting specific gas diffusion media properties and by fine tuning the MEA hot pressing parameters, the formation of such membrane irregularities was mitigated.

08 HYDROGEN↗

Understanding syringeability and injectability of high molecular weight PEO solution through time-dependent force-distance profiles

Opioid medications play a vital role in treating moderate to severe pain. Unfortunately, many drug misusers and abusers attempt to alter the formulations or properties of these drugs by manipulation, (e.g., crushing, chewing, smoking, snorting, injecting). The intravenous (IV) route is most dangerous to abusers, as the drugs directly enter the circulatory system and produce intense euphoria. To obtain a full understanding of the impact of syringe factors (e.g., needle gauge size, needle length, syringe barrel size), on the ease of injection, we undertook a comprehensive assessment of syringeability and injectability of manipulated abuse-deterrent formulations (ADFs). A texture analyzer-based testing method was developed for the measurement of the resistance force of pulling, holding, and pushing phases of injections. Results showed that the finer needle gauge sizes required higher injection force to withdraw drug solutions. In addition, the syringed liquid volume was highly dependent on needle gauge size, holding time, and sample viscosity. In most cases, a lower needle gauge number and a longer holding time increased the syringed volume. Needle length was highly correlated to injection force (R 2 = 0.99). Using longer needles to inject drug solution requires greater force. Furthermore, large barrel size was correlated to pushing force (R 2 = 0.99); thus, increasing the difficulty of pushing the plunger of a large syringe with one hand. Lastly, relationships between injection force, sample viscosity, and testing conditions were elucidated using a mathematical model, which could be used in the future to assess and predict injection force of solution samples.

60 APPLIED LIFE SCIENCES↗

Prussian blue analogues as platform materials for understanding and developing oxygen evolution reaction electrocatalysts

Transition metal based materials containing Fe have drawn great attention as oxygen evolution reaction (OER) catalysts. The nature of the electrocatalytic active species remains under debate due to the ambiguous physicochemical properties of the catalyst materials, such as the oxidation states and crystal structures. Here, in order to address this issue, transition metal Prussian blue analogues (TM-PBA, Na(TM)(Fe)(CN) 6 , TM = V, Fe, Co, and Ni) with an isomorphous structure are investigated for OER catalysis. Our combined experimental measurements and density functional theory (DFT) calculations reveal that TM-PBAs exhibit volcano-like OER activity with Ni-PBA located near the top of the volcano. Such a volcano-like activity profile can be attributed to the distinctive binding energy difference between *O and *OH on different TM-PBAs surfaces. This research demonstrates that TM-PBAs can be used as platform materials for understanding structure-property-activity relationships in OER catalysts.

25 ENERGY STORAGE↗

Probing the relationship between bulk and local environments to understand impacts on electrocatalytic oxygen reduction reaction

Local catalyst environments fluctuate during electrochemical reactions which significantly influences reaction efficiency and selectivity. However, elucidating fundamental relationships between local environment and electrocatalytic performance is challenging due to the difficulty in probing this local region. Here, we study the impact of electrolyte composition on the kinetics and mechanism of the oxygen reduction reaction (ORR) for a carbon catalyst. Using a rotating ring-disk electrode equipped with an iridium oxide pH probe, we monitor changes in local pH during ORR. Additionally, we confirm that local pH changes significantly for near-neutral bulk pH and find that different cations provide variable pH-buffering, thereby modulating overall magnitude and onset of local pH changes. Overall, local pH more strongly dictates changes in mechanisms and performance, while the cation identity modulates local pH to influence these trends. This work highlights the importance relating local pH to electrocatalytic performance to further improve understanding of complex electrochemical processes

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the dynamic evolution of atomically dispersed Cu catalyst for CO 2 electrochemical conversion using integrated XANES analysis and mechanistic studies

Direct electrochemical conversion of CO 2 to ethanol (CH 3 CH 2 OH) offers a promising strategy to lower CO 2 emission while storing energy from renewable electricity. Our recent study reported a carbon-supported atomically dispersed Cu catalyst that achieved the highest reported selectivity for CH 3 CH 2 OH formation (91%) at a relatively low potential (-0.6 V), however, the active site structure that is responsible for such high activity and selectivity has yet to be understood. Here, in this paper, we demonstrate a computational investigation combining X-ray absorption near edge structure (XANES) simulations and a mechanistic study via density functional theory (DFT) to understand the catalyst structures of this Cu catalyst during electrocatalysis and the corresponding reaction mechanisms of the key products. An integrated computational and experimental XANES analysis depicted the dynamic evolution of the catalytic site during electrocatalysis. The as-prepared, atomically dispersed Cu catalyst aggregates and forms metallic clusters/nanoparticles under electrochemical condition, which then break down to smaller oxidized clusters after electrocatalysis. The formed Cu clusters/nanoparticles showed distinct catalytic activity and selectivity as a function of particle size based on the mechanistic investigation using DFT, which is consistent with experimental observations for catalyst samples with different Cu loadings. This comprehensive study which combines experimental and computational XANES investigation, mechanistic study via DFT calculations, and experimental performance of the catalysts, provides unprecedented dynamic and mechanistic insights into the supported atomically dispersed metal catalysts for CO 2 reduction. Such strategy and details gained can further guide discovery of novel catalyst materials for CO 2 electrochemical reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the effect of organic coatings on 4-nitrostyrene hydrogenation selectivity over Pt/TiO 2 catalysts

The hydrogenation of 4-nitrostyrene was investigated over Pt/TiO 2 catalysts to understand the effects of different catalyst coatings on product selectivity and reaction rates. This reaction is a much-investigated selectivity probe due to difficulty in controlling reactivity between the nitro and vinyl groups of 4-nitrostyrene, with C=C reduction generally being more favorable. 4-Nitrostyrene hydrogenation reactions were carried out in a batch reactor using uncoated, organothiol coated, phosphonic acid (PA) coated, and ion-conducting polymer (ionomer) coated catalysts. Thiols form dense coatings on Pt surfaces, whereas PAs preferentially accumulate on TiO 2 ; ionomer binding preference is unknown for this type of catalyst. The coating densities of the thiols and PAs were varied to observe the effects of loading on catalytic activity and reaction selectivity relative to the uncoated catalyst. Changes in selectivity were observed for catalysts with all coatings, with thiol coatings shifting selectivity towards the nitro reduction product, 4-vinylaniline (4-VA), and both ionomer and PA coatings shifting towards 4-ethylnitrobenzene, the olefin hydrogenation product. It was observed that selectivity toward 4-VA increased with thiol coating density, where 1,2-benzenedithiol (BDT) coated catalysts exhibited a selectivity of >99%. These changes were attributed to the identity of the adsorption sites blocked by the different coatings: blocking of metal sites via thiols decreased the rate of C=C hydrogenation, whereas blocking of TiO 2 sites by PAs decreased the rate of nitro group hydrogenation. The changes observed for ionomer and PA coatings suggested that ionomers, like PAs, bind preferentially to the metal oxide support rather than the active metal. This work provides new support to the proposal that nitro group hydrogenation preferentially occurs on TiO 2 sites after hydrogen spillover and underscores how selection of ligand functionality can be used to tune catalyst selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

What do physics-informed DeepONets learn? Understanding and improving training for scientific computing applications

Physics-informed deep operator networks (DeepONets) have emerged as a promising approach toward numerically approximating the solution of partial differential equations (PDEs). In this work, we aim to develop further understanding of what is being learned by physics-informed DeepONets by assessing the universality of the extracted basis functions and demonstrating their potential toward model reduction with spectral methods. Results provide clarity about measuring the performance of a physics-informed DeepONet through the decays of singular values and expansion coefficients. In addition, we propose a transfer learning approach for improving training for physics-informed DeepONets between parameters of the same PDE as well as across different, but related, PDEs where these models struggle to train well. This approach results in significant error reduction and learned basis functions that are more effective in representing the solution of a PDE.

Deep operator networks↗