Results for “Process integration” — Page 49

DOE OSTI2025

Thermal processing to modulate surface chemistry and bulk charge distribution in nickel-rich layered lithium positive electrodes

The broader application of nickel-rich layered oxides as positive electrode materials for lithium-ion batteries has been hindered by their high manufacturing cost and inferior cycling stability. Thermal processing, which is integral to electrode materials manufacturing and fundamental in materials science, has not been fully utilized to design advanced positive electrode materials. Herein, we demonstrate the capability of using quenching heat treatment to regulate Li distribution and modulate electronic structure near particle surface. The resulting materials exhibit less parasitic reactions with the electrolyte and an improved charge distribution homogeneity in secondary particles, leading to more stable cycling performance at high voltages (4.5 V vs Li/Li + ). Our synchrotron X-ray analyses reveal the underlying interplay between surface structure and bulk charge distribution in positive electrode materials particles. While strategies used to stabilize positive electrode materials through compositional control, surface modification, and electrolyte engineering have become mature, thermal processing can be advantageous to further improve positive electrode materials manufacturing.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Volatile Fatty Acid Recovery from Arrested Anaerobic Digestion for the Production of Sustainable Aviation Fuel: A Review

The process of producing sustainable aviation fuel (SAF) from organic waste involves the use of volatile fatty acids (VFAs) as intermediates that are obtained via arrested anaerobic digestion (AAD) and VFA recovery. This recovery process often requires several steps, including dewatering, filtration, extraction, and purification. The recovery of VFAs is crucial for their upgrading and can pose a challenge in the production of SAF from organic waste due to high costs and compatibility issues. This review discusses various dewatering methods, including centrifuges, belt filter presses, and screw presses, and explores conditioning technologies that can improve dewatering performance. It also introduces filtration technologies, with a focus on dynamic filtration, which shows promise in addressing the issue of membrane fouling. Additionally, the review describes extraction technologies such as electrodialysis, adsorption, and liquid–liquid extraction (LLE). By providing insights into these different techniques, the review aims to contribute to the development of an integrated VFA recovery process with low carbon footprint.

09 BIOMASS FUELS↗

DOE OSTI2025

Resonant metasurface‐enabled quantum light sources for single‐photon emission and entangled photon‐pair generation

Light encodes information in multiple degrees of freedom (e.g., frequency, amplitude, and phase), enabling high‐speed, high‐bandwidth communication through fiber optics. Unlike classical light, quantum light (single or entangled photons) can transmit quantum states over long distances without loss of coherence, thereby coherently interconnecting quantum nodes for distributed quantum entanglement. Quantum light sources are critical for developing scalable quantum networks aimed at distributed quantum computing, quantum teleportation, and secure quantum communications. However, existing quantum light sources suffer from limited integrability, insufficient spectral and spatial tunability, and inefficiencies in achieving mass‐produced, deterministic, on‐demand quantum light generation. These limitations significantly hinder progress toward direct, on‐chip integration with quantum processing units and detectors – an essential step toward scalable quantum networks. Resonant metasurfaces that leverage photonic modes – such as Mie resonances, guided‐mode resonances, or symmetry‐protected bound states in the continuum – offer strong spatial and temporal confinement of electromagnetic fields, characterized by high quality factors and small mode volumes. These metasurfaces greatly enhance linear and nonlinear light‐matter interactions, making them ideal for efficient on‐chip quantum light generation and manipulation. Here, we describe recent advances in nanoscale quantum light sources and quantum photonic state manipulation enabled by resonant metasurfaces. We also provide an outlook on next‐generation miniaturized quantum light sources achievable through materials innovations in quantum emitters, the co‐design of resonant metasurfaces, and ultimately, the heterogeneous integration of emerging layered van der Waals materials with resonant metasurfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Simulated moving bed-inspired method for continuous adsorptive denitrogenation of model fuel

Efficient, continuous routes for removing nitrogen-containing compounds from hydrothermal liquefaction-derived synthetic aviation fuel are needed to enable direct blending with conventional jet fuels. Here, we report a simulated moving bed-inspired process for adsorptive denitrogenation of a model fuel. Unlike conventional simulated moving bed systems, which are designed for sharp separations between similar solutes, this approach was run deliberately outside the classical separation region so that both pyridine and indole were removed together from the hydrocarbon stream. Alcohol solvents were used to regenerate the silica adsorbent, maintaining performance over extended operation and avoiding the downtime and energy demand associated with calcination. Under these conditions, the system demonstrates removal of more than 98% of nitrogen while cutting solvent use by 28% compared to batch operation. Classical modeling tools predicted column concentration profiles even in this nontraditional regime, suggesting a straightforward path to scaling. Together, these results motivate solvent-efficient, continuous denitrogenation strategies that could be integrated with biorefinery processes.

Adsorption↗

DOE OSTI2023

Towards On-Chip Learning for Low Latency Reasoning with End-to-End Synthesis

The Software Defined Architectures (SODA) Synthesizer is an open-source compiler-based tool able to automatically generate domain-specialized systems targeting Application-Specific Integrated Circuits (ASICs) or Field Programmable Gate Arrays (FPGAs) starting from high-level programming. SODA is composed of a frontend, SODA-OPT, which leverages the multilevel intermediate representation (MLIR) framework to interface with productive programming tools (e.g., machine learning frame-works), identify kernels suitable for acceleration, and perform high-level optimizations, and of a state-of-the-art high-level synthesis backend, Bambu from the PandA framework, to generate custom accelerators. One specific application of the SODA Synthesizer is the generation of accelerators to enable ultra-low latency inference and control on autonomous systems for scientific discovery (e.g., electron microscopes, sensors in particle accelerators, etc.). This paper provides an overview of the flow in the context of the generation of accelerators for edge processing to be integrated in transmission electron microscopy (TEM) devices, focusing on use cases from precision material synthesis. We show the tool in action with an example of design space exploration for inference on reconfigurable devices with a conventional deep neural network model (LeNet). Finally, we discuss the research directions and opportunities enabled by SODA in the area of autonomous control for scientific experimental workflows.

Castellana, Vito G.↗

DOE OSTI2016

IOTA : integration optimization, triage and analysis tool for the processing of XFEL diffraction images

Serial femtosecond crystallography (SFX) uses an X-ray free-electron laser to extract diffraction data from crystals not amenable to conventional X-ray light sources owing to their small size or radiation sensitivity. However, a limitation of SFX is the high variability of the diffraction images that are obtained. As a result, it is often difficult to determine optimal indexing and integration parameters for the individual diffraction images. Presented here is a software package, called IOTA , which uses a grid-search technique to determine optimal spot-finding parameters that can in turn affect the success of indexing and the quality of integration on an image-by-image basis. Integration results can be filtered using a priori information about the Bravais lattice and unit-cell dimensions and analyzed for unit-cell isomorphism, facilitating an improvement in subsequent data-processing steps.

Chemistry↗

DOE OSTI2016

Toward a Mechanistic Source Term in Advanced Reactors: Characterization of Radionuclide Transport and Retention in a Sodium Cooled Fast Reactor

A vital component of the U.S. reactor licensing process is an integrated safety analysis in which a source term representing the release of radionuclides during normal operation and accident sequences is analyzed. Historically, source term analyses have utilized bounding, deterministic assumptions regarding radionuclide release. However, advancements in technical capabilities and the knowledge state have enabled the development of more realistic and best-estimate retention and release models such that a mechanistic source term assessment can be expected to be a required component of future licensing of advanced reactors. Recently, as part of a Regulatory Technology Development Plan effort for sodium cooled fast reactors (SFRs), Argonne National Laboratory has investigated the current state of knowledge of potential source terms in an SFR via an extensive review of previous domestic experiments, accidents, and operation. As part of this work, the significant sources and transport processes of radionuclides in an SFR have been identified and characterized. This effort examines all stages of release and source term evolution, beginning with release from the fuel pin and ending with retention in containment. Radionuclide sources considered in this effort include releases originating both in-vessel (e.g. in-core fuel, primary sodium, cover gas cleanup system, etc.) and ex-vessel (e.g. spent fuel storage, handling, and movement). Releases resulting from a primary sodium fire are also considered as a potential source. For each release group, dominant transport phenomena are identified and qualitatively discussed. The key product of this effort was the development of concise, inclusive diagrams that illustrate the release and retention mechanisms at a high level, where unique schematics have been developed for in-vessel, ex-vessel and sodium fire releases. This review effort has also found that despite the substantial range of phenomena affecting radionuclide release, the current state of knowledge is extensive, and in most areas may be sufficient. Several knowledge gaps were identified, such as uncertainty in release from molten fuel and availability of thermodynamic data for lanthanides and actinides in liquid sodium. However, the overall findings suggest that high retention rates can be expected within the fuel and primary sodium for all radionuclides other than noble gases.

Brunett, Acacia J.↗

DOE OSTI2024

Controlling the helicity of light by electrical magnetization switching

Controlling the intensity of emitted light and charge current is the basis of transferring and processing information. By contrast, robust information storage and magnetic random-access memories are implemented using the spin of the carrier and the associated magnetization in ferromagnets. In this study, the missing link between the respective disciplines of photonics, electronics and spintronics is to modulate the circular polarization of the emitted light, rather than its intensity, by electrically controlled magnetization. Here we demonstrate that this missing link is established at room temperature and zero applied magnetic field in light-emitting diodes through the transfer of angular momentum between photons, electrons and ferromagnets. With spin-orbit torque a charge current generates also a spin current to electrically switch the magnetization. This switching determines the spin orientation of injected carriers into semiconductors, in which the transfer of angular momentum from the electron spin to photon controls the circular polarization of the emitted light. The spin-photon conversion with the nonvolatile control of magnetization opens paths to seamlessly integrate information transfer, processing and storage. Our results provide substantial advances towards electrically controlled ultrafast modulation of circular polarization and spin injection with magnetization dynamics for the next-generation information and communication technology, including space-light data transfer. The same operating principle in scaled-down structures or using two-dimensional materials will enable transformative opportunities for quantum information processing with spin-controlled single-photon sources, as well as for implementing spin-dependent time-resolved spectroscopies.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Optimizing the Operational Parameters of an Electrochemical Purification Cell for Corrosion Mitigation in CSP Plants During Operation: Preprint

To make concentrating solar power (CSP) cost-competitive, the next generation of CSP plants will increase efficiency by operating at a higher temperature, which will require a new thermal energy storage material. One option for the thermal energy storage material is a ternary chloride salt that is stable at the temperatures required, but reacts easily with the atmosphere to form MgOHCl, a corrosive impurity. If left unchecked, this impurity will corrode the containment alloys, potentially leading to dangerous spills. We are working to design an electrochemical purification cell to remove MgOHCl from the molten chloride salt during CSP plant operation. In this paper, we use predictive modeling to assess the rate at which purification must occur. Additionally, we analyze possible process flow pathways for the molten chloride salts. Ultimately, we determine that implementation of a single reactor through which all chloride salts flow is the most efficient design to reduce impurity concentration below 0.1 mol % impurity.

concentrating solar power↗

DOE OSTI2016

Integrated oil production and upgrading using molten alkali metal

A method that combines the oil retorting process (or other process needed to obtain/extract heavy oil or bitumen) with the process for upgrading these materials using sodium or other alkali metals. Specifically, the shale gas or other gases that are obtained from the retorting/extraction process may be introduced into the upgrading reactor and used to upgrade the oil feedstock. Also, the solid materials obtained from the reactor may be used as a fuel source, thereby providing the heat necessary for the retorting/extraction process. Other forms of integration are also disclosed.

02 PETROLEUM↗

DOE OSTI2023

Integration of a Smart Outlet-Based Plug Load Management System with a Building Automation System

The growth of and reliance on renewable energy necessitate a multi-pronged approach to achieve grid reliability and economics. As they represent a notable portion of U.S. energy consumption, commercial buildings must play an active role in this effort. Conserving energy and responding to grid conditions through demand flexibility can be achieved through the integration of major building systems. Integration of plug and process loads with lighting and heating, ventilation, and air conditioning systems maximizes the effectiveness of integrated building energy management. In this research, we demonstrate the integration of smart outlets into a building automation system. We cover the installation process as well as the architecture required for smart outlets to communicate data to the building automation system and to receive commands back. After recording power measurements for one week as a baseline, we configured the building automation system to turn the smart outlets on and off according to a set schedule. This resulted in energy savings of 66% during 1 week on 25 plug loads. This work demonstrates that grid-interactive efficient buildings are achievable through building system integration.

building automation system↗

DOE OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗

DOE OSTI2015

Modeling biomass gasification system using multistep kinetics under various oxygen–steam conditions

Biomass gasification is an effective method to convert low‐value lingocellulosic biomass into useful gas products. The ability to predict the gas composition is important to process design. In this study, simulations of biomass gasification were carried out for various feedstocks at different operating conditions, and the model results were validated using experimental data. A multistep kinetics model was developed to predict the syngas composition using different biomass feedstocks under various oxygen‐enriched air and steam conditions. The oxygen level in the gasifying agent ranged from 21% (air) to 45% (pure oxygen). Five different biomass materials were used, including pine, maple–oak mixture, seed corn, corn stover, and switchgrass. The fluidized bed gasifier was maintained at 800°C. The present kinetics model was able to predict the concentrations of H 2 , CO, CO 2 , H 2 O, CH 4 , and N 2 in the syngas, and the predicted compositions were in good agreement with the experimental data. The results show that the model was sensitive to the variation in the oxygen level, steam flow rate, and the composition of the biomass material. As the oxygen level increased, the model also predicted the increase in H 2 , CO, CH 4 , and the H 2 /CO ratio. The mechanism on improving the syngas quality was also explained by analyzing the reaction equations. The increase in hydrogen is believed to be due to the use of steam for gasification. The present model can further be integrated into the process simulation model for predicting the performance of a biorefinery to help utilize biomass energy. © 2015 American Institute of Chemical Engineers Environ Prog, 34: 1148–1155, 2015

Banerjee, Sudhanya↗

DOE OSTI2020

Predicting Biological Cleanliness: An Empirical Bayes Approach for Spacecraft Bioburden Accounting

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Bayesian Framework for Bioburden Density Estimation in Planetary Protection

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A Review of Water and Climate Change Analysis in Electric Utility Integrated Resource Planning

The purpose of this paper is to examine the extent to which electric utility integrated resource plans (IRPs) evaluate the impact of water constraints on electric generation resource portfolios and the extent to which IRPs consider the impacts of climate change to generation and loads. This white paper reviewed 30 IRPs to determine best practices with respect to analyzing and reporting on potential water-based and climate change risks within the integrated resource planning process. Best practices from electric utility IRPs are identified and additional recommendations and considerations are put forth. In recent years, thermal generating facilities have experienced challenges with water availability: a shortage of cooling water, conditions in which incoming cooling water is too warm for optimal operation, and/or water discharge temperatures exceeding permit limits. S&P Global Market Intelligence recently reported on a study that identified for the year 2030, 98.2 gigawatts (GW) of coal capacity at risk due to water stress. Climate change effects on hydrological cycles may adjust the timing, temperature, and volume of water availability for thermal electric cooling and for hydropower generation, which could further exacerbate the frequency and duration of operational constraints. Climate change can also impact the timing and intensity of electric loads that utilities must serve, most notably for heating and cooling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

Facile integration of low-cost black phosphorus in solution-processed organic solar cells with improved fill factor and device efficiency

Black phosphorus (BP) as a promising two-dimensional (2D) material has gained great attention in nanoelectronic devices because of its intrinsic semiconductor characteristics. However, the poor material availability and solution processability have been major roadblocks that hinder its wider application in microelectronics. Herein, readily available, lost-cost BP was utilized as an effective component that was integrated via a facile solution process for the fabrication of bulk heterojunction organic solar cells (OSCs). An impressive fill factor (FF) of 74.2% and power conversion efficiency (PCE) of 10.5% were realized in the OSCs incorporating 10 wt% of BP in the active layer of the benchmark polymer donor PTB7-Th and PC71BM acceptor, corresponding to a 20% PCE enhancement compared to the BP-free binary devices. The efficiency enhancement can be attributed to BP's high hole carrier mobility that facilitates better carrier extraction and suppression of the recombination. BP has been further demonstrated to be effective in additional solar cells based on other photovoltaic (PV) materials, including non-fullerene OSCs. The successful incorporation of the inexpensive BP in the solution-based fabrication of OSCs opens the door for its application in high performance, low cost flexible electronics.

14 SOLAR ENERGY↗

DOE OSTI2026

A Robotic High-Throughput Grid-Search Platform for Mapping Phase Behavior in Triblock Copolymer–Homopolymer Blends

We present a high-throughput experimental investigation of the phase behavior in triblock copolymers (PS-b-PB-b-PS and PS-b-PI-b-PS) and polystyrene (PS) homopolymer blends as a function of homopolymer molecular weight (MW) and blend ratio. Using a robotic thin-film processing platform (NOVA) integrated with Grazing Incidence Small-Angle X-ray Scattering (GISAXS) and Atomic Force Microscopy (AFM), we systematically mapped the order–disorder transition (ODT) boundaries and domain spacing evolution across a broad MW range (4.0–101.3 kDa) with varying homopolymer loadings (10% to 90%). The results reveal three distinct regimes: low-MW homopolymers, corresponding to the wet-brush regime produced only gradual domain swelling before disordering at high blend ratios (weight fraction); medium-MW homopolymers, corresponding to thedry-brush regime induced significant domain spacing increase up to 80% followed by earlier disordering, while high-MW homopolymers led to macrophase separation with minimal changes in domain spacing. Additionally, coarse-grained molecular dynamics simulations confirmed our experimental finding that in the low-MW region, the PS homopolymer uniformly distributed in the PS domain. These findings demonstrate that homopolymer molecular weight critically governs both the extent of domain swelling and the onset of disorder in triblock copolymer systems. This high-throughput platform enables the rapid mapping of composition–morphology relationships and can be integrated with AI/ML tools for designing next-generation nanostructured polymers.

36 MATERIALS SCIENCE↗