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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Wettability Alteration with Weak Acid-Assisted Surfactant Flood

Oil-wetness and heterogeneity are two key reasons for low oil recovery by waterflooding in carbonate reservoirs. Surfactants have been effective in altering the oil-wet matrix to a more water-wet condition and initiating spontaneous imbibition. Because it takes time for the surfactant to alter wettability, oil recovery from the tight matrix is slow and sometimes not economically feasible. Acids have the potential of dissolving minerals, which may alter wettability. In this study, the enhanced oil recovery (EOR) performance of an acid-assisted surfactant solution, a novel technique, was evaluated for low-temperature applications. A set of acids and their acetates were tested. Bulk rock-acid reaction, wettability alteration (WA) tests, and spontaneous imbibition measurements were conducted at reservoir temperature (35°C) to identify effective candidates. Coreflood tests were then performed to evaluate the selected acid-surfactant formulations. Before and after a coreflood test, the core was scanned using micro-computed tomography (CT) to investigate pore structure alteration. Bulk reaction measurements showed that weak acids, especially acetic acid (AA), have the desired low reaction rates at 35°C. WA tests showed that AA can remove the crude oil off the rock surface and alter wettability through mineral dissolution. The surfactant can reduce contact angles from 160° to 58°; adding acid into the surfactant can further reduce it to 52°. Spontaneous imbibition experiments showed the synergy between the acid and the surfactant; the AA-surfactant solution had the highest oil recovery (62.6%) among acid-surfactant formulations. The acid improves the WA efficiency by the surfactant through surface mineral dissolution and lower ζ-potential. The imbibition transports the acid-surfactant solutions into the matrix, which minimizes face dissolution. Coreflood tests show that the AA-surfactant flood can increase the oil recovery rate and recover about 8% more oil compared to the surfactant flood. Micro-CT showed that a few mineral particles were transported along the core and partially plugged pore throats, which reduced permeability and diverted flow leading to improved oil recovery. Here, the transport of the acid in reservoirs and the potential plugging issues have to be carefully evaluated in future studies.

58 GEOSCIENCES↗
DOE OSTI2019

High Thermal Conductivity Resin Systems for High Energy Physics Magnets

In Nb3Sn superconducting magnets, the cable and insulation system dominate the behavior of a completed magnet, with contributions to the mechanical behavior from the stiff, brittle components of the superconductor, the soft annealed copper stabilizer, and the properties of the composite insulation system. As these components are closely integrated on a small scale, it is of value to explore the properties of the entire system at a larger scale, to enable practical magnet design. Subscale composite testing (Stack Testing) has been used extensively to study the bulk material properties of the magnet composite structure. Small samples that mimic the fabrication process of magnets are fabricated and tested to qualify and characterize magnet insulation systems for use in future magnet projects as well as to better inform magnet designers about means for assembly and general handling processes. Subscale composite samples will be fabricated and characterized using various novel resins to work to improve magnet performance. New resin systems will be screened to allow for down selection to one or more highly promising resin systems. The work performed under this agreement at Fermilab will feed via CTD into the fabrication of subscale magnets at Lawrence Berkeley National Laboratory (LBNL) for verification of magnet performance.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Doping Metallic Grain Boundaries to Control Atomic Structure and Damage Tolerance

Grain boundaries often act as sites for crack and void nucleation during plastic deformation of metallic materials. While it is known that grain boundary character and structure can greatly influence this damage nucleation process, the current level of control over such details is limited. The objective of this project was to obtain a fundamental understanding of how metallic grain boundary structure can be controlled through intelligent doping, with the idea of inducing planned amorphous grain boundary phases or complexions. The effect of amorphous complexion structure on dislocation accommodation mechanisms was studied, to improve the field’s understanding of damage nucleation at a promising type of interface. Different microstructural descriptors were studied, as grain boundaries can have large variations and complexity of local structure, and influence the mechanical damage resistance of these features was tested. Nanocrystalline systems that contain amorphous grain boundary complexions were prioritized, as these have more extreme variations in interfacial structure and damage tolerance, with an emphasis on isolating the importance of complexion population (type, thickness, etc.), network topology, local structure, and local chemistry. This research used a combination of computational, experimental, and characterization techniques to isolate and understand the importance of nanoscale grain boundary structure and interfacial chemistry. Amorphous grain boundary complexions were found to clearly increase a material’s resistance to mechanical damage, with the local distribution of structural short-range order within the complexions found to be an important descriptor for damage and the proposed focus of future work in this area.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tagged deep inelastic scattering measurement on deuterium with the LAD experiment

Here, the origin of the modification of the quark structure of nucleons in the nuclear medium can be tested with tagged recoil nucleon measurements from deep inelastic scattering off electrons on deuterium. The LAD experiment at the Thomas Jefferson National Laboratory (JLab) will measure the modification of the neutron structure function for high-momentum, highly-virtual neutrons by measuring the spectator recoil protons in coincidence with the scattered electron. An update on the experimental setup and projected results is presented. The experiment will collect data in Fall 2024.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Effect of compensatory immigration on the genetic structure of coyotes

Despite efforts to reduce their impacts on livestock and native ungulates within the southeastern United States, coyotes (Canis latrans) are able to recover from control programs. It is unknown how coyotes compensate for high mortality following trapping, so there is great interest to identify methods that can provide insight into coyote response to intensive trapping. To investigate if population genetic tools can decipher how coyotes recover from intensive trapping, we combined an empirical test of how genetic differentiation, diversity, and familial structure changed following trapping on the Savannah River Site (SRS), South Carolina with spatially explicit genetic simulations.The empirical dataset found that pre- and post-trapping periods had similar genetic diversities and were not genetically differentiated as expected by either compensatory reproduction or immigration from a single genetic source. The post-trapping coyote populations exhibited weaker signatures of philopatry with little evidence for increased dispersal distances of young coyotes, which suggests immigration caused a decrease in familial structure. Our simulations indicated that spatial autocorrelation coefficients and observed heterozygosities change as immigration increases while population differentiation, allelic richness, and displacement distances do not. Collectively, our results suggest that coyotes recover from intensive trapping via both reproduction and immigration, which likely makes preventing compensation difficult. Furthermore, monitoring post-trapping populations may offer more insight into maximizing the effectiveness of control efforts, and based on our simulations, population genetics can provide critical information about the amount of compensatory immigration following trapping.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

COZMIC. III. Cosmological Zoom-in Simulations of Self-interacting Dark Matter with Suppressed Initial Conditions

We present eight cosmological dark matter (DM)-only zoom-in simulations of a Milky Way–like system that include suppression of the linear matter power spectrum P(k), and/or velocity-dependent DM self-interactions, as the third installment of the COZMIC suite. We consider a model featuring a massive dark photon that mediates DM self-interactions and decays into massless dark fermions. The dark photon and dark fermions suppress linear matter perturbations, resulting in dark acoustic oscillations in P(k), which ultimately affect dwarf galaxy scales. The model also features a velocity-dependent elastic self-interaction between DM particles (SIDM), with a cross section that can alleviate small-scale structure anomalies. For the first time, our simulations test the impact of P(k) suppression on gravothermal evolution in an SIDM scenario that leads to core collapse in (sub)halos with present-day virial masses below ≈10 9 M ⊙ . In simulations with P(k) suppression and self-interactions, the lack of low-mass (sub)halos and the delayed growth of structure reduce the fraction of core-collapsed systems relative to SIDM simulations without P(k) suppression. In particular, P(k) suppression that saturates current warm DM constraints almost entirely erases core collapse in isolated halos. Models with less extreme P(k) suppression produce core collapse in ≈20% of subhalos and ≈5% of isolated halos above 10 8 M ⊙ , and also increase the abundance of extremely low-concentration isolated low-mass halos relative to SIDM. These results reveal a complex interplay between early and late-Universe DM physics, revealing new discovery scenarios in the context of upcoming small-scale structure measurements.

dark matter↗
DOE OSTI2025

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗
DOE OSTI2025

What drives embodied carbon policy? A global perspective on adoption

Abstract Embodied carbon refers to the greenhouse gas emission associated with the lifecycle of buildings. Embodied carbon policies are critical for addressing the environmental impact of construction materials and advancing climate goals. Despite their importance, the adoption of embodied carbon policies has been limited globally, influenced by economic, environmental, institutional, and trade factors. This study employs structural equation modeling to analyze 37 countries, testing ten hypotheses across four categorical factors. The base model reveals the significant influence of environmental vulnerability and institutional frameworks on policy adoption, while robustness models confirm the critical role of trade dependencies and economic competitiveness in shaping national embodied carbon strategies. Findings underscore that countries with high climate vulnerability and strong institutional support are more likely to adopt embodied carbon policies. Conversely, trade-reliant nations face challenges balancing competitiveness and sustainability. Policy implications suggest the need for international collaboration to align trade policies with carbon reduction goals, targeted support for vulnerable nations, and the integration of embodied carbon considerations into existing climate frameworks. These results offer a roadmap for policymakers to design more effective and equitable embodied carbon policies, fostering global progress toward sustainable construction and decarbonization.

Hu, Ming (ORCID:0000000325831161)↗
DOE OSTI2018

The Role of Wheel Surface Quality on Structural and Hard Magnetic Properties of Nd–Fe–B Permanent Magnet Powders

Rapidly solidified Nd{sub 15}Fe{sub 77}B{sub 8} magnetic alloy powders have been produced by using melt-spinning method. Different wheel surface structures such as smooth and textured were tested to investigate the effect of wheel surface morphology on powder shape, microstructure, Curie temperature, and magnetic properties. Produced powders were subjected to surfactant-active ball-milling process for powder size reduction and to enhance magnetic and thermal properties. Generally, flaky-shaped powders were obtained with smooth surface wheels and spherical-shaped powders were produced with textured surface wheel. Microstructure of flaky-shaped powders consisted of polygonal fine equiaxed grains with an average grain size of 0.45 µm. Spherical-shaped powders had dendritic microstructure regardless of their sizes. Both flaky and spherical powders involved hard magnetic Nd{sub 2}Fe{sub 14}B phase located in the grain interior and a fine network of Nd-rich phase at the grain boundaries. Surfactant-active ball-milling process significantly contributed to magnetic and thermal properties of powders. The coercivity values of flaky-shaped powders milled for 90, 150, 210, 270, 330, and 390 min milling times were substantially higher than that of spherical-shaped powders milled for the same period of times. The Curie temperatures of Nd{sub 15}Fe{sub 77}B{sub 8} ingot alloy and spherical- and flaky-shaped powders were found as 279, 305, and 321 {sup ∘}C, respectively. On the other hand, the Curie temperatures of flaky- and spherical-shaped powders milled for 390 min were measured as 331 and 311 {sup ∘}C, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Synthesis and Characterization of Hydrophobic Fe{sub 3}O{sub 4} Magnetic Nanoparticles with High Saturation Magnetization

A simple one-step solvothermal method is proposed to prepare hydrophobic Fe{sub 3}O{sub 4} nanoparticles (MNPs) using iron acetylacetonate (Fe(acac){sub 3}), oleylamine (OAm), and ethylene glycol (EG). X-ray powder diffraction, scanning electron microscope, infrared spectroscopy, transmission electron microscopy, X-ray photoelectron spectrometry, and vibrating sample magnetometer are used to characterize the structure, morphology, and properties of products. The testing results indicate that the as-synthesized products are spherical-like hydrophobic MNPs, superparamagnetic at room temperature, with a saturation magnetization up to 76.8 emu/g. The good hydrophobic property of MNPs is attributed to the coverage of oleylamine, without causing a remarkable loss of magnetic property. In addition, the influences of material ratio, aging time, oleic acid, and stearic acid used as additives are studied in our research.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Plug-in electric vehicles in China and the USA: a technology and market comparison

As the top two plug-in electric vehicle (PEV) markets in the world, China and the United States of America (USA) have developed different market structures that are influenced by government policies, test procedures, customer acceptance, and vehicle performance. There are differences in PEV test procedures and vehicle class definitions as well. This paper quantifies such differences and compares PEV characteristics and markets in the two countries using actual data collected over several years. First, although China surpasses the USA in annual PEV production because of generous PEV policies and higher charging infrastructure availability, the USA has a higher PEV adoption rate per capita (2.3 versus 0.81 per 1000 people at the end of 2017). Second, the most popular vehicle classes are A00 battery electric vehicles (BEVs) in China but long-range mid-size BEVs in the USA. Moreover, China's electric and plug-in hybrid sport utility vehicle market is growing quickly. Third, the electricity consumption rated under Chinese test procedures is 20%-40% lower than that rated under US procedures. The sales-weighted electricity consumption of an average BEV in China is 23% lower than that in the USA because of larger proportions of small and micro BEVs in China. Fourth, PEV battery cost in the two countries is currently close to $210-$220 kWh. Finally, China has higher numbers of charging infrastructure, and the ratio of PEVs to public chargers is 9.0 in China versus 17.9 in the USA at the end of 2018.

China EV market↗
DOE OSTI2018

Mechanical Behavior of Commercially Pure Titanium Weldments at Lower Temperatures

Commercially pure titanium is used for low-temperature applications due to good toughness attributed to single-phase microstructure (α). Electron beam welding (EBW) and gas tungsten arc welding (GTAW) processes have been used for welding two grades of commercially pure titanium (Grade 2 and Grade 4). Martensitic microstructure is found to be finer in the case of EBW joint as compared to GTAW joint due to faster rate of cooling in the former process. Weldments have been characterized to study the mechanical behavior at ambient (298 K) and cryogenic temperatures (20 and 77 K). Strength of weldments increases with the decrease in temperature, which is found to be more prominent in case of Grade 4 titanium as compared to Grade 2. Weld efficiency of Grade 4 is found to be higher at all the temperatures (ambient, 77 and 20 K). However, ultimate tensile strength/yield strength ratio is higher for Grade 2 as compared to Grade 4. % Elongation is found to increase/retained at cryogenic temperatures for Grade 2, and it is found to decrease for Grade 4. Electron backscattered diffraction analysis and transmission electron microscopy of deformed samples confirmed the presence of extensive twinning in Grade 2 and the presence of finer martensitic structure in Grade 4. Fractography analysis of tested specimens revealed the presence of cleavage facets in Grade 4 and dimples in specimens of Grade 2. Higher strength in Grade 4 is attributed to higher oxygen restricting the twin-assisted slip, which is otherwise prominent in Grade 2 titanium.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Understanding the microstructural evolution of hypersaline cemented paste backfill with low-field NMR relaxation

Highlights: • Microstructural evolution of CPB, prepared with tap and hypersaline water, is monitored using low-field NMR relaxometry. • T{sub 1} and T{sub 2} NMR relaxation measurements compared with mechanical strength via UCS tests • Hypersaline mixing water results in slower structural evolution and lower mechanical strength. Cemented paste backfill (CPB) comprising mineral tailings, binders and mixing water is an important potential support material in the mining industry. As the mechanical properties of CPB are significantly influenced by its microstructural characteristics the development of measurement tools to better understand its pore structure evolution is important for its increased utilisation. This study reports the application of low-field nuclear magnetic resonance (NMR) relaxation time measurements to characterise the microstructural evolution of CPB materials over 56 days of hydration, contrasting common tap water and hypersaline water (~22 wt% salt) as mixing water. Distinct NMR relaxation time populations were evidenced within each CPB sample, revealing the presence of both capillary (T{sub 1,2} ≈ 10 ms) and gel pore water (T{sub 1,2} ≈ 300–500 μs), with time-dependent relaxation measurements facilitating characterisation of capillary pore structure evolution over the hydration period assessed. Hypersaline samples demonstrated a time-lag in this measured capillary pore evolution, relative to those hydrated with tap water, while pore structure evolution rates were observed to increase with increased CPB binder content. Further, both T{sub 1} and T{sub 2} NMR relaxation times were found to correlate with the uniaxial compressive strength of the CPB materials investigated, facilitating the formulation of a predictive correlation function between NMR relaxation characteristics and mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Directed energy deposition of radially functionally graded nickel based superalloys IN625 and IN738: Microstructure and mechanical properties

This study investigates the microstructure and mechanical properties of radially functionally graded (RFG) materials fabricated from nickel-based superalloys IN625 and IN738 using directed energy deposition (DED). RFG cylindrical deposits with radial gradients of IN625-IN738 and IN738-IN625 were successfully fabricated and confirmed to be crack-free through tailored composition grading, scan strategy and process parameters that minimized thermal gradients and solidification velocities. Microstructural analysis revealed distinct variations across the gradient, characterized by differences in dendrite arm spacing, microsegregation, and the formation of distinct γ' precipitates and carbide/boride phases (MC, M 6 C, M 2 C, and MB 2 ) in as-deposited (AD) conditions, which evolved into M 23 C 6 and M 2 B upon subsequent heat treatment (HT). EBSD showed predominant columnar grains with a [100] texture, while microhardness profiles demonstrated consistent variation across the gradients. Mechanical testing highlighted the synergy of the graded structure, combining IN738's strength with IN625's ductility, resulting in enhanced properties such as a yield strength of 1131 MPa, ultimate tensile strength of 1382 MPa, and elongation of 12 % for HT IN625-IN738 grading. Numerical simulations employing CALPHAD thermodynamic calculations and finite element thermal modeling are used to establish phase evolution and microstructural feature correlation with thermal profiles, aiding in the optimization of process-structure-property relationship.

Additive manufacturing↗
DOE OSTI2026

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Facile polymerization in a bicellar template to produce polymer nano-rings

We report a well-defined discoidal bicelle composed of three lipids, specifically zwitterionic long-chain 1,2-dipalmitoyl phosphocholine (DPPC) and short-chain 1,2-dihexanoyl phosphocholine (DHPC) doped with anionic 1,2-dipalmitoyl phosphoglycerol (DPPG) provides a generalized template for the synthesis of hydrophobic polymer nano-rings. The lipid molar ratio of DPPC/DHPC/DPPG is 0.71/0.25/0.04. The detailed investigation and discussion were based on styrene but tested on three other vinyl monomers. The structure of nano-rings is identified through the detailed analysis of small angle X-ray/neutron scattering (SAXS and SANS) data and transmission electron micrographs (TEM), supported by the differential scanning calorimetric (DSC) data before and after polymerization. The investigation covers samples with a styrene-to-lipid ratio ranged varied from 1:50 to 1:10.The styrene monomers are initially located at both the discoidal planar (long-chain lipid rich) and rim (short-chain lipid rich) regions. During polymerization, they migrate to the more fluid rim region-section. The formation mechanism involves the interplay of hydrophobic interaction, mismatched miscibility of polystyrene between the ordered and disordered phases, and crystallinity of the long lipid acyl chains. This facile synthesis is proven applicable for several hydrophobic monomers. The well-defined nano-rings greatly enhance the interfacial area and have the potential to be the building blocks for functional materials, if monomers are incorporated with desirable functions, for future applications. Crosslinked polymer nano-rings are produced in well-defined discoidal bicelles. The enhanced immiscibility in the planar region drives the hydrophobic polymers to the fluidic rim. The platform can be generalized for synthesis of other hydrophobic polymer nano-rings.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Tuning Inner-Ear Tip-Link Affinity Through Alternatively Spliced Variants of Protocadherin-15

Human hearing relies upon the tip-to-tip interaction of two nonclassical cadherins, protocadherin-15 (PCDH15) and cadherin-23 (CDH23). Together, these proteins form a filament called the tip link that connects neighboring stereocilia of mechanosensitive hair cells. As sound waves enter the cochlea, the stereocilia deflect and tension is applied to the tip link, opening nearby transduction channels. Disruption of the tip link by loud sound or calcium chelators eliminates transduction currents and illustrates that tip-link integrity is critical for mechanosensing. Tip-link remodeling after disruption is a dynamic process, which can lead to the formation of atypical complexes that incorporate alternatively spliced variants of PCDH15. These variants are categorized into six groups (N1–N6) based upon differences in the first two extracellular cadherin (EC) repeats. Here, we characterized the two N-terminal EC repeats of all PCDH15 variants (pcdh15(N1) to pcdh15(N6)) and combined these variants to test complex formation. We solved the crystal structure of a new complex composed of CDH23 EC1-2 (cdh23) and pcdh15(N2) at 2.3 Å resolution and compared it to the canonical cdh23–pcdh15(N1) complex. While there were subtle structural differences, the binding affinity between cdh23 and pcdh15(N2) is ~6 times weaker than cdh23 and pcdh15(N1) as determined by surface plasmon resonance analysis. Steered molecular dynamics simulations predict that the unbinding force of the cdh23–pcdh15(N2) complex can be lower than the canonical tip link. Our results demonstrate that alternative heterophilic tip-link structures form stable protein–protein interactions in vitro and suggest that homophilic PCDH15–PCDH15 tip links form through the interaction of additional EC repeats.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis

Molecular design is a critical aspect of various scientific and industrial fields, where the properties of molecules hold significant importance. In this study, a 3-fold methodology design is presented that leverages the power of generative artificial intelligence (AI), predictive modeling, and reinforcement learning to create tailored molecules with desired properties. This model synergistically combines deep learning techniques with Self-Referencing Embedded Strings (SELFIES) molecular representation to build a generative model that generates valid molecules and a graphical neural network model that accurately forecasts molecular properties. The Variational Autoencoder (VAE) coupled with reinforcement learning helps refine molecule generation based on targeted attributes. Data from an experimental study involving surfactants were used to test the framework. A validation of the structural integrity of the molecules generated was conducted, and Tanimoto similarities were used to quantify the similarity and diversity between the original and generated molecular structures. Also, saliency maps for the generated surfactants were produced to identify the features explaining the property values. Lastly, molecular dynamics simulations were used to validate the stability of the generated molecules. The results showed that the proposed framework can effectively produce valid molecules within the set property threshold value.

36 MATERIALS SCIENCE↗