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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

genomeocean: a pretrained microbial genome foundational model (genomeoceanLLM) v1.0

We present Genomeocean, a foundational genome language model that represents the microbial genome sequences from complex environmental samples. By training on a large, diverse metagenomic dataset, Genomeocean learns species-specific sequence composition and can generate long, realistic open reading frames (ORFs). Our model employs a Byte-pair-encoding (BPE) tokenization strategy, allowing it to efficiently process large genomic datasets and generate long sequences up to 50kb. We demonstrate that fine-tuning Genomeocean can generate novel gene clusters encoding biosynthetic pathways, showcasing its ability to model both fundamental and complex biological processes. Our work establishes Genomeocean as a powerful tool for understanding microbial genome biology and paves the way for its application in a range of fields, from synthetic biology to microbiome research.

Wang, Zhong [Lawrence Berkeley National Laboratory↗
DOE OSTI2024

Catalytically Active Site Mapping Realized through Energy Transfer Modeling

Abstract The demands of a sustainable chemical industry are a driving force for the development of heterogeneous catalytic platforms exhibiting facile catalyst recovery, recycling, and resilience to diverse reaction conditions. Homogeneous‐to‐heterogeneous catalyst transitions can be realized through the integration of efficient homogeneous catalysts within porous matrices. Herein, we offer a versatile approach to understanding how guest distribution and evolution impact the catalytic performance of heterogeneous host–guest catalytic platforms by implementing the resonance energy transfer (RET) concept using fluorescent model systems mimicking the steric constraints of targeted catalysts. Using the RET‐based methodology, we mapped condition‐dependent guest (re)distribution within a porous support on the example of modular matrices such as metal–organic frameworks (MOFs). Furthermore, we correlate RET results performed on the model systems with the catalytic performance of two MOF‐encapsulated catalysts used to promote CO 2 hydrogenation and ring‐closing metathesis. Guests are incorporated using aperture‐opening encapsulation, and catalyst redistribution is not observed under practical reaction conditions, showcasing a pathway to advance catalyst recyclability in the case of host–guest platforms. These studies represent the first generalizable approach for mapping the guest distribution in heterogeneous host–guest catalytic systems, providing a foundation for predicting and tailoring the performance of catalysts integrated into various porous supports.

Thompson, William J.↗
DOE OSTI2024

Catalytically Active Site Mapping Realized through Energy Transfer Modeling

Abstract The demands of a sustainable chemical industry are a driving force for the development of heterogeneous catalytic platforms exhibiting facile catalyst recovery, recycling, and resilience to diverse reaction conditions. Homogeneous‐to‐heterogeneous catalyst transitions can be realized through the integration of efficient homogeneous catalysts within porous matrices. Herein, we offer a versatile approach to understanding how guest distribution and evolution impact the catalytic performance of heterogeneous host–guest catalytic platforms by implementing the resonance energy transfer (RET) concept using fluorescent model systems mimicking the steric constraints of targeted catalysts. Using the RET‐based methodology, we mapped condition‐dependent guest (re)distribution within a porous support on the example of modular matrices such as metal–organic frameworks (MOFs). Furthermore, we correlate RET results performed on the model systems with the catalytic performance of two MOF‐encapsulated catalysts used to promote CO 2 hydrogenation and ring‐closing metathesis. Guests are incorporated using aperture‐opening encapsulation, and catalyst redistribution is not observed under practical reaction conditions, showcasing a pathway to advance catalyst recyclability in the case of host–guest platforms. These studies represent the first generalizable approach for mapping the guest distribution in heterogeneous host–guest catalytic systems, providing a foundation for predicting and tailoring the performance of catalysts integrated into various porous supports.

Thompson, William J.↗
DOE OSTI2024

Precision Structure Engineering of High-Entropy Oxides under Ambient Conditions

High-entropy oxides (HEOs) have unveiled a unique frontier in the realm of heterogeneous catalysis, taking advantage of the entropic effect and increased complexities to deliver ultrahigh stability and large tuning capability. However, current HEO synthesis mainly relies on high-temperature annealing approaches affording HEOs possessing no or low surface area, inferior active site exposure efficiency, and low controllability over the structure tuning. The grand challenge lies in producing high-quality HEO catalysts with high active site utilization efficiency, which relies on precision structure engineering, preferably under mild conditions. In this work, an in situ lattice engineering approach was developed to afford a supported HEO catalyst under ambient conditions. The HEO compositions (CuCoFeNiMnO x ) were uniformly integrated into the lattice of CeO 2 driven by cavitation-induced nucleation being generated via ultrasonication. The as-afforded catalysts were featured by high surface area, atomically dispersed HEO compositions, active redox properties, abundant oxygen vacancies (O V ), antiagglomeration, and high phase stability under harsh conditions. Compared with the ex situ introduction of HEO on the surface, the in situ method provides dual benefits to maintain the dispersity of HEO via entropic and lattice confinement effects. Engineering the complex HEO within the lattice of fluorite-structured CeO 2 also yields abundant defects (e.g., O V ) and active metal sites with strong reducing properties (e.g., Ce 3+ and Cu + ), which greatly improves the activity of the lattice oxygen and tunability of the adsorption behavior of the guest molecules, especially in the presence of impurities (e.g., water and propane). The catalytic performance of the supported HEO catalyst in oxidative procedures surpasses the pure dense phase HEO as well as the ex situ-generated catalysts. Further, the synthesis approach being developed in this work, together with the fundamental understanding in structure evolution and reaction mechanism, showcases a facile pathway under ambient conditions to generate stable catalysts capable of maintaining structural robustness in high-temperature conditions while delivering enhanced catalytic performance.

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

Asymmetric pathways for lithium extraction and recovery based on the two-phase equilibrium of layered oxides

Electrochemical intercalation offers a promising platform for Li + extraction. However, only limited types of electrode materials have been investigated. The challenge to broaden and tailor materials for electrochemical intercalation-based Li + extraction lies in the lack of understanding of material’s response upon co-intercalation of multiple ions, therefore, paired process design to enable reversible Li + extraction and recovery. Here, we showcase the design of asymmetric ion pathways for Li + extraction and recovery for host material with complex Li + and Na + interaction using layered cobalt oxide as a model material. The two-phase equilibrium of Na 0.48 CoO 2 and Li 0.94 CoO 2 governs Li + selectivity when a high depth of intercalation is achieved (low vacancy level). We show that the relative rate between ion exchange and intercalation is critical to determine the ion pathways. The relationship can be quantitatively compared using the average pseudo ion exchange rate (C pseudoIX ) and the intercalation rate (C inter ). The ion pathways at the three regimes with C pseudoIX > C inter , C pseudoIX ~ C inter , and C pseudoIX < C inter are constructed. By selecting the optimized ion pathway and particle size, we demonstrate 9.7×10 4 Li + selectivity with 99% purity Li + recovery from an initial 1:1000 Li: Na molar ratio solution using 115 mAh/g specific capacity.

electrochemistry↗
DOE OSTI2025

Meta Biome: a multiscale model integrating agent-based and metabolic networks to reveal spatial regulation in gut mucosal microbial communities

ABSTRACT Mucosal microbial communities (MMCs) are complex ecosystems near the mucosal layers of the gut essential for maintaining health and modulating disease states. Despite advances in high-throughput omics technologies, current methodologies struggle to capture the dynamic metabolic interactions and spatiotemporal variations within MMCs. In this work, we presentMetaBiome, a multiscale model integrating agent-based modeling (ABM), finite volume methods, and constraint-based models to explore the metabolic interactions within these communities. Integrating ABM allows for the detailed representation of individual microbial agents each governed by rules that dictate cell growth, division, and interactions with their surroundings. Through a layered approach—encompassing microenvironmental conditions, agent information, and metabolic pathways—we simulated different communities to showcase the potential of the model. Using ourin-silicoplatform, we explored the dynamics and spatiotemporal patterns of MMCs in the proximal small intestine and the cecum, simulating the physiological conditions of the two gut regions. Our findings revealed how specific microbes adapt their metabolic processes based on substrate availability and local environmental conditions, shedding light on spatial metabolite regulation and informing targeted therapies for localized gut diseases.MetaBiome provides a detailed representation of microbial agents and their interactions, surpassing the limitations of traditional grid-based systems. This work marks a significant advancement in microbial ecology, as it offers new insights into predicting and analyzing microbial communities. IMPORTANCE Our study presents a novel multiscale model that combines agent-based modeling, finite volume methods, and genome-scale metabolic models to simulate the complex dynamics of mucosal microbial communities in the gut. This integrated approach allows us to capture spatial and temporal variations in microbial interactions and metabolism that are difficult to study experimentally. Key findings from our model include the following: (i) prediction of metabolic cross-feeding and spatial organization in multi-species communities, (ii) insights into how oxygen gradients and nutrient availability shape community composition in different gut regions, and (iii) identification of spatiallyregulated metabolic pathways and enzymes inE. coli. We believe this work represents a significant advance in computational modeling of microbial communities and provides new insights into the spatial regulation of gut microbiome metabolism. The multiscale modeling approach we have developed could be broadly applicable for studying other complex microbial ecosystems.

Microbiology↗
DOE OSTI2024

“Green” Fabrication of High-performance Transparent Conducting Electrodes by Blade Coating and Photonic Curing on PET for Perovskite Solar Cells

This study presents an innovative material processing approach to fabricate transparent conducting electrodes (TCEs) on polyethylene terephthalate (PET) substrates using blade coating and photonic curing. The hybrid TCEs consist of a multiscale Ag network, combining silver metal bus lines and nanowires, overcoated by an indium zinc oxide layer, and then photonically cured. Blade coating ensures film uniformity and thickness control over large areas. Photonic curing, a non-thermal processing method with significantly lower carbon emissions, enhances the conductivity and transparency of the coated layers. Our hybrid TCEs achieve an average transmittance of (81 ± 0.4)% referenced to air ((90 ± 0.4)% referenced to the PET substrate) in the visible range, an average sheet resistance of (11 ± 0.5) Ω sq−1, and an average surface roughness of (4.3 ± 0.4) nm. We benchmark these values against commercial PET/TCE substrates. Mechanical durability tests demonstrate <3% change in resistance after 2000 bending cycles at a 1 in radius. The scalable potential of the hybrid TCE fabrication method is demonstrated by high uniformity and excellent properties in 7 in × 8 in large-area samples and by performing the photonic curing process at 11 m min−1. Furthermore, halide perovskite solar cells fabricated on these hybrid TCEs achieve average and champion power conversion efficiencies of (10.5 ± 1.0) % and 12.2%, respectively, and significantly outperform devices made on commercial PET/TCEs. This work showcases our approach as a viable pathway for high-speed “green” manufacturing of high-performance TCEs on PET substrates for flexible optoelectronic devices.

Bonner, Justin C↗
DOE OSTI2025

Activity-targeted metaproteomics uncovers rare syntrophic bacteria central to anaerobic community metabolism

Syntrophic microbial consortia can contribute significantly to the activity and function of anoxic ecosystems, yet are often too rare to study their in situ physiologies using traditional molecular methods. Here, in this study, we describe a technical innovation combining bioorthogonal non-canonical amino acid tagging (BONCAT), stable isotope probing, and metaproteomics to improve the recovery of proteins from active community members and track isotope incorporation. Both click chemistry-enabled cell-sorting and direct protein pulldown coupled to metaproteomics improved recovery of isotopically labeled proteins during acetate oxidation within a full-scale anaerobic digester. Resulting labeled protein expression profiles revealed elevated activity of a rare and uncharacterized syntrophic bacterium belonging to the family Natronincolaceae. BONCAT-based capture of newly translated proteins provided direct molecular evidence for the expression of a previously hypothesized oxidative glycine pathway for syntrophic acetate oxidation by this microorganism, showcasing the potential of targeted metaproteomics to characterize rare and active cells central to community metabolism in natural and engineered ecosystems.

Friedline, Skyler [Univ. of British Columbia, Vanc↗
DOE OSTI2025

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗
DOE OSTI2024

Dynamically generated decoherence-free subspaces and subsystems on superconducting qubits

Abstract Decoherence-free subspaces and subsystems (DFS) preserve quantum information by encoding it into symmetry-protected states unaffected by decoherence. An inherent DFS of a given experimental system may not exist; however, through the use of dynamical decoupling (DD), one can induce symmetries that support DFSs. Here, we provide the first experimental demonstration of DD-generated decoherence-free subsystem logical qubits. Utilizing IBM Quantum superconducting processors, we investigate two and three-qubit DFS codes comprising up to six and seven noninteracting logical qubits, respectively. Through a combination of DD and error detection, we show that DFS logical qubits can achieve up to a 23% improvement in state preservation fidelity over physical qubits subject to DD alone. This constitutes a beyond-breakeven fidelity improvement for DFS-encoded qubits. Our results showcase the potential utility of DFS codes as a pathway toward enhanced computational accuracy via logical encoding on quantum processors.

Physics↗
DOE OSTI2025

Solvent Determines the Formation Pathway in Sol–Gel Synthesized Disordered Rock Salt Material for Lithium Ion Battery Application

The increasing demand for lithium-ion batteries with high capacity and cycling stability, in combination with the scarcity of cobalt and nickel, has led to significant efforts to develop new cathode materials based on earth-abundant transition metals. Mn- and Ti-based disordered rock salt (DRX) cathodes are promising candidates fulfilling these requirements. However, their large-scale fabrication can be energy- and time-intensive using traditional fabrication methods, e.g., solid-state synthesis. The present study showcases sol-gel synthesis as an alternative method with control over the crystallization pathway through solvent choice. Dimethylformamide (DMF) aids the homogenization of the transition metals during early crystallization stages and formation of Li2TiO3 and LiMn2O4 intermediates before the DRX phase is formed. In contrast, 2-methoxyethanol (2-ME) shows transition metal segregation and formation of an additional transition metal intermediate (Ti2MnO4) while not resulting in phase-pure DRX material after calcination. Coin cells prepared with DMF-material yield higher capacity and cycling stability compared with 2-ME material.

Kodalle, Tim↗
DOE OSTI2024

Self-Assembling Cell-Free Systems for Scalable Bioconversion

This project focused on developing cell-free systems to directly express multi-enzyme catalysts and perform CO2 bioconversions for industrial chemical production. The use of cell-free expression (CFE) systems derived from bacterial lysates is emerging as a promising approach for biomanufacturing. CFEs are genetically programmable, permit the expression of toxic enzymes, and allow for rapid prototyping of metabolic pathways. Research Contributions: 1. Understanding the Area Investigated: This research advances the understanding of cell-free systems by demonstrating their capability to perform complex multi-enzyme reactions. By directly expressing multi-gene systems, CFEs avoid the high costs and inefficiencies associated with producing and purifying enzymes for multi-step pathways. 2. Technical Effectiveness and Economic Feasibility: The project successfully engineered a CFE-based multienzyme biocatalyst for the de novo synthesis of serine and glycine from CO2 equivalents (formate and bicarbonate) and ammonia. This method achieved a 30% conversion rate of formate into these industrially important amino acids. Additionally, an 8-gene CFE biocatalyst was developed to produce malate, conserving 43% of carbon that would otherwise be lost as CO2. This approach has the potential to reach higher carbon efficiency than microbial production. 3. Public Benefit: The cell-free production of chemicals like serine, glycine, and malate using electrochemically generated formate could significantly reduce CO2 emissions. For example, satisfying the global malate market with this method could avoid approximately 400,000 tons of CO2 emissions annually. This work demonstrates the potential of CFE systems to produce platform chemicals, contributing to environmental sustainability and reducing reliance on petrochemicals. Future Prospects: The CFE-based biocatalyst process could be extended to produce a variety of chemicals, including other industrial di-acids, aromatics, terpenes, alcohols, and polymers. This project showcases the capabilities of cell-free expression systems for prototyping carbon-conserving pathways and sustainably bioproducing platform chemicals, marking a significant step towards economically-viable industrial processes.

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

Steady motion of 80-nm-size skyrmions in a 100-nm-wide track

The current-driven movement of magnetic skyrmions along a nanostripe is essential for the advancement and functionality of a new category of spintronic devices resembling racetracks. Despite extensive research into skyrmion dynamics, experimental verification of current-induced motion of ultra-small skyrmions within an ultrathin nanostripe is still pending. Here, we unveil the motion of individual 80 nm-size skyrmions in an FeGe track with an ultrathin width of 100 nm. The skyrmions can move steadily along the track over a broad range of current densities by using controlled pulse durations of as low as 2 ns. The potential landscape, arising from the magnetic edge twists in such a geometrically confined system, introduces skyrmion inertia and ensures efficient motion with a vanishing skyrmion Hall angle. Our results showcase the steady motion of skyrmions in an ultrathin track, offering a practical pathway for implementing skyrmion-based spintronic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Refining a Novel Process Monitoring Method to Safeguard Continuously Cycling Designs Using Isotopic Ratios

In advanced reactor (AR) designs, a common feature is continuous chemical processing and circulation of the nuclear material. This work bridges a significant measurement gap in safeguarding reactors with circulating fuel or continuous refueling by leveraging and building on the isotope ratio method first developed by our team under an FY21 Advanced Reactors International Safeguards Engagement (ARISE) project (Uribe et al. 2021). In circulating fuel designs, the radioisotope inventory changes from traditional effects (e.g., radioactive decay, fission) but also includes material transport due to pressure and temperature gradients. Such designs may also require regular or continuous additions or removals during operation, which significantly increases the rate of inventory change compared to traditional pressurized water reactor (PWR)s. Thus, directly tracking the nuclear inventory is ineffective since the isotopes are continuously added and removed. The isotope ratio method instead focuses on detecting changes to the input and output flows of radioisotopes. Previous work showed that for well-chosen pairs of isotopes, the isotopic ratio provides a sensitive and lasting indicator of deviation from normal conditions (e.g., startup, shutdown, diversion). The isotope ratio method is a process monitoring method with potential for application in for forward-looking approaches to International Atomic Energy Agency (IAEA) safeguards. The original process monitoring method was developed for a specific case—the decay tank of a thorium-fueled molten salt breeder reactor. In this expanded work, we explored other types of reactors and processes with nonstationary (e.g., flowing) nuclear material, which are difficult to safeguard with traditional methods because of the transient nature of the systems. The goal of the present work is to generalize the isotope ratio method for use in processes with continuously flowing nuclear material. All continuous processes have an average time for isotopes to be replaced in the system. The isotope ratio method works by choosing radioisotopes with half-lives both above and below the processing time. The present work seeks to explore which isotopes are suitable for the method by simulating the nuclear inventory, radioisotope emissions, and detector responses for several classes of advanced reactors. While the method can in principle be applied to other processes (e.g., enrichment or reprocessing facilities), the present work limits scope to ARs with continuously flowing fuel. Section 2 details the mathematics supporting the isotope ratio method, and Section 3 introduces the representative ARs selected for this work. Section 4 discusses how each reactor was analyzed, and Section 5 showcases the results for each representative reactor. Finally, Section 6 provides concluding remarks and suggests pathways for further analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Quantum Computing for Energy-Related Applications

Growing interest in quantum computing and simulations have created opportunities for its deployment to improve processes pertaining to energy production, distribution, and consumption. While quantum computing is considered as a paradigm shift in our basic understanding of physical computation, effective implementation of quantum computing in energy applications also depends on progress and development in the dimensions of both quantum computing hardware and quantum computing algorithms. To fully address the status and future challenges of quantum information science (QIS) applied within the energy sector, in this presentation, we firstly summarize recent advancements on the applications of quantum computing to energy infrastructure and materials, complex energy system processes, advanced manufacturing, and energy system security. Then, we will demonstrate the results of quantum computing both on a simulator and a quantum device accessing from OLCF. Our first example is to use the variational quantum eigensolver (VQE) with a unitary coupled cluster with singles and doubles (UCCSD) ansatz to simulate a series of LixHyq molecules (q=-1, 0, +1). The obtained results showed that the quantum computing VQE-UCCSD is comparable to classical CCSD for small systems like LiH with respect to full configuration interaction (FCI). Targeting on CO2 capture application, our second example is to use VQE to quantify molecular vibrational energies and reaction pathways between CO2 and a simplified amine-based solvent model—NH3 to form H2NCOOH. This research showcases quantum computing applications in the study of CO2 capture reactions.

Duan, Yuhua↗
DOE OSTI2025

Atomic-resolution imaging as a mechanistic tool for studying single-site heterogeneous catalysis

Heterogeneous catalysts dominate the chemical industry but typically feature diverse, incompletely defined active sites. Thus, describing structure-activity relationships, unlike homogeneous catalysts, remains challenging. In contrast, molecularly defined single-site heterogeneous catalysts (SSHCs), using appropriate tools, are poised to address these challenges and provide new avenues for catalysis research and development. The present study explores eco-friendly H 2 production mediated by discrete MoO 2 sites supported on carbon nanohorns (CNHs) and active for alcohol dehydrogenation. While informative, detailed ensemble EXAFS/XANES/XPS, kinetic measurements, and DFT analysis alone cannot provide a full molecular picture of the reaction pathway. Here, using single-molecule atomic-resolution time-resolved electron microscopy (SMART-EM), we propose the identification of four key catalytic intermediates anchored to CNHs and uncover a new reaction pathway involving alkoxide/hemiacetal equilibration and acetal oligomerization. Furthermore, these intermediates are inferred through a combination of theory and SMART-EM, showcasing the potential of SMART-EM as a complementary tool for exploring mechanistic hypotheses in catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ultrafast creation of a light-induced semimetallic state in strongly excited 1T-TiSe 2

Screening, a ubiquitous phenomenon associated with the shielding of electric fields by surrounding charges, has been widely adopted as a means to modify a material’s properties. While most studies have relied on static changes of screening through doping or gating thus far, here we demonstrate that screening can also drive the onset of distinct quantum states on the ultrafast timescale. By using time- and angle-resolved photoemission spectroscopy, we show that intense optical excitation can drive 1T-TiSe 2 , a prototypical charge density wave material, almost instantly from a gapped into a semimetallic state. By systematically comparing changes in band structure over time and excitation strength with theoretical calculations, we find that the appearance of this state is likely caused by a dramatic reduction of the screening length. In summary, this work showcases how optical excitation enables the screening-driven design of a nonequilibrium semimetallic phase in TiSe 2 , possibly providing a general pathway into highly screened phases in other strongly correlated materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Exploiting correlations in multi-coincidence Coulomb explosion patterns for differentiating molecular structures using machine learning

Coulomb explosion imaging (CEI) is a powerful technique for capturing the real-time motion of individual atoms during ultrafast photochemical reactions. CEI generates high-dimensional data with naturally embedded correlations that allow mapping the coordinated motion of nuclei in molecules. This enables reliable separation of competing reaction pathways and makes this approach uniquely suited for characterizing weak reaction channels. However, rich information contained in experimental CEI patterns remains largely underexploited due to challenges in visualizing correlations between multiple observables in multi-dimensional parameter space. Here we present a new approach to CEI of intermediate-sized polyatomic molecules, detecting up to eight ionic fragments in coincidence and leveraging machine-learning-based analysis to identify patterns and correlations in the resulting high-dimensional momentum-space data, enabling robust molecular structure identification and differentiation. Our approach provides high-dimensional background-free data encoding exceptionally rich structural information and establishes an automated, scalable framework for extracting insightful information from the data. As a demonstration, we apply this method to image and distinguish dichloroethylene isomers, showcasing its potential for broader applications in molecular imaging. Our results pave the way for channel-specific analysis of ultrafast structural dynamics in chemically relevant systems, particularly for disentangling mixed reaction pathways and detecting contributions from weak channels and minority species.

Chemical Physics (physics.chem-ph)↗