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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Similarity of Precursors in Solid-State Synthesis as Text-Mined from Scientific Literature

Collecting and analyzing the vast amount of information available in the solid-state chemistry literature may accelerate our understanding of materials synthesis. However, one major problem is the difficulty of identifying which materials from a synthesis paragraph are precursors or are target materials. In this study, we developed a two-step chemical named entity recognition model to identify precursors and targets, based on information from the context around material entities. Using the extracted data, we conducted a meta-analysis to study the similarities and differences between precursors in the context of solid-state synthesis. To quantify precursor similarity, we built a substitution model to calculate the viability of substituting one precursor with another while retaining the target. From a hierarchical clustering of the precursors, we demonstrate that the “chemical similarity” of precursors can be extracted from text data. Quantifying the similarity of precursors helps provide a foundation for suggesting candidate reactants in a predictive synthesis model.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Kinetic Pathways Templated by Low-Temperature Intermediates during Solid-State Synthesis of Layered Oxides

Layered oxides have been the dominant cathodes in lithium-ion batteries, and among them, high-nickel (Ni) systems are attractive because of their high capacity. For practical use, synthetic control of stoichiometry and structural ordering is crucial but has been nontrivial due to the complexity inherent to synthesis reactions, which often proceed via nonequilibrium pathways. In this paper, we report here a combined in situ synchrotron X-ray diffraction and ab initio study of solid-state synthesis of layered oxides starting from acetate precursors for LiCoO 2 and LiNiO 2 and their solid solution LiNi 0.8 Co 0.2 O 2 . While all three systems ultimately evolve into the same thermodynamically stable layered phase ($R\overline{3}m$), each chemistry involves distinct metastable intermediates. We explain the phase progressions using a structural template model, demonstrating that during the synthesis of LiCoO 2 , the formed metastable spinel polymorph (Li 2 Co 2 O 4 ; $Fd\overline{3}m$) is a kinetically facile lithiation product of spinel Co 3 O 4 —the low-temperature (LT) intermediate from the decomposed Co-acetate. Similarly, in the Ni-based systems, the acetate decomposition products, rocksalts (Ni,Co)O, topotactically template the kinetic pathways of forming disordered rocksalts (Li x (Ni,Co) 2–x O 2 ; $Fm\overline{3}m$), consequently leading to off-stoichiometric Li x (Ni,Co)O 2 with undesired high Li/Ni mixing. These findings highlight new opportunities for engineering precursors to form LT intermediates that template the synthesis of target phases and structural properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding the Fluorination of Disordered Rocksalt Cathodes through Rational Exploration of Synthesis Pathways

Here, we have designed and tested several synthesis routes targeting a highly fluorinated disordered rocksalt (DRX) cathode, Li 1.2 Mn 0.4 Ti 0.4 O 1.6 F 0.4 , with each route rationalized by thermochemical analysis. Precursor combinations were screened to raise the F chemical potential and avoid the formation of LiF, which inhibits fluorination of the targeted DRX phase. MnF 2 was used as a reactive source of F, and Li 6 MnO 4 , LiMnO 2 , and Li 2 Mn 0.33 Ti 0.66 O 3 were tested as alternative Li sources. Each synthesis procedure was monitored using a multi-modal suite of characterization techniques including X-ray diffraction, nuclear magnetic resonance, thermogravimetric analysis, and differential scanning calorimetry. From the resulting data, we advance the understanding of oxyfluoride synthesis by outlining the key factors limiting F solubility. At low temperatures, MnF 2 consistently reacts with the Li source to form LiF as an intermediate phase, thereby trapping F in strong Li-F bonds. LiF can react with Li 2 TiO 3 to form a highly lithiated and fluorinated DRX (Li 3 TiO 3 F); however, MnO is not easily incorporated into this DRX phase. Although higher temperatures typically increase solubility, the volatility of LiF above its melting point (848 °C) inhibits fluorination of the DRX phase. Based on these findings, metastable synthesis techniques are suggested for future work on DRX fluorination.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synthesis and Structural Study of Substituted Ternary Nitrides for Ammonia Production

Over the past few decades, inorganic nitride materials have grown in importance in part due to their potential as catalysts for the synthesis of NH 3 , a key ingredient in fertilizer and precursor to industrial chemicals. Of particular interest are the ternary (ABN) or higher-order nitrides with high metal-to-nitrogen ratios that show promise in enhancing NH 3 synthesis reaction rates and yields via heterogeneous catalysis or chemical looping. Although metal nitrides are predicted to be numerous, the stability of nitrogen triple bonds found in N 2 , especially in comparison to the metal–nitrogen bonds, has considerably hindered synthetic efforts to produce complex nitride compounds. In this study, we present an exhaustive down-selection process to identify ternary nitrides for a promising chemical looping NH 3 production mechanism. We also report on a facile and efficient two-step synthesis method that can produce well-characterized η-carbide Co 3 Mo 3 N/Fe 3 Mo 3 N or filled β-manganese Ni 2 Mo 3 N ternaries, as well as their associated quaternary, (Co,Fe) 3 Mo 3 N, (Fe,Ni) 2 Mo 3 N, and (Co,Ni) 2 Mo 3 N, solid solutions. To further explore the quaternary space, syntheses of (Co,Ni) 3 Mo 3 N (Ni ≤ 10 mol %) and Co 3 (Mo,W) 3 N (W ≤ 10 mol %) were also investigated. The structures of the nitrides were characterized via X-ray powder diffraction. The morphology and compositions were characterized with scanning electron microscopy. In conclusion, the multitude of chemically unique, but structurally related, nitrides suggests that properties such as nitrogen activity may be tunable, making the materials of great interest for NH 3 synthesis schemes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Direct Mechanochemical Synthesis, Phase Stability, and Electrochemical Performance of α-NaFeO 2

To better understand polymorph control in transition metal oxides, the mechanochemical synthesis of NaFeO 2 was explored. In this paper, we report the direct synthesis of α-NaFeO 2 through a mechanochemical process. By milling Na 2 O 2 and γ-Fe 2 O 3 for 5 h, α-NaFeO 2 was prepared without high-temperature annealing needed in other synthesis methods. While investigating the mechanochemical synthesis, it was observed that changing the starting precursors and mass of precursors affects the resulting NaFeO 2 structure. Density functional theory calculations on the phase stability of NaFeO 2 phases show that the α phase is stabilized over the β phase in oxidizing environments, which is provided by the oxygen-rich reaction between Na 2 O 2 and Fe 2 O 3 . This provides a possible route to understanding polymorph control in NaFeO 2 . Annealing the as-milled α-NaFeO 2 at 700 °C has resulted in increased crystallinity and structural changes that improved electrochemical performance in terms of capacity over the as-milled sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

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

Unraveling In-Situ Formation of Surface Nickel Nitride Structures in Plasma-Assisted Catalytic Ammonia Synthesis

We report the in situ formation of Ni nitride for plasma-assisted ammonia synthesis. Both the surface nitrogen concentration and the ammonia formation rate exhibit dependence on the N 2 :H 2 feed ratio. The maximum surface nitrogen concentration occurs at a N 2 :H 2 ratio of 4:1, and the maximum catalytic activity occurs at 2:1. In contrast, the formation of gas phase radicals is less sensitive to feed composition, indicating that Ni nitride is more kinetically relevant to ammonia production than gas-phase radicals. The plasma-induced formation of Ni nitride is therefore proposed to be a critical contributor to the synergistic effects in plasma-assisted catalytic ammonia synthesis. Additionally, Ni nitride alters the surface reaction mechanism of plasma-assisted ammonia synthesis, with the rate-determining-step (RDS) shifting to surface-bound NH 3 formation rather than N 2 activation at temperatures below 373 K. These findings provide mechanistic insight that opens opportunities for optimizing the performance of plasma-assisted catalytic ammonia synthesis

Ammonia↗
DOE OSTI2021

Diastereoselective Template Synthesis on Iron and Uranium

The addition of 2 equiv of t Bu 2 PSiMe 3 to 2,6-pyridinedicarboxaldehyde ((CHO) 2 Py) results in a rac / meso diastereomeric mixture of the PNP-chelating ligand 2,6-bis((trimethylsiloxy)(di- tert -butylphosphino)-methyl)-pyridine ( (OTMS) PNP t Bu ) ( 1 - r / m ) via addition of the P–Si bond across both of the aldehyde C–O bonds. Chelation of (OTMS) PNP t Bu to FeCl 2 results in the same diastereotopic ratio of ( (OTMS) PNP t Bu )FeCl 2 ( 2- r / m ) as the free ligand. Fractional crystallization allows for the isolation of the C 2 isomer, 2- r , and a template synthesis protocol allows for the synthesis and isolation of the C s isomer, 2- m , in good yield. Furthermore, the template synthesis protocol was also expanded to the f -block with the use of UCl 4 in order to assess the specificity of the template synthesis on a larger metal cation. This reaction performed on UCl 4 forms the meso diastereospecific uranium complex ( ( t Bu2P) ONO)UCl 2 (dtbpy), 3 - m , with observation of the rational intermediate ( (OTMS) PNO t Bu )UCl 3 (dtbpy), 4 - m , which arose from the respective formation of two- or one-equivalents of TMS–Cl and formation of the corresponding U–O bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Coupling High-Throughput Experiments and Regression Algorithms to Optimize PGM-Free ORR Electrocatalyst Synthesis

Over the past decades, significant improvement has been achieved in the performance of platinum group metal-free (PGM-free) materials as an alternative to Pt-based electrocatalysts for oxygen reduction reaction (ORR). However, further progress in ORR activity requires evaluation of precursors and synthesis approaches. In response to this challenge, we generated a first of its kind experimental data set of 36 samples using high-throughput synthesis and activity measurements. Several control parameters (e.g., Fe precursor identity, the precursor content, and pyrolysis temperature) were varied. We then developed several state-of-the-art machine learning (ML) based regression models to predict ORR activity, dependent on selected synthesis variables. Through an iterative algorithm, higher prediction accuracy (smaller root-mean-square error) was achieved. We identified that gradient boosting regression (GBR) and support vector regression (SVR), among several methods, work best for this data set. Aided by our ML-based surrogate models, we decided to alter catalyst synthesis conditions, which resulted in a 36% increase in measured ORR activity in comparison to the maximum ORR mass activity value of 21.9 A/g catalyst in the original data set. Overall, this combined experiment and machine learning approach represents a promising path forward toward developing highly efficient next-generation ORR electrocatalysts and, more generally, functional materials.

25 ENERGY STORAGE↗
DOE OSTI2025

Expanding Parameter Space to Enable Low-Temperature Synthesis of Crystalline Indium Phosphide Quantum Dots

Established methods to synthesize indium phosphide quantum dots (QDs) require high temperatures (>180 °C) to make high-quality material for optoelectronic applications. Nonpolar solvent environments are overwhelmingly used in InP QD synthesis to reach the necessary high temperatures and for compatibility with the reactive precursors. In this study, we explored InP QD synthesis in polar aprotic solvent environments to dramatically decrease the temperature required for InP crystallization by imparting ionicity to the precursors and stabilizing charged reaction intermediates. A custom air-free 96- well plate setup was employed to identify key factors impacting low-temperature QD formation, including an increased percentage of polar solvent, carboxylic acid choice, and inclusion of polar additives. Guided by these insights, we developed a synthesis of crystalline, green-emitting InP QDs at 60 °C in a toluene-dimethylformamide mixture. Here's, the QDs withstood established Zn 2+ and HF surface treatments, which increased the photoluminescence quantum yield to 25%. Additionally, we demonstrated the rapid synthesis of quasi-wurtzite InP QDs at room temperature in a polar solvent environment using an acid-free indium myristate precursor.

absorption↗
DOE OSTI2020

Techno-Economic Analysis of Recycled Ionic Liquid Solvent Used in a Model Colloidal Platinum Nanoparticle Synthesis

Ionic liquids have garnered significant attention over the past 20 years as alternatives to conventional volatile organic solvents because they are non-flammable, have negligible vapor pressures, possess high thermal and chemical stabilities, and can potentially be recycled. A more recent use of ionic liquids is their application as a solvent in the synthesis of colloidal inorganic nanoparticles; however, a major challenge in the adoption of ionic liquids is that they are generally more expensive than their traditional organic solvent counterparts. Herein, we provide insight into how recycling an ionic liquid solvent affects the product characteristics in a model colloidal platinum nanoparticle synthesis, the structure of the ionic liquid through each recycle, and the overall cost of nanoparticle fabrication using a techno-economic analysis. Using a standard ionic liquid, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (BMIM-NTf2), as the solvent for a Pt nanoparticle synthesis, we demonstrate that the ionic liquid can be recovered and reused through multiple successive reactions following the initial reaction with virgin, or as-purchased, ionic liquid. The use of recycled ionic liquid does not cause any degradation in the product quality or change in nanoparticle morphology. Techno-economic analysis of this synthesis method revealed that, through ionic liquid recycling, nanoparticle preparation using BMIM-NTf2 can achieve a cost that is not only competitive but also potentially lower than that of the conventional organic solvent, 1-octadecene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Selectivity in Yttrium Manganese Oxide Synthesis via Local Chemical Potentials in Hyperdimensional Phase Space

In sharp contrast to molecular synthesis, materials synthesis is generally presumed to lack selectivity. The few known methods of designing selectivity in solid-state reactions have limited scope, such as topotactic reactions or strain stabilization. This contribution describes a general approach for searching large chemical spaces to identify selective reactions. This novel approach explains the ability of a nominally “innocent” Na 2 CO 3 precursor to enable the metathesis synthesis of single-phase Y 2 Mn 2 O 7 : an outcome that was previously only accomplished at extreme pressures and which cannot be achieved with closely related precursors of Li 2 CO 3 and K 2 CO 3 under identical conditions. By calculating the required change in chemical potential across all possible reactant-product interfaces in an expanded chemical space including Y, Mn, O, alkali metals, and halogens, using thermodynamic parameters obtained from density functional theory calculations, we identify reactions that minimize the thermodynamic competition from intermediates. In this manner, only the Na-based intermediates minimize the distance in the hyperdimensional chemical potential space to Y 2 Mn 2 O 7 , thus providing selective access to a phase which was previously thought to be metastable. Experimental evidence validating this mechanism for pathway-dependent selectivity is provided by intermediates identified from in situ synchrotron-based crystallographic analysis. Finally, this approach of calculating chemical potential distances in hyperdimensional compositional spaces provides a general method for designing selective solid-state syntheses that will be useful for gaining access to metastable phases and for identifying reaction pathways that can reduce the synthesis temperature, and cost, of technological materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mixed-Flux Techniques for Rational Synthesis and Structural Control in Silver Chalcogenides

The functionality of materials is intrinsically linked to their structures, an axiom encapsulated in the principle of structure-property relationships. The pinnacle of materials design is the tailoring of its structure for a specific function, which requires the ability of rational synthesis and the development of synthesis science. This idea, however, remains elusive for the synthesis of complex extended solids. A major obstacle is the difficulty in using established chemical principles selectively to control reaction paths and favor certain structural patterns over numerous other possible results. In this context, we are developing a synthesis science approach that facilitates the control of the structure and bonding to create new structures. This is achieved by employing a two-component flux consisting of mixed hydroxides and halides as the reaction medium. This enables reaction conditions that allow better control of the structure dimensionality and composition by manipulating the temperature and solvent basicity (via the flux component ratio). Here, we demonstrate the efficacy of this method in controlling their structural motifs to arrive at 23 unreported compositions and 6 unique structure types. These materials are expected to exhibit a broad range of properties, from metallic to semiconducting, with calculations suggesting the potential for emergent phenomena such as Dirac semimetals. The reaction paths afforded by these mixed fluxes establish a direct correlation between the synthetic variables and properties, providing significant insight into a broadly applicable approach for new materials.

Zhou, Xiuquan [Argonne National Laboratory (ANL), ↗
DOE OSTI2026

Design Principles for the Synthesis of Self-Pillared ZSM-5 Zeolite Nanosheets

The design of next-generation materials for emerging energy and environmental applications heavily relies on empirical approaches to direct nonclassical nucleation and crystal growth pathways, polymorphism, intercrystalline transformations, and seed-assisted growth processes. A long-standing obstacle to nanoporous materials design is the complexity of their crystallization, which hinders the development of predictive models and/or physical descriptors that can guide their synthesis. In this study, we use a combination of state-of-the-art synthesis, characterization, and computational design to prepare hierarchical MFI-type zeolites, which we couple with benchmark catalytic testing to assess structure-property-performance relationships. These hierarchical materials are intergrowths of two commercially relevant zeolite frameworks, MFI and MEL, prepared as self-pillared pentasil (SPP) zeolites through seed-assisted, organic-free syntheses for which little theoretical guidance existed. Here, by comparing a large library of zeolite seeds with different pore sizes, dimensions, and structural composite building units, we determined the relative impact of seed and silica source selection, among other synthesis variables. Combined experimental and computational studies are used to test several hypotheses in literature to rationalize the choice of seed structure and establish a more robust selection criteria for seed-assisted synthesis of zeolites. Specifically, we show that a data-driven approach to develop structural descriptors correlates to new, facile routes to rationally design SPP zeolites, addressing knowledge gaps in the fundamental understanding of (non)classical crystal growth mechanisms that are characteristic of nanoporous aluminosilicates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Template-independent enzymatic synthesis of RNA oligonucleotides

Abstract RNA oligonucleotides have emerged as a powerful therapeutic modality to treat disease, yet current manufacturing methods may not be able to deliver on anticipated future demand. Here, we report the development and optimization of an aqueous-based, template-independent enzymatic RNA oligonucleotide synthesis platform as an alternative to traditional chemical methods. The enzymatic synthesis of RNA oligonucleotides is made possible by controlled incorporation of reversible terminator nucleotides with a common 3′-O-allyl ether blocking group using new CID1 poly(U) polymerase mutant variants. We achieved an average coupling efficiency of 95% and demonstrated ten full cycles of liquid phase synthesis to produce natural and therapeutically relevant modified sequences. We then qualitatively assessed the platform on a solid phase, performing enzymatic synthesis of severalN + 5 oligonucleotides on a controlled-pore glass support. Adoption of an aqueous-based process will offer key advantages including the reduction of solvent use and sustainable therapeutic oligonucleotide manufacturing.

Biotechnology & Applied Microbiology↗
DOE OSTI2024

Navigating phase diagram complexity to guide robotic inorganic materials synthesis

Abstract Efficient synthesis recipes are needed to streamline the manufacturing of complex materials and to accelerate the realization of theoretically predicted materials. Often, the solid-state synthesis of multicomponent oxides is impeded by undesired by-product phases, which can kinetically trap reactions in an incomplete non-equilibrium state. Here we report a thermodynamic strategy to navigate high-dimensional phase diagrams in search of precursors that circumvent low-energy, competing by-products, while maximizing the reaction energy to drive fast phase transformation kinetics. Using a robotic inorganic materials synthesis laboratory, we perform a large-scale experimental validation of our precursor selection principles. For a set of 35 target quaternary oxides, with chemistries representative of intercalation battery cathodes and solid-state electrolytes, our robot performs 224 reactions spanning 27 elements with 28 unique precursors, operated by 1 human experimentalist. Our predicted precursors frequently yield target materials with higher phase purity than traditional precursors. Robotic laboratories offer an exciting platform for data-driven experimental synthesis science, from which we can develop fundamental insights to guide both human and robotic chemists.

Chen, Jiadong (ORCID:0009000476038838)↗
DOE OSTI2020

Active Learning-driven Quantitative Synthesis-Structure-Property Relations for Improving Performance and Revealing Active Sites of Nitrogen-Doped Carbon for the Hydrogen Evolution Reaction

While quantitative structure-properties relations (QSPRs) have been developed successfully in multiple fields, catalyst synthesis affects structure and in turn performance, making simple QSPRs inadequate. Furthermore, catalysts often have multiple active sites preventing one from obtaining insights into structure-property relations. Here, we develop a data-driven quantitative synthesis-structure-property relation (QS2PRs) methodology to elucidate correlations between catalyst synthesis conditions, structural properties as well as observed performance and to provide fundamental insights into active sites and a systematic way to optimize practical catalysts. Here, we demonstrate the approach to the synthesis of nitrogen-doped catalysts (NDC) made via pyrolysis for the performance of the electrochemical hydrogen evolution reaction (HER), quantified by the onset potential and the current density. We determine crystallinity, nitrogen species type and fraction, surface area, and pore structure of the NDC’s using XRD, XPS, and BET characterization. We demonstrated that an active learning-based optimization combined with various elementary machine learning tools (regression, principal component analysis, partial least squares) can efficiently identify optimum pyrolysis conditions to tune structural characteristics and performance with concomitant savings in materials and experimental time. Unlike previous reports on the importance of pyridinic or graphitic nitrogen, we discover that the electrochemical performance is not driven by a single catalyst property; rather, it arises from a multivariate influence of nitrogen dopants, pore structure and disorder in the NDC materials. Identification of active sites can help mechanistic understanding and further catalyst improvement.

42 ENGINEERING↗
DOE OSTI2022

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗