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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Phase transformations and thermal expansion coefficients of unirradiated U-X wt.% Zr (X = 6, 10, 20, 30) measured via neutron diffraction

This work characterizes the crystallographic evolution of unirradiated U-X wt.% Zr (X = 6, 10, 20, 30) while cooling from equilibration, single phase γ-U-Zr, at 900 °C to ambient temperature using time-of-flight neutron diffraction. The β-U phase was unobserved during cooling at 1 °C/min in all alloys. All alloys followed the phase transformation pathway of γ-U-Zr→γ-U-Zr+α-U→α-U +δ-UZr2 with an observed miscibility gap in γ-U-Zr. The α-U and δ-UZr2 transformation took place simultaneously in the U-30 wt.% Zr sample. These findings strengthen the need to re-approach the U-Zr phase diagram in entirety. Bulk volumetric CTEs agree well with published data, strengthening the quantification of lattice-specific CTEs reported in this study. A compositionally dependent discontinuity in thermal expansion, increasing in magnitude with decreasing U content, occurs during the γ-U-Zr→α-U+δ-UZr2 transformation. The γ-U-Zr lattice parameter was measured to have a compositional dependency.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Aperture size distribution, length, and preferential location of bed-parallel veins in shale

Bed-parallel, calcite-filled veins (BPVs) are common in shale formations, and although they have been widely described in other studies, little is known about their population aperture size distribution. To address this knowledge gap, we analyzed BPV sizes in outcrops and cores from the Vaca Muerta Formation, Neuquén Basin, Argentina; in two cores from the Marcellus Formation, Appalachian Basin, northeast Pennsylvania; and in one core from the Wolfcamp Shale, Delaware Basin, West Texas. Nine out of ten aperture size populations follow a negative exponential distribution, with one following a weak power law. Bed-parallel vein size distribution and intensity vary among formations and within the same shale. We define three groups of distributions: (1) Vaca Muerta outcrops, with the highest BPV intensity and the largest BPVs (cumulative frequency of 4.9 BPVs per meter [BPVs/m] for apertures 0.265 mm to 8.7 cm); (2) Vaca Muerta cores with a similar BPV intensity overall but with no apertures wider than 1.2 cm; and (3) Vaca Muerta, Wolfcamp, and Marcellus cores with the fewest BPVs (cumulative frequency up to 0.63 BPVs/m) and very few wider than 1 cm. Aperture and length in two outcrop data sets are weakly positively correlated and follow power laws with exponents of 0.44 and 0.49. Mechanical interfaces at boundaries between different lithologies exert a strong control on BPV location, with 65–75% of observed interfaces having BPVs along them. Only 25–30% of the BPVs occur at observed material interfaces, however, and unless subtle, unobserved mechanical layering is present, other factors must also control location. BPV intensity and organic richness (TOC) from Vaca Muerta well logs are correlated in some instances but not in others, indicating TOC is not always a good proxy for BPV location or intensity. Furthermore, these findings provide useful information for modeling of hydraulic fracture treatments where BPVs may influence development of the stimulated fracture network, for example by limiting height growth.

58 GEOSCIENCES↗
DOE OSTI2021

Ride-hailing and taxi versus walking: Long term forecasts and implications from large-scale behavioral data

Introduction: Although ride-hailing and taxi trips can potentially reduce single-occupant vehicle trips and auto ownership, they can also replace pedestrian trips. Because physical activity is associated with improved health outcomes, the extent to which ride-hailing and taxi travel captures walking's mode share is of interest to policymakers. Methods: Based on large-scale behavioral data from the 2017 U.S. National Household Travel Survey, this paper reports on the development of a full Bayesian logistic regression model for determining the mode split between (1) ride-hailing and taxi and (2) walk while accounting for unobserved heterogeneity. The results from the stand-alone model inform two longer-term travel forecasting scenarios: a) higher risk of walk trips converting to ride-hailing and taxi, specifically in the future with high prevalence of automated vehicles, b) higher probability of such trips remaining as walking. Results: The results revealed that some of the important characteristics that increase the likelihood of a traveler using the ride-hailing and taxi mode versus walking include having a longer trip, using a smartphone to access the internet, having an interest in technologies, having a medical condition, and living in a metropolitan area with rail access. Further, the results from the first scenario suggest that an overall increase of up to 2.9% in the ride-hailing and taxi mode share may be expected. The second scenario shows that between 68% and 76% of ride-hailing and taxi trips could be diverted to walking if supportive pedestrian infrastructure were provided in the case study locations. The planning process can be adapted to consider not only congestion, crash, and emissions impacts of such shifts but also the effects of a loss of physical activity. Conclusions: The study findings show how the ride-hailing and taxi mode competes with walking. Further, the findings enable planners to update their regional travel forecasting models; policy makers can thus encourage active travel by prioritizing pedestrian infrastructure investments that may divert ride-hailing and taxi trips to walking. However, equity should be a key consideration to ensure that addressing the competition between these two modal choices does not hinder the provision of pedestrian facilities in communities that depend on walking.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Nuclear Data Sheets for A=48

Experimental nuclear structure data from various reactions and decays are compiled and evaluated for all known nuclides with mass number A=48 (S, Cl, Ar, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni). For each nuclide, detailed evaluated nuclear structure information is presented for each individual reaction and decay, and the best values combining all available data are recommended for spectroscopic properties, such as level energies, half-lives, γ-ray energies and intensities, decay radiations. No excited states have been identified in 48 S, 48 Cl, 48 Co and 48 Ni, among which the first three even have no measured ground-state half-lives and decay modes. For 48 Fe, a level scheme with a sequence of excited states was established for the first time from a recent one-neutron removal measurement by 2021Ya33. Data for excited states in 48 Ar, 48 K and 48 Mn remain limited; no decay scheme has been measured for 48 Ar and 48 K yet, while the decay scheme for 48 Ni is incomplete due to unobserved levels. 48 Ti is the most studied nuclide through various reactions and decays, followed by 48 V, 40 Ca, 48 Sc, and 48 Cr, among which no decay event to 48 Sc has been observed and the decay schemes for 48 V and 48 Cr are considered as incomplete. Furthermore, this work supersedes the previous full evaluations of A=48: 2006Bu08, 1993Bu04, 1985Al14, 1978Be01.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Field-scale dynamics of planting dates in the US Corn Belt from 2000 to 2020

Crop planting dates are a dynamic feature of agricultural systems that respond to short- and long-term climate signals, crop and cultivar selection, and technology changes. Planting date records are essential for yield gap analyses, accurate crop modeling, and tracking farmer adaptations to weather and climate change. Although planting dates have high variation at local scales due to heterogeneity in farm resources and decision-making, available long-term data on planting dates is largely restricted to aggregated regional statistics or, at best, satellite-derived datasets with limited spatiotemporal extent and at resolutions unable to distinguish individual fields (> 250 m). Here, we generated retrospective annual field-scale (30 m) planting date maps for both maize and soybeans spanning 2000-2020 across a 12 state region in the United States Corn Belt based on Landsat satellite data and a large ground sample of over 28,000 maize and soybean fields. Using training data from 2015-2020 for model selection, we found that planting date predictions improved with harmonic regression of Landsat data and additional annual weather covariates. The preferred random forests model approximately doubled performance compared to a null model based on state median planting dates, capturing 47% of field-level variation for maize (mean absolute error, MAE = 7.4 days) and 44% for soybeans (MAE = 7.5 days) against held-out ground truth test data for 2008-2014. We also evaluated the full 2000-2020 dataset with state agricultural statistics, finding strong agreement with median planting dates for maize (R 2 = 0.76, MAE = 4.4 days) and slightly lower agreement for soybeans (R 2 = 0.65, MAE = 5.4 days) when aggregated to the state level. We then used this new dataset to analyze environmental determinants of planting dates at a finer-scale than previously possible, controlling for unobserved variation at the sub-state district level. We found that during 2000-2020, each standard deviation increase in rainfall delayed planting by ~ 2.5 days, and fields with higher soil productivity ratings tended to be planted earlier. We did not find meaningful trends over the last two decades in planting dates for maize or soybeans, in contrast to trends towards earlier planting dates late last century and predicted for this period in climate adaptation studies. We hypothesize increases in early season rainfall may have inhibited these shifts towards earlier planting. Remotely sensed planting dates will be a useful tool for yield gap analyses, crop simulation modeling, and ongoing assessment of climate adaptation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Predicting battery capacity from impedance at varying temperature and state of charge using machine learning

Prediction of battery health from electrochemical impedance spectroscopy (EIS) data can enable rapid measurement of battery state in real-world applications without using additional sensors or time-consuming performance measurements. However, deconvoluting the effect of capacity, state of charge, and temperature on EIS response is complicated analytically. Here, various machine-learning models, such as linear, Gaussian process, random forest, and artificial neural network regression, are utilized to predict capacity from EIS using hundreds of capacity, direct current (DC) resistance, and EIS measurements recorded under varying conditions of health, temperature, and state of charge (SOC). Several feature extraction and selection methods from traditional electrochemical analysis and statistical modeling are explored using machine-learning pipelines. EIS data from just two frequencies can accurately predict capacity, and interrogation shows that the optimal set of frequencies is not usually intuitive. Best results are achieved with an ensemble model, which predicts battery capacity with a mean absolute error of 1.9% on data from unobserved cells.

25 ENERGY STORAGE↗
DOE OSTI2021

Control of Catalyst Isomers Using an N -Phenyl-Substituted RN(CH 2 CH 2 P i Pr 2 ) 2 Pincer Ligand in CO 2 Hydrogenation and Formic Acid Dehydrogenation

A novel pincer ligand, i Pr PN Ph P [PhN- (CH 2 CH 2 P i Pr 2 ) 2 ], which is an analogue of the versatile MACHO ligand, iPr PN H P [HN(CH 2 CH 2 P i Pr 2 ) 2 ], was synthesized and characterized. The ligand was coordinated to ruthenium, and a series of hydride-containing complexes were isolated and characterized by NMR and IR spectroscopies, as well as X-ray diffraction. Comparisons to previously published analogues ligated by iPr PN H P and iPr PN Me P [CH 3 N(CH 2 CH 2 P i Pr 2 ) 2 ] illustrate that there are large changes in the coordination chemistry that occur when the nitrogen substituent of the pincer ligand is altered. For example, ruthenium hydrides supported by the iPr PN Ph P ligand always form the syn isomer (where syn/anti refer to the relative orientation of the group on nitrogen and the hydride ligand on ruthenium), whereas complexes supported by iPr PN H P form the anti isomer and complexes supported by iPr PN Me P form a mixture of syn and anti isomers. We evaluated the impact of the nitrogen substituent of the pincer ligand in catalysis by comparing a series of iPr PN R P (R = H, Me, Ph)-ligated ruthenium hydride complexes as catalysts for formic acid dehydrogenation and carbon dioxide (CO 2 ) hydrogenation to formate. The iPr PN Ph P-ligated species is the most active for formic acid dehydrogenation, and mechanistic studies suggest that this is likely because there are kinetic advantages for catalysts that operate via the syn isomer. In CO 2 hydrogenation, the iPr PN Ph P-ligated species is again the most active under our optimal conditions, and we report some of the highest turnover frequencies for homogeneous catalysts. Experimental and theoretical insights into the turnover-limiting step of catalysis provide a basis for the observed trends in catalytic activity. Additionally, the stability of our complexes enabled us to detect a previously unobserved autocatalytic effect involving the base that is added to drive the reaction. Overall, by modifying the nitrogen substituent on the MACHO ligand, we have developed highly active catalysts for formic acid dehydrogenation and CO 2 hydrogenation and also provided a framework for future catalyst development.

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

Synthesis and Characterization of Layered Actinide (U, Np, Pu) Oxide and Hydroxide Phases

Systematic structural comparisons across the early actinides remain limited by the scarcity of well-defined transuranic layered oxide and oxyhydroxide phases. Here, we report the synthesis and single-crystal characterization of new layered actinide compounds spanning U, Np, and Pu obtained under mild hydrothermal conditions in concentrated alkali hydroxide media. These include hydrated oxides α-Cs 2 U 2 O 7 •0.5H 2 O and Rb 2 An 2 O 7 •0.5H 2 O (An = Np, Pu), oxy-hydroxides Rb 6 [(AnO 2 ) 6 O 8 (OH) 2 ]•xH 2 O x = 0, 0.5 (An = U, Np) and Rb 4 [(UO 2 ) 5 O 6 (OH) 2 ]•2H 2 O, as well as nitrate-intercalated compounds Cs 6 [(AnO 2 ) 3 O 4 (OH) 2 ](NO 3 ) 2 (An = Np, Pu). Single-crystal X-ray diffraction studies reveal extended two-dimensional architectures constructed from edge- and vertex-sharing actinyl polyhedra, with systematic evolution in equatorial coordination, hydration, and anionic sheet topology across the U–Np–Pu series. Incorporation of nitrate anions within the interlayer region of Cs 6 [(AnO 2 ) 3 O 4 (OH) 2 ](NO 3 ) 2 establishes a previously unobserved structural motif in layered transuranic oxyhydroxides, demonstrating an additional pathway for anion-mediated framework stabilization. Correlation of crystallographic metrics with single-crystal Raman spectroscopy provides new vibrational benchmarks linking differences in An═O yl bond lengths to the equatorial coordination and the interstitial cations. These findings expand the structural hierarchy of layered actinide materials and address clarifying periodic trends governing topology, bonding, and vibrational signatures in high-valent 5ƒ oxide systems.

actinides↗
DOE OSTI2021

Atomic-Level Features for Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or other processes and accelerate the prediction of the chemical evolution by up to four order of magnitude. Such models go beyond the commonly employed potential energy surface fitting methods in that they are aimed purely at describing kinetic effects. So far, such kinetic models utilize molecular descriptions of reactions and have been constrained to only reproduce molecules previously observed in MD simulations. Therefore, these descriptions fail to predict the reactivity of unobserved molecules, for example in the case of large molecules or solids. In this work, we propose a new approach for the extraction of reaction mechanisms and reaction rates from MD simulations, namely the use of atomic-level features. Using the complex chemical network of hydrocarbon pyrolysis as example, it is demonstrated that kinetic models built using atomic features are able to explore chemical reaction pathways never observed in the MD simulations used to parametrize them, a critical feature to describe rare events. Atomic-level features are shown to construct reaction mechanisms and estimate reaction rates of unknown molecular species from elementary atomic events. Through comparisons of the model ability to extrapolate to longer simulation timescales and different chemical compositions than the ones used for parameterization, it is demonstrated that kinetic models employing atomic features retain the same level of accuracy and transferability as the use of features based on molecular species, while being more compact and parametrized with less data. We also find that atomic features can better describe the formation of large molecules enabling the simultaneous description of small molecules and condensed phases.

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

Ultrafast Yttrium Hydride Chemistry at High Pressures via Non-equilibrium States Induced by an X-ray Free Electron Laser

Controlling the formation and stoichiometric content of the desired phases of materials has become of central interest for a variety of fields. The possibility of accessing metastable states by initiating reactions by X-ray-triggered mechanisms over ultrashort time scales has been enabled by the development of X-ray free electron lasers (XFELs). Utilizing the exceptionally high-brilliance X-ray pulses from the EuXFEL, we report the synthesis of a previously unobserved yttrium hydride under high pressure, along with nonstoichiometric changes in hydrogen content as probed at a repetition rate of 4.5 MHz using time-resolved X-ray diffraction. Furthermore, exploiting non-equilibrium pathways, we synthesize and characterize a hydride in a Weaire–Phelan structure type at pressures as low as 125 GPa, predicted using a crystal structure search, with a hydrogen content of 4.0–5.75 hydrogens per cation, that is enthalpically metastable on the convex hull.

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

Resonance-Enhanced Excitation of Interlayer Vibrations in Atomically Thin Black Phosphorus

The strength of interlayer coupling critically affects the physical properties of 2D materials such as black phosphorus (BP), where the electronic structure depends sensitively on layer thickness. Rigid-layer vibrations reflect directly the interlayer coupling strength in 2D van der Waals solids, but measurement of these characteristic frequencies is made difficult by sample instability and small Raman scattering cross sections in atomically thin elemental crystals. Here, we overcome these challenges in BP by performing resonance-enhanced low-frequency Raman scattering under an argon-protective environment. Interlayer breathing modes for atomically thin BP were previously unobservable under conventional (nonresonant) excitation but became strongly enhanced when the excitation energy matched the sub-band electronic transitions of few-layer BP, down to bilayer thicknesses. The measured out-of-plane interlayer force constant was found to be 10.1 × 10 19 N/m 3 in BP, which is comparable to graphene. Accurate characterization of the interlayer coupling strength lays the foundation for future exploration of BP twisted structures and heterostructures.

interlayer interaction↗
DOE OSTI2023

U–C Bond Insertion, Ring-Opening, and C–H Activation in a Uranium Bis(diisopropylamino)cyclopropenylidene (BAC) Adduct

Reaction of [U(NR 2 ) 3 ] (R = SiMe 3 ) with 1 equiv of bis(diisopropylamino)cyclopropenylidene (BAC) in Et 2 O results in the formation of [(NR 2 ) 3 U(BAC)] (1), which can be isolated in modest yields. Thermolysis of 1 in C 6 D 6 at 85 °C results in the formation of the ring-opened U(IV) product, [(NR 2 ) 2 U{N(R)(SiMe 2 CH=C(NiPr 2 )C(NiPr 2 )=CH)}] (2), which can be isolated in low yields. Mechanistic studies suggest that the formation of 2 proceeds via dissociation of BAC from 1 to regenerate [U(NR 2 ) 3 ], which converts into [U{N(R)(SiMe 2 CH 2 )}(NR 2 ) 2 ] at the elevated temperatures. BAC then inserts into the U–C bond of [U{N(R)(SiMe 2 CH 2 )}(NR 2 ) 2 ] to generate a cyclopropenyl intermediate, which undergoes ring opening and C–H activation to afford the final product, 2. We hypothesize that the ring-opening generates an unobserved carbene intermediate. Notably, thermolysis of a 1:1 mixture of independently prepared [U{N(R)(SiMe 2 CH 2 )}(NR 2 ) 2 ] and BAC results in clean formation of 2, providing strong support for the proposed mechanism. The formulations of both 1 and 2 were confirmed by X-ray crystallography. Finally, theoretical calculations indicate that the hypothesized uranium carbene intermediate features strong U–C bonding, potentially with some carbyne character in the electronic structure.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Understanding the Reactivity and Decomposition of a Highly Active Iron Pincer Catalyst for Hydrogenation and Dehydrogenation Reactions

The iron pincer complex ( iPr PNP)Fe(H)(CO) (1, iPr PNP – = N(CH 2 CH 2 PiPr 2 ) 2 - ) is an active (pre)catalyst for many hydrogenation and dehydrogenation reactions. This is in part because 1 can reversibly add H 2 across the iron-amide bond to form ( iPr PN H P)Fe(H) 2 (CO) (2, iPr PN H P = HN(CH 2 CH 2 P i Pr 2 ) 2 ). However, rapid decomposition limits the catalytic performance of 1 and related complexes. We explored the pathways through which catalytic intermediates related to 1 and 2 undergo decomposition. This involved characterizing the unstable and previously unobserved complexes [( iPr PN H P)Fe(H)(CO)(L)] + (5-L; L = THF or N 2 ) and [( iPr PN H P)Fe(H)(H 2 )(CO)] + (8), which are proposed as intermediates when 1 and 2 are used as catalysts. Compound 8 was synthesized through the reaction of ( iPr PN H P)Fe(H)(CO)(PF 6 ) (6) with H 2 , and the solid-state structure was established using both X-ray and neutron diffraction. As part of our studies on understanding the reactivity of 5-L, we determined the thermodynamic hydricity of 2, which is valuable for predicting its reactivity as a hydride donor. Further, it is shown that species such as 5-L decompose to the same inactive species observed in catalysis using 1 and 2, and theoretical calculations suggest that this likely occurs via a bimolecular pathway. To provide support for this hypothesis, we isolated the dimeric species [{( iPr PN H P)Fe(H)(CO)} 2 {μ-CN}] + (11) and [{( iPr PN H P)Fe(H)(CO)} 2 {μ-OC(H)O}] + (12), which show that catalytic intermediates ligated by iPr PN H P can form dimeric species. Our results provide general strategies for improving catalysis using 1 and 2, and we used this information to rationally increase the performance of 1 in formic acid dehydrogenation.

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

Expanding the Landscape of Dual Action Antifolate Antibacterials through 2,4-Diamino-1,6-dihydro-1,3,5-triazines

Antibiotics that operate via multiple mechanisms of action are a promising strategy to combat growing resistance. Previous studies have shown that dual action antifolates formed from a pyrroloquinazolinediamine core can inhibit the growth of bacterial pathogens without developing resistance. Here, in this work, we expand the scope of dual action antifolates by repurposing the 2,4-diamino-1,6-dihydro-1,3,5-triazine (DADHT) cycloguanil scaffold to a variety of derivatives designed to inhibit dihydrofolate reductase (DHFR) and disrupt bacterial membranes. Dual mechanism DADHTs have activity against a variety of target pathogens, including Mycobacterium tuberculosis, Mycobacterium abscessus, and Pseudomonas aeruginosa, among other ESKAPEE organisms. Through X-ray crystallography, we confirmed engagement of the Escherichia coli DHFR target and found that some DADHTs stabilize a previously unobserved conformation of the enzyme but, broadly, bind in the occluded conformation. Using in vitro inhibition of purified E. coli and Staphylococcus aureus DHFR and disruption of E. coli membranes, we determined that alkyl substitution of dihydrotriazine at the 6-position best optimizes the DADHT's two mechanisms of action. By employing both mechanisms, the DADHT spectrum of activity was extended beyond the scope of traditional antifolates. Finally, we are optimistic that the dual mechanism approach, particularly through the action of antifolates, offers a unique means of combating hard-to-treat bacterial infections.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Writing and Detecting Topological Charges in Exfoliated Fe 5– x GeTe 2

Fe 5–x GeTe 2 is a promising two-dimensional (2D) van der Waals (vdW) magnet for practical applications, given its magnetic properties. These include Curie temperatures above room temperature, and topological spin textures–TST (both merons and skyrmions), responsible for a pronounced anomalous Hall effect (AHE) and its topological counterpart (THE), which can be harvested for spintronics. Here, we show that both the AHE and THE can be amplified considerably by just adjusting the thickness of exfoliated Fe 5–x GeTe 2 , with THE becoming observable even in zero magnetic field due to a field-induced unbalance in topological charges. Using a complementary suite of techniques, including electronic transport, Lorentz transmission electron microscopy, and micromagnetic simulations, we reveal the emergence of substantial coercive fields upon exfoliation, which are absent in the bulk, implying thickness-dependent magnetic interactions that affect the TST. We detected a “magic” thickness t ≈ 30 nm where the formation of TST is maximized, inducing large magnitudes for the topological charge density (~6.45 × 10 20 cm –2 ), and the concomitant anomalous (ρ xy A,max ≃22.6 μΩ cm) and topological (ρ xy u,T 1≃5 μΩ cm) Hall resistivities at T ≈ 120 K. These values for ρ xy A,max and ρ xy u,T are higher than those found in magnetic topological insulators and, so far, the largest reported for 2D magnets. Furthermore, the hitherto unobserved THE under zero magnetic field could provide a platform for the writing and electrical detection of TST aiming at energy-efficient devices based on vdW ferromagnets.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Size-Resolved Shape Evolution in Inorganic Nanocrystals Captured via High-Throughput Deep Learning-Driven Statistical Characterization

Precise size and shape control in nanocrystal synthesis is essential for utilizing nanocrystals in various industrial applications, such as catalysis, sensing, and energy conversion. However, traditional ensemble measurements often overlook the subtle size and shape distributions of individual nanocrystals, hindering the establishment of robust structure–property relationships. In this study, we uncover intricate shape evolutions and growth mechanisms in Co 3 O 4 nanocrystal synthesis at a subnanometer scale, enabled by deep-learning-assisted statistical characterization. By first controlling synthetic parameters such as cobalt precursor concentration and water amount then using high resolution electron microscopy imaging to identify the geometric features of individual nanocrystals, this study provides insights into the interplay between synthesis conditions and the sizedependent shape evolution in colloidal nanocrystals. Utilizing population-wide imaging data encompassing over 441,067 nanocrystals, we analyze their characteristics and elucidate previously unobserved size-resolved shape evolution. This high-throughput statistical analysis is essential for representing the entire population accurately and enables the study of the size dependency of growth regimes in shaping nanocrystals. Our findings provide experimental quantification of the growth regime transition based on the size of the crystals, specifically (i) for faceting and (ii) from thermodynamic to kinetic, as evidenced by transitions from convex to concave polyhedral crystals. Additionally, we introduce the concept of an “onset radius,” which describes the critical size thresholds at which these transitions occur. This discovery has implications beyond achieving nanocrystals with desired morphology; it enables finely tuned correlation between geometry and material properties, advancing the field of colloidal nanocrystal synthesis and its applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments

Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primarily focus on the optimization of a predefined target; while accelerating this goal, such an approach limits the discovery of unexpected or unknown physical phenomena. Here, we introduce a novel framework, INS 2 ANE (Integrated Novelty Score−Strategic Autonomous Non-Smooth Exploration), to enhance the discovery of novel phenomena in autonomous microscopy experimentation. Our method integrates two key components: (1) a novelty scoring system that evaluates the uniqueness of experimental results and (2) a strategic sampling mechanism that promotes exploration of under-sampled regions even if they appear less promising by conventional criteria. We validate this approach on a preacquired data set with a known ground truth comprising of image−spectral pairs. We further implement the process on autonomous scanning probe microscopy experiments. INS 2 ANE significantly increases the diversity of explored phenomena in comparison to conventional optimization routines, enhancing the likelihood of discovering previously unobserved phenomena. These results demonstrate the potential for autonomous microscopy experiments to enhance the scientific discovery by navigating complex experimental spaces to uncover novel phenomena.

Materials↗