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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Counterdiabatic Driving with Performance Guarantees

Counterdiabatic (CD) driving has the potential to speed up adiabatic quantum state preparation by suppressing unwanted excitations. However, existing approaches either require intractable classical computations or are based on approximations that do not have performance guarantees. We propose and analyze a nonvariational, system-agnostic CD expansion method and analytically show that it converges exponentially quickly in the expansion order. In finite systems, the required resources scale inversely with the spectral gap, which we argue is asymptotically optimal. To extend our method to the thermodynamic limit and suppress errors stemming from high-frequency transitions, we leverage finite-time adiabatic protocols. In particular, we show that a time determined by the quantum speed limit is sufficient to prepare the desired ground state, without the need to optimize the adiabatic trajectory. Numerical tests of our method on the quantum Ising chain show that our method can outperform state-of-the-art variational CD approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A Lakehouse Architecture for the Management and Analysis of Heterogeneous Data for Biomedical Research and Mega-biobanks

Data Lakehouse is a new paradigm in data architectures that embodies and integrates already established concepts for the systematic management of disparate, large-scale data – a data lake for heterogeneous data management, use of open standards for high-performance querying, and systematic maintenance of the data "freshness". In addition to being a new concept, the data lakehouse is also still a conceptual construct. Many projects that use the lakehouse require maturing, empirical studies, and specific implementations. In this paper, we present our implementation of the data lakehouse concept in a biomedical research and health data analytics domain, and we discuss the implementation of some unique and novel features such as support for specialized access controls in support of HIPAA regulation and IRB protocols, and support for the FAIR standard.

Begoli, Edmon↗
DOE OSTI2025

Detection limits for laser absorption spectroscopy of Li in laser ablation plumes

A high-sensitivity laser absorption spectroscopy (LAS) method is demonstrated for rapid and non-contact analysis of Li in solids. Glass samples with Li concentrations ranging from 1-500 ppm by mass are ablated in 5 Torr air, and time-resolved Li atomic absorption is measured using a tunable laser near 671 nm. Significant improvements in analytical performance over prior laser-induced breakdown techniques are demonstrated. Here, a single-shot limit of detection (LOD) of 180 ppb is shown for fixed wavelength operation, improving to 6 ppb with averaging over 1000 ablation shots (100 s acquisition time). Isotope-resolved Li absorption spectra are measured with a 17 ppb LOD in 40 s. Methods for optimizing LOD based on noise/averaging properties of LAS experiments in LA plumes are discussed.

(020.3260) Isotope shifts↗
DOE OSTI2020

Characteristics of flow through randomly packed impermeable and permeable particles using pore resolved simulations

Pore resolved simulations are performed to study the mean flow characteristics in porous media formed by random distribution of impermeable and permeable particles. Here, permeability of the medium and reactive surface areas are analyzed for a range of solid fractions, packing patterns and flow rates. The results are compared with models presented in the literature and with simulations of flow through ordered packings. Permeability of a randomly packed porous medium is found to depend on the heterogeneous distribution of porosity which results from particle agglomeration and is typically ignored by simpler models. The reactive surface area is dependent on the flow field at pore scale in addition to geometry. Moreover, the wake formed downstream of the particles at moderately high flow rates also affects the reactive surface area. Similar analysis is also performed by assuming particles to be permeable to account for dual scale porosity relevant for various engineering applications.

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

Identifying High-Performance Metal–Organic Frameworks for Low-Temperature Oxygen Recovery from Helium by Computational Screening

Metal–organic frameworks (MOFs) are an important class of porous crystalline materials for applications ranging from gas adsorption and separation to catalysis. There are thousands of potential MOFs available for separation applications. Here, we developed a computational approach to screen MOFs for the separation of oxygen–helium mixtures at low temperatures (100–200 K), conditions that were motivated by issues associated with propulsion in space-based settings. We used detailed molecular simulations for a small number of MOFs to develop screening methods that were then used to estimate the optimum temperatures for separations using pressure swing adsorption for 2932 MOFs from the CoRE MOF database and the swing capacity and oxygen–helium selectivity at these temperatures. We used the stability of the best-performing structures in the presence of moisture as a means to provide a short list of high-performance materials. In addition to identifying specific materials for oxygen–helium separations, this approach could prove useful for selecting adsorbents for other gas separations.

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

In Situ Phosphatizing of Triphenylphosphine Encapsulated within Metal–Organic Frameworks to Design Atomic Co 1 –P 1 N 3 Interfacial Structure for Promoting Catalytic Performance

The engineering coordination environment offers great opportunity in performance tunability of isolated metal single-atom catalysts. For the most popular metal–N x (MN x ) structure, the replacement of N atoms by some other atoms with relatively weak electronegativity has been regarded as a promising strategy for optimizing the coordination environment of an active metal center and promoting its catalytic performance, which is still a challenge. Herein, we proposed a new synthetic strategy of an in situ phosphatizing of triphenylphosphine encapsulated within metal–organic frameworks for designing atomic Co 1 –P 1 N 3 interfacial structure, where a cobalt single atom is costabilized by one P atom and three N atoms (denoted as Co-SA/P-in situ). In the acidic media, the Co-SA/P-in situ catalyst with Co 1 –P 1 N 3 interfacial structure exhibits excellent activity and durability for the hydrogen evolution reaction (HER) with a low overpotential of 98 mV at 10 mA cm –2 and a small Tafel slope of 47 mV dec –1 , which are greatly superior to those of catalyst with Co 1 –N 4 interfacial structure. We discover that the bond-length-extended high-valence Co 1 –P 1 N 3 atomic interface structure plays a crucial role in boosting the HER performance, which is supported by in situ X-ray absorption fine structure (XAFS) measurements and density functional theory (DFT) calculation. With this work, we hope to promote the development of high performance metal single-atom catalysts.

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

New Trick for an Old Dog: From Prediction to Properties of “Hidden Clathrates” Ba 2 Zn 5 As 6 and Ba 2 Zn 5 Sb 6

The zinc–antimony phase space has been heavily investigated due to the structural complexity and abundance of high-performing thermoelectric materials. Consequentially, the desire to use zinc and antimony as framework elements to encage rattling cations and achieve phonon-glass-electron-crystal-type properties has remained an enticing goal with only two alkali metal clathrates to date, Cs 8 Zn 18 Sb 28 and K 58 Zn 122 Sb 207 . Guided by Zintl electron-counting predictions, here we explored the Ba–Zn–Pn (Pn = As, Sb) phase space proximal to the expected composition of the type-I clathrate. In situ powder X-ray diffraction studies revealed two “hidden” compounds which can only be synthesized in a narrow temperature range. The ex situ synthesis and crystal growth unveiled that instead of type-I clathrates, compositionally close but structurally different new clathrate-like compounds formed, Ba 2 Zn 5 As 6 and Ba 2 Zn 5 Sb 6 . These materials crystallize in a unique structure, in the orthorhombic space group Pmna with the Wyckoff sequence i 2 h 6 gfe. Single-phase synthesis enabled the exploration of their transport properties. Rattling of the Ba cations in oversized cages manifested low thermal conductivity, which, coupled with the high Seebeck coefficients observed, are prerequisites for a promising thermoelectric material. Potential for further optimization of the thermoelectric performance by aliovalent doping was computationally analyzed.

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

Economic Extraction and Recovery of REEs and Production of Clean Value-Added Products from Low-Rank Coal Fly Ash

The University of North Dakota (UND) Energy & Environmental Research Center (EERC) teamed with Pacific Northwest National Laboratory (PNNL) , the North Dakota Industrial Commission Lignite Research Program, and commercial partners Basin Electric Power Cooperative, Great River Energy, and Southern Company to execute a Cooperative Agreement funded by the U.S. Department of Energy’s (DOE’s) National Energy Technology Laboratory (NETL) focused on identifying unique pathways and pretreatments to extract rare-earth elements (REEs) from low-rank coal (LRC) ash in a more economical and environmentally benign manner than current methods. The EERC drew upon the unique and deep knowledge of the team regarding LRC geochemistry, ash transformation mechanisms during combustion, and fly ash chemistry in the approach to understand the portioning of REEs in LRC ash. A comprehensive characterization effort was undertaken to fully establish the form, associations, and partitioning of the REEs and other elements/minerals of interest in fly ash, as well as the ash chemistry, mineralogy, and morphology. Using this information, the team tested methods of REE extraction to take advantage of the unique and advantageous properties of LRC ash. Multiple complementary approaches were evaluated that combined both novel and proven methods to develop an extractive process for REEs and other high-value metals from LRC ash that provide technological and economic progress on the current state of the art. Methodologies were also evaluated for the potential to synergistically remove toxic metals while extracting other high-value metals from the ash, generating a clean, safe ash material as a value-added product. This would eliminate waste and offer significant additional revenue potential. Based on laboratory-scale testing, an initial high-level technical and economic analysis to estimate operating expenses and product revenues to guide future phases of technology development was implemented. By focusing on minimizing process steps and consumptive use of extraction solutions, a tunable, economically viable process for REE extraction from LRC ash was developed. The tunable process has the ability to be adjusted to adapt to the differing ash chemical and physical properties that are characteristic of LRC ash. This is key to deployment as a commercial process. In demonstrating the process, the EERC was able to illustrate mixed REE concentration greater than the goal of 2 wt%. High-level economic analysis of the process with LRC ash of moderate REE levels demonstrated the potential of the process, but recovery of just the REEs was insufficient to cover operational costs. With the additional extraction of other high-value metals found in LRC ash, the process economics approach would break even, and it is anticipated that with process optimization, the developed process could potentially be economically sound. The same economic analysis performed utilizing LRC ash with high levels of REEs showed the recovery of the REEs alone would make the process economically viable even without further optimization.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Ground and excited state gradients with end-to-end differentiable semiempirical quantum chemistry

Accurate and efficient gradients of molecular energy with respect to nuclear degrees of freedom are essential for geometry optimization and molecular dynamics, including simulations that go beyond the Born–Oppenheimer regime. A common approach involves deriving analytical formulas for new electronic structure methods, which is often conceptually difficult and requires tedious coding. Here, we implement analytical, semi-numerical, and automatic differentiation (AD)-based gradient pathways for semiempirical Hamiltonian models in the PYSEQM software package, leveraging both graphics processing unit (GPU) and central processing unit (CPU) architectures. We further extend these capabilities to excited states calculated using the configuration interaction singles and time-dependent Hartree–Fock ansätze. We benchmark wall time, peak memory usage, and accuracy across three molecular families of varying chemical complexity, including systems of up to a thousand atoms. For ground-state simulations, analytical and AD gradients achieve near-identical GPU runtimes, while semi-numerical gradients are slower on GPU but remain competitive on CPU. For excited states, both analytical and custom AD approaches using implicit differentiation show similar performance and low memory requirements, whereas gradients with full AD are memory-limited. AD gradients match analytical ones in accuracy across all tested systems, aided by a quaternion-based diatomic frame rotation for two-center quantities that ensures smooth energy surfaces. Overall, automatic differentiation emerges as a practical alternative to analytical gradients in semiempirical quantum chemistry, offering high accuracy while allowing seamless integration in AI-driven workflows and popular packages, such as PyTorch and JAX. Our results provide actionable guidance for selecting optimal gradient strategies in large-scale ground- and excited-state molecular dynamics simulations.

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

CODEX weak lensing mass catalogue and implications on the mass–richness relation

The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at 0.35 < z < 0.65. It was selected from ROSAT data in the 10 000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX programme on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ lensfit shape measurement and perform a conservative colour–space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large-scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope α, normalization β, and scatter σln λ|μ of our richness–mass scaling relation model in log-space: ${\langle {\rm In}\,\, \lambda\!\!\mid\!\!\mu\rangle = \alpha\mu + \beta,} $ with μ = ln (M 200c /M piv ), and M piv = 10 14.81 M ⊙ . We find a slope $\alpha = 0.49^{+0.20}_{-0.15}$, normalization $\exp (\beta) = 84.0^{+9.2}_{-14.8}$, and $\sigma _{\ln \lambda | \mu } = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness–mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range (0.0 < z < 0.65) and with different cluster selection (X-ray, Sunyaev–Zeldovich, and optical).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Global Experiences with HPC Operational Data Measurement, Collection and Analysis

As we move into the exascale era, supercomputers grow larger, denser, more heterogeneous, and ever more complex. Operating such machines reliably and efficiently requires deep insight into the operational parameters of the machine itself as well as its supporting infrastructure. To fulfill this need, early adopter sites have started the development and deployment of Operational Data Analytics (ODA) frameworks allowing the continuous monitoring, archiving, and analysis of near realtime performance data from the machine and infrastructure levels, providing immediately actionable information for multiple operational uses. To understand their ODA goals, requirements, and use cases, we have conducted a survey among eight early adopter sites from the US, Europe, and Japan that operate top 50 high-performance computing systems. We have assessed the technologies leveraged to build their ODA frameworks, identified use cases and other push and pull factors that drive the sites' ODA activities, and report on their operational lessons.

Ott, Michael↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Development and Validation of a Non-Invasive, Chairside Oral Cavity Cancer Risk Assessment Prototype Using Machine Learning Approach

Oral cavity cancer (OCC) is associated with high morbidity and mortality rates when diagnosed at late stages. Early detection of increased risk provides an opportunity for implementing prevention strategies surrounding modifiable risk factors and screening to promote early detection and intervention. Historical evidence identified a gap in the training of primary care providers (PCPs) surrounding the examination of the oral cavity. The absence of clinically applicable analytical tools to identify patients with high-risk OCC phenotypes at point-of-care (POC) causes missed opportunities for implementing patient-specific interventional strategies. This study developed an OCC risk assessment tool prototype by applying machine learning (ML) approaches to a rich retrospectively collected data set abstracted from a clinical enterprise data warehouse. We compared the performance of six ML classifiers by applying the 10-fold cross-validation approach. Accuracy, recall, precision, specificity, area under the receiver operating characteristic curve, and recall–precision curves for the derived voting algorithm were: 78%, 64%, 88%, 92%, 0.83, and 0.81, respectively. The performance of two classifiers, multilayer perceptron and AdaBoost, closely mirrored the voting algorithm. Integration of the OCC risk assessment tool developed by clinical informatics application into an electronic health record as a clinical decision support tool can assist PCPs in targeting at-risk patients for personalized interventional care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Ultrastable Carboxyl–Functionalized Pore–Space–Partitioned Metal–Organic Frameworks for Gas Separation

Isoreticular chemistry, which enables property optimization by changing compositions without changing topology, is a powerful synthetic strategy. One of the biggest challenges facing isoreticular chemistry is to extend it to ligands with strongly coordinating substituent groups such as unbound –COOH, because competitive interactions between such groups and metal ions can derail isoreticular chemistry. It is even more challenging to have an isoreticular series of carboxyl-functionalized MOFs capable of encompassing chemically disparate metal ions. Furthermore, with the simultaneous introduction of carboxyl functionalization and pore space partition, a family of carboxyl-functionalized materials is developed in diverse compositions from homometallic Cr 3+ and Ni 2+ to heterometallic Co 2+ /V 3+ , Ni 2+ /V 3+ , Co 2+ /In 3+ , Co 2+ /Ni 2+ . Cr-MOFs remain highly crystalline in boiling water. Unprecedentedly, one Cr-MOF can withstand the treatment cycle with 10m NaOH and 12m HCl, allowing reversible inter-conversion between unbound –COOH acid form and –COO – base form. These materials exhibit excellent sorption properties such as high uptake capacity for CO 2 (100.2 cm 3 g –1 ) and hydrocarbon gases (e.g., 142.1 cm 3 g –1 for C 2 H 2 , 110.5 cm 3 g –1 for C 2 H 4 ) at 1 bar and 298K, high benzene/cyclohexane selectivity (up to ≈40), and promising separation performance for gas mixtures such as C 2 H 2 /CO 2 and C 2 H 2 /C 2 H 4 .

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

High-Performance All-Polymer Solar Cells and Photodetectors Enabled by a High-Mobility n-Type Polymer and Optimized Bulk-Heterojunction Morphology

All-polymer solar cells (all-PSCs) and all-polymer photodetectors (all-PPDs) are promising for application in flexible electronics, but their performance is greatly limited by the lack of polymer acceptors and the difficulties in morphology control. Herein, we report the use of a high-mobility n-type polymer semiconductor, PNDI-DTBT, for fabricating high-performance all-PSCs and all-PPDs. By pairing PNDI-DTBT with a matched polymer donor, a prominent power conversion efficiency of 8.5% was obtained in all-PSCs, demonstrating the great potential of high-mobility n-type polymers with a conventional donor–acceptor skeleton for photovoltaic application. Moreover, all-PPDs with a low dark current density of 1.32 × 10 –8 A cm –2 at –0.1 V bias and a high specific detectivity of 4.77 × 10 12 Jones were achieved, which belong to the best results of organic photodetectors. Morphology investigations revealed that the formation of a bicontinuous interpenetrating network with optimal phase separation scale, high domain purity, and preferential vertical composition distribution in the bulk-heterojunction active layer contribute to the remarkable device performance. Furthermore, these results suggest that combining high-mobility n-type polymers and morphology optimization is fruitful to achieving high-performance all-PSCs and all-PPDs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Influence of Ordered Mesoporous Oxides in Plasma-Assisted Ammonia Synthesis

Widespread implementation of dielectric barrier discharge (DBD)-assisted NH 3 synthesis, a nascent technology operating under sustainable, ambient conditions, is hindered by low energy yields due to, in part, poor fundamental understanding. Porous oxides used to support metal nanoparticle catalysts have shown significant energy yield contributions for DBD-assisted NH 3 synthesis even without metal. Using an AC-powered, coaxial, single-stage reactor at 16 kV with equimolar (N 2 /H 2 ) feed, we measured NH 3 synthesis rates in the presence of different nonordered oxides, ordered SiO 2 structures (SBA-15 and MCM-41), and ordered Al-incorporated analogues (γ-Al 2 O 3 -coated with varying Al-loadings and Al-substitution, respectively: Al 2 O 3 -SBA-15 and Al-MCM-41). We systematically quantified NH 3 energy yield dependence on pore structures and material identities (i.e., ordered pores and Al incorporation) known to facilitate higher DBD-assisted NH 3 synthesis rates. SBA-15 displayed a higher steady-state energy yield than MCM-41, indicating that framework type is a crucial factor, with both ordered porous systems outperforming fumed SiO 2 . 10 wt % Al maximized in situ NH 3 uptake among the various Al loadings, exhibiting a higher steady-state energy yield and similar power to SBA-15. However, Al-MCM-41 had a similar steady-state energy yield and lower power than MCM-41, likely due to the extended γ-Al 2 O 3 surface that has a dielectric constant higher than that of SiO 2 . Both Al-incorporated analogues benefit from surface acid sites that can adsorb NH 3 in situ, resulting in higher overall NH 3 energy yields than that of their parent ordered SiO 2 . Al 2 O 3 -SBA-15 shielded more NH 3 than Al-MCM-41, likely due to a higher acid site density than the acid site identity. Furthermore, Al incorporation via γ-Al 2 O 3 coating more successfully improves the NH 3 energy yield; together with the high-performing ordered framework, these analogues are potential metal catalyst supports with promising energy yields for DBD-assisted synthesis of NH 3 and other chemicals.

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

Photogating-driven enhanced responsivity in a few-layered ReSe 2 phototransistor

A wide variety of two-dimensional (2D) metal dichalcogenide compounds have recently attracted much research interest due to their very high photoresponsivities (R) making them excellent candidates for optoelectronic applications. High R in 2D photoconductors is associated with trap state dynamics leading to a photogating effect, which is often manifested by a fractional power dependence (γ) of the photocurrent (I ph ) at an effective illumination intensity (P eff ). Furthermore, we present photoconductivity studies as a function of gate voltages, over a wide temperature range (20 K to 300 K) of field-effect transistors fabricated using thin layers of mechanically exfoliated Rhenium Diselenide (ReSe 2 ). We obtain very high responsivities R ~ 16500 A/W and external quantum efficiency (EQE) ~ 3.2 × 106% (at 140 K, V g = 60 V and P eff = 0.2 nW). A strong correlation between R and γ was established by investigating the dependence of these two quantities at various gate voltages and over a wide range of temperatures. Such correlations indicate the importance of trap state mediated photogating and its role in promoting high photo-responsivities in these materials. We believe such correlations can offer valuable insights for the design and development of high-performance photoactive devices using 2D materials.

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

Microstructure–Property Correlation in a Laser Powder Bed Fusion Processed High-Strength AF-9628 Steel

Laser powder bed fusion additive manufacturing (LPBF-AM) of a low-alloy, high-performance AF-9628 steel results in exceptionally high strength and good ductility. The reasons for such mechanical properties are investigated through detailed microscopy performed at several length scales. Thus, the characterization of melt pool, porosity, grain morphology, phases, and dislocations is performed in the as-printed material. The as-printed material consists of only 0.004 vol% of uniformly distributed porosity, single-phase martensitic laths with an average lath size of ≈2.5 μm, the absence of carbides indicating interstitial trapping of C atom, and high dislocation density in the martensitic laths. Experimental data through microscopy are then fed in analytical models for calculating strengthening contributions from various strengthening mechanisms. Calculated yield strength agrees well with experimentally determined value, and therefore, activation of various strengthening mechanisms is established in as-printed AF-9628.

36 MATERIALS SCIENCE↗