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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 199 records · Page 11

Dual C–H functionalization of polyolefins for covalent adaptable network formation via cooperative electrolysis

The increasing demand for carbon fibre-reinforced polymer composites with polyolefin thermoset matrices will lead to the generation of large volumes of low molecular weight waste oligomers during the fibre recovery process. To address this challenge, we present a cooperative electrolytic dual C–H bond functionalization strategy for the one-step installation of two key functional groups essential for dynamic linkages of these deconstructed oligomers. Through direct competition studies, we reveal the predominance of tertiary allylic C–H activation along the complex, branched oligomer backbone. The resulting difunctionalized oligomers form covalently adaptable networks with exceptional circularity. By establishing a sustainable pathway for upcycling deconstructed oligomers from carbon fibre-reinforced polymer fibre recovery, this strategy introduces thermoset materials derived directly from waste. Here, it advances sustainable manufacturing practices, contributing to a net-zero waste synthetic ecosystem, and highlights the prospects of mediated electrolysis in macromolecular transformations.

Electrocatalysis↗

Bioconversion of self-neutralized chemically depolymerized lignin streams into polyhydroxyalkanoates

Lignin is a chemically complex, diverse, and abundant plant polymer mainly composed of aromatic monomers. These aromatic monomers make lignin a potential source of aromatics and a viable substitute for petrochemically-derived aromatics. However, the structural recalcitrance of lignin requires harsh reagents from the chemical process and expensive catalysts for effective depolymerization. This chemical process often results in poor yields of chemical intermediate mixtures of varying bioavailability and/or toxicity. Furthermore, the cost of additional reagents required to separate or detoxify these intermediates makes processing lignin impractical. We report progress towards the use of such chemically depolymerized lignin streams by employing bacterial strains to produce polyhydroxyalkanoates (PHA). PHAs are a group of biodegradable microbial polyesters that have potential as a replacement for petroleum-based plastics. In this study we utilized two distinct lignin streams obtained after chemical depolymerization of lignin under alkaline and acidic pH in the presence of catalysts. We mixed the alkali-treated depolymerized stream with the acid-treated depolymerized stream to create a solution of neutral-pH chemically depolymerized lignin (CDL). We found moderate to substantial growth of both native and non-native PHA producers on the mixture of CDL as well as its aliphatic and aromatic components. PHA was detected by Sudan Black B staining in C. necator H16, P. putida KT2440, and E. coli LSBJ STQKAB grown on mixed CDL as the sole carbon source. For C. necator H16 and E. coli LSBJ STQKAB we found that PHA content was greater when grown on mixed CDL when compared to their preferred carbon source by GC-FID quantification. Our study provided progress towards a cost-competitive, sustainable, and industrially relevant use for lignin.

Winkler, Gordon L. W. [Univ. of Wisconsin, Madison↗

A bloom of a single bacterium shapes the microbiome during outdoor diatom cultivation collapse

Algae-dominated ecosystems are fundamentally influenced by their microbiome. We lack information on the identity and function of bacteria that specialize in consuming algal-derived dissolved organic matter in high algal density ecosystems such as outdoor algal ponds used for biofuel production. Here, we describe the metagenomic and metaproteomic signatures of a single bacterial strain that bloomed during a population-wide crash of the diatom, Phaeodactylum tricornutum, grown in outdoor ponds. 16S rRNA gene data indicated that a single Kordia sp. strain (family Flavobacteriaceae) contributed up to 93% of the bacterial community during P. tricornutum demise. Kordia sp. expressed proteins linked to microbial antagonism and biopolymer breakdown, which likely contributed to its dominance over other microbial taxa during diatom demise. Analysis of accompanying downstream microbiota (primarily of the Rhodobacteraceae family) provided evidence that cross-feeding may be a pathway supporting microbial diversity during diatom demise. In situ and laboratory data with a different strain suggested that Kordia was a primary degrader of biopolymers during algal demise, and co-occurring Rhodobacteraceae exploited degradation molecules for carbon. An analysis of 30 Rhodobacteraceae metagenome assembled genomes suggested that algal pond Rhodobacteraceae commonly harbored pathways to use diverse carbon and energy sources, including carbon monoxide, which may have contributed to the prevalence of this taxonomic group within the ponds. These observations further constrain the roles of functionally distinct heterotrophic bacteria in algal microbiomes, demonstrating how a single dominant bacterium, specialized in processing senescing or dead algal biomass, shapes the microbial community of outdoor algal biofuel ponds.

Kordia↗

Molecular structures of residual solvent in polyacrylonitrile based electrolytes: Implications for conductivity and stability

Lithium-ion batteries increasingly play significant roles in modern technologies; however, increased energy density also raises concerns about electrolyte safety. Traditional electrolytes that use volatile organic solvents face risks of thermal runaways and fires from electrode shorting. In response, polymer-based solid electrolytes have been developed for replacement. Polyacrylonitrile (PAN) is a promising fire-resistant component for electrolyte fabrication, but its limited solubility necessitates using low-volatility solvents, which are notoriously difficult to remove in subsequent drying processes. Here, we use femtosecond two-dimensional infrared spectroscopy to provide an in-depth understanding of how residual solvent from processing affects the molecular structures and dynamics within a polymer electrolyte. To this end, linear and nonlinear infrared spectroscopies are employed to interrogate the molecular interactions in PAN-based electrolytes containing various contents of N,N-dimethylformamide (DMF). We show that the amount of DMF within the PAN electrolyte affects the Li+ structure. Further, the coordination can proceed through the carbonyl group and/or the amide nitrogen to form antiparallel structures with the nitrile groups of PAN through dipole–dipole interactions. The free motion of DMF is drastically inhibited upon interaction with Li+ and PAN, which decreases the ionic conductivity and potentially affects the stability (resistance toward removal and chemical decomposition). These findings have implications for the design and processing of solid polymer electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nickel Sulfide-Nanowire-Filled Carbon Nanotubes as an Efficient Overall Water Splitting Electrocatalyst

Pursuing stable, efficient, and cost-effective nanostructured bifunctional electrocatalysts is crucial for advancing the electrochemical water splitting process and enabling clean hydrogen energy production. In recent years, considerable efforts have focused on developing highly efficient and durable commercial electrocatalysts for the oxygen evolution reaction (OER) and overall water splitting (OWS). This research introduces an OWS electrocatalyst-nickel sulfide-filled carbon nanotubes grown on a carbon cloth substrate (Ni 3 S 2 @CNTs/CC), synthesized via a one-step in-situ process. The synergistic integration of metal sulfide (Ni 3 S 2 ) and carbon nanotubes provides abundant active sites for catalytic reactions, ensuring a robust composite nanostructure with enhanced durability. Furthermore, the electrocatalytic performance for OER and OWS has been significantly improved by a simple acid treatment to the electrocatalysts, which introduces physical and chemical defects, particularly oxygen functional groups (the acid-treated sample is termed as Ni 3 S 2 @CNTs/CC-AT). As OER electrocatalysts, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT present overpotentials of 304 and 200 mV, respectively, for achieving a current density of 10 mA/cm 2 in the OER process. Furthermore, for complete water splitting in 1.0 M KOH electrolyte, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT exhibit potentials of 1.63 and 1.44 V, respectively, to achieve a current density of 10 mA/cm 2 when employed as both anode and cathode. Moreover, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT demonstrate durable nature for 22 and 20 h durability in the OER and OWS processes, respectively, offering a promising alternative to ruthenium- and iridium-based electrocatalysts for electrochemical hydrogen production through water splitting. In conclusion, the in-situ synthesis method and acid treatment strategy described in this research are promising approaches to fabricating high-performance encapsulated carbon-nanotube-based electrocatalysts.

36 MATERIALS SCIENCE↗

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗

Investigation of Sub‐Bandgap Emission and Unexpected n‐Type Behavior in Undoped Polycrystalline CdSe x Te 1‐x

Abstract Se alloying has enabled significantly higher carrier lifetimes and photocurrents in CdTe solar cells, but these benefits can be highly dependent on CdSe x Te 1‐x processing. This work evaluates the optoelectronic, chemical, and electronic properties of thick (3 µm) undoped CdSe x Te 1‐x of uniform composition and varied processing conditions (CdSe x Te 1‐x evaporation rate, CdCl 2 anneal, Se content) chosen to reflect various standard device processing conditions. Sub‐bandgap defect emission is observed, which increased as Se content increased and with “GrV‐optimized CdCl 2 ” (i.e., CdCl 2 anneal conditions used for group‐V‐doped devices). Low carrier lifetime is found for GrV‐optimized CdCl 2 , slow CdSe x Te 1‐x deposition, and low‐Se films. Interestingly, all films (including CdTe control) exhibited n‐type behavior, where electron density increased with Se up to an estimated ≈10 17 cm −3 . This behavior appears to originate during the CdCl 2 anneal, possibly from Se diffusion leading to anion vacancy (e.g., V Se , V Te ) and Cl Te generation.

14 SOLAR ENERGY↗

Abstraction of Hydride from Alkanes and Dihydrogen by the Perfluorotrityl Cation

Abstract Lewis acids play a central role in a large variety of chemical transformations. The reactivity of the strongest Lewis acids is typically studied in the context of affinity towards hard bases, such as fluoride or oxygenous species. Carbocations can be viewed as soft Lewis acids, possessing significant affinity for softer bases, such as hydride. This work presents the ambient‐temperature isolation of salts of the perfluorotrityl cation ((C 6 F 5 ) 3 C + or F 15 Tr + ) in combination with halogenated carborane anions. The F 15 Tr + cation exhibits remarkable hydride affinity, illustrated by the observation of hydride abstraction from dihydrogen, and of the rapid abstraction of hydride from −CH 2 −groups in alkanes. Theoretical studies support the favorability of hydride abstraction from dihydrogen, and indicate that the hydride abstraction from alkanes proceeds via a concerted hydride transfer process that is sensitive to steric effects.

Leong, Derek W. [Department of Chemistry Texas A&a↗

Abstraction of Hydride from Alkanes and Dihydrogen by the Perfluorotrityl Cation

Abstract Lewis acids play a central role in a large variety of chemical transformations. The reactivity of the strongest Lewis acids is typically studied in the context of affinity towards hard bases, such as fluoride or oxygenous species. Carbocations can be viewed as soft Lewis acids, possessing significant affinity for softer bases, such as hydride. This work presents the ambient‐temperature isolation of salts of the perfluorotrityl cation ((C 6 F 5 ) 3 C + or F 15 Tr + ) in combination with halogenated carborane anions. The F 15 Tr + cation exhibits remarkable hydride affinity, illustrated by the observation of hydride abstraction from dihydrogen, and of the rapid abstraction of hydride from −CH 2 −groups in alkanes. Theoretical studies support the favorability of hydride abstraction from dihydrogen, and indicate that the hydride abstraction from alkanes proceeds via a concerted hydride transfer process that is sensitive to steric effects.

Leong, Derek W. [Department of Chemistry Texas A&a↗

Kinetic and modeling studies of the mechanism of the dehydrogenation of Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2

Since its discovery over 15 years ago, the reversible dehydrogenation of Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2 has remained one of the more intriguing hydrogen-cycling systems. While the mechanism of this reaction has been the subject of a good deal of speculation and computational studies, prior to this work it had not been probed through kinetic studies. Previous reports of the dehydrogenation of Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2 have not included kinetic studies. The present studies have shown that the dehydrogenation of Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2 is suppressed by hydrogen pressure indicating that the rate-limiting step in this process involves hydrogen elimination. Computational modeling of kinetic data obtained from monitoring the hydrogen elimination from Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2 under static vacuum over a range of temperatures supports that the dehydrogenation occurs through a reversible three-step process in which the elimination of hydrogen from the [B 3 H 10 ] − intermediate is rate limiting. A mechanism involving the low energy transfer of neighboring BH3 groups is proposed to account for the formation of [B 3 H 8 ] − at relatively low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Paired Neural Network for Matching Experimental and Predicted Infrared Spectra

Here, we present a novel machine learning (ML)-based scoring technique for determining the similarity between experimental and predicted infrared (IR) spectra for identification purposes. IR spectroscopy is a powerful technique used to identify the molecular structure and composition of a sample by measuring the unique vibrational frequency pattern of the molecule’s functional groups. Molecular identifications are often made by comparing experimental and reference spectra. However, the limited number of reference spectra available in spectral libraries can confound the identification process. Alternative identification procedures rely on in silico techniques to simulate spectra for a wide range of molecules. However, scoring spectral similarity between an experimental query and computationally predicted reference remains a significant challenge. Our proposed ML-based scoring technique overcomes these barriers by accurately and efficiently determining spectral similarity.

Neural Network↗

Characterizing Hydrated Polymers via Dielectric Relaxation Spectroscopy: Connecting Relative Permittivity, State of Water, and Salt Transport Properties of Sulfonated Polysulfones

Sulfonated polysulfone is a promising membrane material for separation and energy generation processes that rely on membranes to control the rates of small-molecule (e.g., water and ions) transport. The interactions among water molecules, ions, and the sulfonate groups in these polymers play a key role in controlling these rates of transport, but much remains unknown about these fundamental interactions in sulfonated polymers. In this study, we used dielectric relaxation spectroscopy to characterize water molecule dynamics in sulfonated polysulfone and Nafion. We found that the charged sulfonate groups contribute to a restriction of water molecule dynamics (i.e., a reduction in the characteristic time scale of dipolar motions) in a manner that is governed by the concentration and nature (i.e., conjugate base strength) of the sulfonate group. Additionally, we develop strategies to use these data to aid in modeling ion transport in sulfonated polysulfone. These results may be useful to guide engineering strategies for polymeric membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Additive-Induced Morphology Change of Polymer Film Enables Enhanced Charge Mobility and Faster Organic Electrochemical Transistor Switching

Conjugated polymers (CPs) play an important role in organic electrochemical transistors (OECTs) for bioelectronics and related applications, where they serve as channel materials. Currently, most successful polymers for CPs are re-engineered from traditional CPs by replacing hydrophobic alkyl side chains with hydrophilic ethylene glycol or ionic groups. Frustratingly, the enhanced ion transport often compromises the charge mobility of the original CP. In this work, we present an additive-mediated method to construct a modified poly(3-hexylthiophene) (P3HT) film to enable efficient ion migration. The additive is designed with a cleavable diazo group that releases nitrogen and 2-methoxyethanol, a volatile compound, to alter the P3HT film morphology. OECTs based on the film exhibit improved response times. Interestingly, the process also enhances the crystallinity of P3HT, leading to higher hole mobility compared with pristine P3HT. This study proposes an in situ strategy to achieve the functionality of the OMIEC via morphological regulation, offering a promising route to simultaneously enhance both ion accessibility and charge mobility.

Organic polymers↗

Metal–Metal Bonding Influences Hydride Reactivity in [Sn–Rh] 3+ and [Sn–Ni] 2+ Bimetallics

Heavier group 14 metal hydrides serve as key intermediates in catalytic transformations, such as hydroboration. Regenerating such intermediates via a clean hydride source like dihydrogen could provide catalytic processes with a more economical alternative to, e.g., silanes and hydridoborane reagents. Herein, we report our efforts toward this goal using a [Sn–Rh] 3+ bimetallic system with the formal Rh I center acting as a potential dihydrogen activator. Targeting the introduction of a hydride ligand to the bimetallic core, our reactivity studies have revealed a preference for the hydride ligand to be bound to the Rh center, instead of the Sn center. Finally, examination of the electronic structures of these complexes via theoretical and experimental methods has revealed the electron acceptor nature of the Rh center within the bimetallic core and offers an explanation for the localization of the hydride between metal centers.

anions↗

Multidimensional scaling informed by F -statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. Here, in this study, we introduce a new MDS-based ordination method, “F-informed MDS,” which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community’s response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

Biological and medical sciences↗

Advancing Porous Carbons: Understanding the Importance of Surface Chemistry for the Energy–Environment Nexus

This review intends, in a critical way, the comprehensive view of the importance of porous carbons surface chemistry for their applications in an energy− environment nexus. Surface chemistry is presented as a combination of functional heteroatom-containing groups, dopants, and structural defects. First, we briefly address carbon surface chemical environment and the methods of its modification and characterization, indicating their practical limitations. Then, the effects of surface chemistry on separation, catalysis, energy storage, sensing and microwave absorption are introduced. Besides a critical analysis of published findings on these topics, we also include our views on the advancement in the processes which rely on porous carbons surface chemistry, and identify strategic areas and directions that should deserve further attention. We focus on new findings and important original contributions to the field. Since the community of carbon researchers grows following the strategic application of these materials, the role of functional groups, dopants and structural defects in various cutting-edge applications is emphasized, showing the progress in the field and the evolution of findings. A clear determination of the effects of carbon surface is often a challenge since carbons porosity and the locations of specific bonds/sites/ defects in the carbon texture provide nanoconfinement effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selectivity of tris complexation for Ni(II), Co(II), and Fe(II) and its effect on carbonate precipitation under alkaline conditions

Simultaneous critical element recovery and ex-situ carbon mineralization of low-grade ultramafic deposits have garnered increasing interest. Understanding the selectivity of metal complexing organic ligands for various divalent metals present in ultramafic rocks during carbonate mineralization is required to optimize this process. Here we evaluate 2-amino-2-(hydroxymethyl)-1,3-propanediol (i.e., Tris) as a model for bidentate ligands that bind divalent metals with both amine and alcohol groups in alkaline conditions (pH 8–10.5) at 25 °C and 80 °C in carbonate-buffered solutions. Protonated Tris forms a stronger complex with metal ions and is selective for trace metals with Ni(II) > Co(II) > Fe(II) during carbonate precipitation, with the rates decreasing but selectivity increasing at lower temperature and lower pH. At 25 °C, metastable amorphous hydrated carbonates form, regardless of the amount of Tris present or pH values. At 80 °C and pH 8, the Co and Fe carbonates that form are a mixture of rosasite-group minerals (Co 2 CO 3 (OH) 2 (H 2 O) and Fe 2 CO 3 (OH) 2 ) and pure carbonates (sphaerocobaltite: CoCO 3 and siderite: FeCO 3 ), with the latter more stabilized with increasing Tris concentration. In mixed metal solutions without Tris at 25 °C where Fe:Ni or Fe:Co is 2:1, Fe increases the rates of Ni or Co carbonate precipitation. However, with increasing Tris concentration the presence of Ni or Co inhibits Fe carbonate precipitation. At 80 °C without Tris, Ni or Co substitute into the iron chukanovite (Fe 2 CO 3 (OH) 2 ) lattice, increasing Ni or Co carbonate precipitation rates. Increasing Tris concentration only slightly inhibits Fe and Co precipitation, but slows Ni precipitation up to 10 times, with Fe progressively partitioning into more pure carbonate phases with distinct crystalline morphologies. These findings suggest bidentate amine-bearing ligands may be effective at Ni and Co recovery during carbon mineralization of Fe-bearing ultramafic deposits at relatively low temperatures and slightly alkaline pH.

54 ENVIRONMENTAL SCIENCES↗

Datum: A Scientific Metadata Catalog

The data catalog market is currently flooded with a myriad of different products, but none serve the scientific community well. There are cloud-native tools like Databricks, Snowflake,to on-premise solutions like Collibra and Datahub. The common failing of all these tools however, is their inability to serve the scientific data community directly. Most catalogs are targeted towards financial, health, or user data - not sensor or scientific domain data. They also prioritize integrations that often don’t exist or are just starting to be used in the scientific realm - all while ignoring common scientific tools and file types. Datum is a catalog which targets the scientific data directly, including the tools and networks in which those tools are used. We work with the producers and consumers of the data where they are, targeting cloud and on-premise with a focus on classified networks. Datum is an Erlang/Elixir application. Technical Features Note: The features listed below are still under development and may change, slightly, upon final delivery of the product. File Formats - Datum has the ability to read additional metadata and provides processing pipelines for the following file formats: Plain Text, PDF, LaTeX, HTML, Open Document Format (.odt), XML, CSV/TSV (and other standard delimiters), OpenDocument Database and Spreadsheets, Geo-Referenced TIFF, Common Data Format, HDF/HDF5, LabView TDMS, Excel, DeltaTables, Parquet, Apache Iceberg, Apache Hudi and many others. Metadata Collection - Scanners for the local and networked file systems and cloud storage providers. Network integration with common databases such as MSSQL and MySQL. User Plugin System - Users are able to provide either file processing, metadata extraction, or sampling plugins in the programming language of their choice. Authentication/Authorization -: OIDC integration, SCIM provisioning and EntraID integration out of the box. Full user and group management system with a “least privilege” operating mode. Governance - Customizable data governance platform; dictate and enforce required metadata, enforce data embargos, and enforce user agreements and NDAs before data access. Ability to create health checks on data, rejecting abandoned or poorly curated data and automatically removing it from the search index. Ability for users to submit corrections. Search - Semantic search is a first class citizen. No licenses to expensive, external software required. Integrated use of vectors and vector-based search allows for AI agent integration at all levels of operation. Metadata Model - Display and control data’s lineage and connections to other data and data directories. Data is modeled after a filesystem - an organization instantly recognizable and navigable by most any user. CLI and SDK - Ships with a Command Line Interface (CLI) tool and with a fully-featured Python SDK. This allows for rapid and programmatic use of Datum by every level of user. Minimal Infrastructure - Datum ships as a single executable file and can be run on any operating system and most CPU architectures. Datum has no reliance on external databases, search indexing tools, or other outside services - and it runs equally well on edge computing devices, cloud services, or in a clustered HPC environment.

darrington, john↗