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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Novel Cell-Type-Specific Drought-Responsive Proteins in Root Tips of Field-Grown Perennial Switchgrass

The root-tip region of plants, including the root cap, forms the most basal terminal of the root and exhibits a high degree of cellular complexity in terms of morphology, cytological function, and interaction with environmental cues in the soil. Cells in this region follow a developmental trajectory, transitioning from stem cells to meristematic cells, and ultimately to fully differentiated cell types. However, our understanding of root-tip cell-type specific proteomic responses to abiotic stresses, such as drought, particularly under field conditions, remains limited. This study aimed to identify spatially resolved, cell type-specific proteomes in switchgrass (Panicum virgatum) root tips under drought stress. Root tips were collected from seven-year-old, field-grown switchgrass ‘Alamo’ plants excavated under both well-watered and long-term drought conditions. Cell type-specific proteins were identified using laser capture microdissection (LCM) coupled with nanoPOTS (Nanodroplet Processing in One Pot for Trace Samples) and nano-LC-MS proteomics analysis. Five distinct cell types were targeted: (1) cells in the quiescent center and stem cell niche (QuC), (2) protodermal epidermal cells (PEC) in the meristematic zone, (3) epidermal cells in the transition and elongation zones above the root cap (Epi), (4) peripheral root cap cells (PRC), forming 2–3 layers below the PEC and 1–2 layers above the root border cells, and (5) columella root cap cells (Col) comprising of the columella initials and a single underlying layer of cells undergoing active growth. Principal component analysis (PCA) revealed clear separation among the five targeted cell types, confirming distinct proteomic profiles. Proteins predominantly enriched in each cell type were linked to distinct cellular functions, with QuC cells showing involvement in chromosomal behavior, DNA replication, and mitosis—key processes for stem cell niche regulation. Drought stress resulted in alterations of proteostasis, as evidenced by significant decreases in ribosomal proteins and increases in protein synthesis inhibitors. Moreover, drought stress induced unique cell-type–specific proteins involved in phytohormone biosynthesis and signaling pathways, including auxin, cytokinin, and jasmonic acid. In particular, QuC cells were more highly enriched in proteins associated with DNA repair and mitotic processes. Metabolic pathways related to amino acids, carbohydrates, and lipids were differentially affected in a cell-type–dependent manner, whereas general stress-responsive proteins exhibited consistent changes across all five cell types. Overall, this study provides unique spatially resolved, cell-type-specific proteomic profiles in root tips, representing a significant advancement in our understanding of the cellular mechanisms underlying plant responses to drought stress in natural field conditions.

perennial grass↗
DOE OSTI2025

Autonomous Synthesis and Inverse Design of Electrochromic Polymers with High Efficiency and Accuracy

Here, the design and synthesis of functional polymers, aimed at targeted properties through specific structures, have long been challenged by their complex and often nonlinear structure–property relationships. Key processes, including knowledge accumulation for predictive design and experimental refinement and validation, are traditionally labor-insensitive and time-consuming, making it difficult to balance accuracy and efficiency. Here, we introduce an accelerated, autonomous system for the on-demand synthesis of electronic polymers that achieves the desired electrochromic functionality with high accuracy and efficiency. Our approach leverages large language model-assisted data mining, a physics-informed copolymer machine learning model, and an AI-driven autonomous robotic workflow in the Polybot lab. Within 72 h, Polybot autonomously synthesized electrochromic polymers (ECPs) with targeted, previously-unreported color values, including green polymers with specific absorption profiles, precisely fine-tuning copolymer structures with a 5% step size in comonomer composition within a three-monomer system. A publicly accessible ECP informatics database has also been created to foster knowledge exchange.

AI-driven Robotic Lab↗
NASA NTRS1985

Video image processing

Current technology projections indicate a lack of availability of special purpose computing for Space Station applications. Potential functions for video image special purpose processing are being investigated, such as smoothing, enhancement, restoration and filtering, data compression, feature extraction, object detection and identification, pixel interpolation/extrapolation, spectral estimation and factorization, and vision synthesis. Also, architectural approaches are being identified and a conceptual design generated. Computationally simple algorithms will be research and their image/vision effectiveness determined. Suitable algorithms will be implimented into an overall architectural approach that will provide image/vision processing at video rates that are flexible, selectable, and programmable. Information is given in the form of charts, diagrams and outlines.

Murray, N. D.↗
DOE OSTI2020

Techno-economic prospects for producing Fischer-Tropsch jet fuel and electricity from lignite and woody biomass with CO 2 capture for EOR

This work explores the prospective techno-economic performance of facilities that produce low- and net-negative-carbon liquid transportation fuels and electricity with CO 2 capture for enhanced oil recovery. The lignite and biomass-to-jet fuel process is based on KBR’s TRIG gasifier, Rectisol (for sulfur removal and CO 2 capture), fixed-bed low temperature Fischer-Tropsch synthesis of liquid fuels, and Brayton/Rankine combined cycles to convert synthesis/refining off-gases and waste heat to electricity. This work leverages a recent, highly-detailed assessment of a prospective first-of-a-kind (FOAK) demonstration facility to develop highly detailed Aspen Plus process simulations for nine prospective N th -of-a-kind (NOAK) plant equipment configurations. Component-level capital costs from the FOAK study are scaled and adjusted to reflective prospective learning-by-doing to estimate capital costs for the NOAK designs. NOAK plant economic performance is found to be largely insensitive to variations in plant configurations and electricity output fraction, but biomass input fraction significantly affects profitability. Facilities that consume only carbon–neutral biomass, with no lignite co-feed, have significantly net-negative carbon emissions and the most favorable prospective economics when carbon emissions are priced. For these facilities, the crude oil price required for plant economic viability falls rapidly from $\$$100/bbl as carbon emission prices increase above $\$$120/tonne CO 2eq . In general, plants that co-fire lignite with biomass are less profitable (than 100% biomass plants) due to their higher net greenhouse gas emissions.

09 BIOMASS FUELS↗
DOE OSTI2021

Activation of anionic redox in d 0 transition metal chalcogenides by anion doping

Expanding the chemical space for designing novel anionic redox materials from oxides to sulfides has enabled to better apprehend fundamental aspects dealing with cationic-anionic relative band positioning. Pursuing with chalcogenides, but deviating from cationic substitution, we here present another twist to our band positioning strategy that relies on mixed ligands with the synthesis of the Li 2 TiS 3-x Se x solid solution series. Through the series the electrochemical activity displays a bell shape variation that peaks at 260 mAh/g for the composition x = 0.6 with barely no capacity for the x = 0 and x = 3 end members. We show that this capacity results from cumulated anionic (Se 2– /Se n– ) and (S 2– /S n– ) and cationic Ti 3+ /Ti 4+ redox processes and provide evidence for a metal-ligand charge transfer by temperature-driven electron localization. Moreover, DFT calculations reveal that an anionic redox process cannot take place without the dynamic involvement of the transition metal electronic states. These insights can guide the rational synthesis of other Li-rich chalcogenides that are of interest for the development of solid-state batteries.

25 ENERGY STORAGE↗
NASA NTRS2018

Igneous Rocks Formed by Hypervelocity Impact

Igneous rocks are the primary building blocks of planetary crusts. Most igneous rocks originate via decompression melting and/or wet melting of protolith lithologies within planetary interiors and their classification and compositional, petrographic, and textural characteristics, arewell-studied. As our exploration of the Solar System continues, so too does the inventory of intrusive and extrusive igneous rocks, settings, and processes. The results of planetary exploration have also clearly demonstrated that impact cratering is a ubiquitous geological process that has affected, andwill continue to affect, all planetary objectswith a solid surface,whether that be rock or ice. It is nowrecognized that the production of igneous rocks is a fundamental outcome of hypervelocity impact. The goal of this review is to provide an up-to-date synthesis of our knowledge and understanding of igneous rocks formed by hypervelocity impact. Following a brief overview of the basics of the impact process, we describe howand whymelts are generated during impact events and howimpactmelting differs fromendogenic igneous processes.While the processmay differ,we showthat the products of hypervelocity impact can share close similarities with volcanic and shallow intrusive igneous rocks of endogenic origin. Such impact melt rocks, as they are termed, can display lobate margins and cooling cracks, columnar joints and at the hand specimen andmicroscopic scale, such rocks can displaymineral textures that are typical of volcanic rocks, such as quench crystallites, ophitic, porphyritic, aswell as features such as vesicles, flowtextures, and so on.Historically, these similarities led to themisidentification of some igneous rocks now known to be impact melt rocks as being of endogenic origin. This raises the question as to how to distinguish between an impact versus an endogenic origin for igneous-like rocks on other planetary bodies where fieldwork and sample analysis may not be possible and all that may be available is remote sensing data.While the interpretation of some impact melt rocks may be relatively straightforward (e.g., for clast-rich varieties and those with clear projectile contamination) we conclude that distinguishing between impact and endogenic igneous rocks is a non-trivial task that ultimately may require sample investigation and analysis to be conducted. Caution is, therefore, urged in the interpretation of igneous rocks on planetary surfaces.

Osinski, Gordon R.↗
DOE OSTI2022

Laser-Assisted Synthesis of Monolayer 2D MoSe 2 Crystals with Tunable Vacancy Concentrations: Implications for Gas and Biosensing

We report tuning the structural and electronic properties of atomically thin two-dimensional (2D) materials via defect and vacancy engineering is the key to enabling their potential use in various applications, including electronics, energy, and sensing devices. Vacancies are, for instance, becoming highly promising for the enhanced interaction of gases and biomolecules with 2D materials in energy and sensing applications. However, the deterministic generation of desirable vacancies with tunable concentrations remains a challenge in 2D materials due to the limitations in the current growth methods, such as the complex reaction chemistries and gas flow dynamics. Therefore, engineering defects and vacancies in 2D materials have been mainly limited to destructive top-down processes such as heating, ion bombardments, and laser postprocessing. Here, we introduce a single-step bottom-up synthesis approach for the growth of monolayer MoSe 2 crystals with tunable vacancy concentrations. This method utilizes the spatiotemporal properties and adjustable power densities of the lasers to control the vaporization dynamics of the stoichiometric MoSe 2 powders. Such a mechanism in the vaporization allows us to grow tunable stoichiometry monolayer MoSe 2–x crystals on the substrates. The localized and time-controlled (250 ms to 2 s) vaporization of the MoSe 2 powder by a CO 2 laser enables the formation of monolayer crystals with controlled vacancy concentrations ranging from ~1 to 20%. The effects of laser power, laser irradiation time, and background pressure on the tuning range and subsequent properties of the crystals are investigated and quantified using Raman and photoluminescence spectroscopy, scanning transmission electron microscopy (STEM), and time-correlated single-photon counting (TCSPC). This bottom-up synthesis is a promising approach that allows the deterministic vacancy tuning for future electronics and, in particular, gas and biosensing applications without the need for further postprocessing and potential structural disruption of the crystals.

2D materials↗
DOE OSTI2024

The synthesis and characterization of an iron(VII) nitrido complex

Abstract Complexes of iron in high oxidation states are captivating research subjects due to their pivotal role as active intermediates in numerous catalytic processes. Structural and spectroscopic studies of well-defined model complexes often provide evidence of these intermediates. In addition to the fundamental molecular and electronic structure insights gained by these complexes, their reactivity also affects our understanding of catalytic reaction mechanisms for small molecule and bond-activation chemistry. Here, we report the synthesis, structural and spectroscopic characterization of a stable, octahedral Fe(VI) nitrido complex and an authenticated, unique Fe(VII) species, prepared by one-electron oxidation. The super-oxidized Fe(VII) nitride rearranges to an Fe(V) imide through an intramolecular amination mechanism and ligand exchange, which is characterized spectroscopically and computationally. This enables combined reactivity and stability studies on a single molecular system of a rare high-valent complex redox pair. Quantum chemical calculations complement the spectroscopic parameters and provide evidence for a diamagnetic ( S = 0) d 2 Fe(VI) and a genuine S = 1/2, d 1 Fe(VII) configuration of these super-oxidized nitrido complexes.

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

Ketjenblack-Supported and Unsupported ZrO 2 –ZrN Nanoparticle Systems for Enabling Efficient Electrochemical Nitrogen Reduction to Ammonia

Artificial N 2 fixation via the electrocatalytic nitrogen (N 2 ) reduction reaction (NRR) has been recently promoted as a rational route toward reducing energy consumption and CO 2 emission as compared with the traditional Haber–Bosch process. Nevertheless, optimizing NRR relies on developing highly efficient electrocatalysts. Herein, we report on the reliable and reproducible synthesis of two promising electrocatalysts in either the presence or absence of Ketjenblack (KB), namely, ZrO 2 –ZrN@KB and ZrO 2 –ZrN systems, synthesized through the nitriding of Zr. Both materials had never previously been considered for NRR, to the best of our knowledge. Nevertheless, both of these electrocatalysts incorporated a combination of tetragonal ZrO 2 , ZrON, and cubic ZrN and showed excellent activity and durability toward NH 3 formation. Moreover, the maximum NH3 production rate of 84.1 μg h –1 mg –1 at -0.7 V vs a reversible hydrogen electrode (RHE) was achieved with the ZrO 2 –ZrN electrocatalyst with an impressive Faradaic efficiency of 21.2% at -0.6 V vs RHE, indicating a high selectivity associated with the NRR. Additionally, the catalysts demonstrated excellent stability during the electrolysis process and recycling tests. Here we postulate that the combination of exposed active sites of ZrN and ZrO 2 likely contributes to the enhanced NRR performance attributed to ZrO 2 –ZrN.

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

Mixed Ionic Electronic Conducting Quaternary Perovskites: Materials by Design for Solar Thermochemical Hydrogen

The innovative research conducted by Arizona State University and Princeton University in the project "Mixed Ionic-Electronic Conducting Quaternary Perovskites: Materials by Design for Solar Thermochemical Hydrogen" marks a significant stride forward in thermochemical water splitting. Through an intricate blend of computational design and experimental validation, the project delved into the promising potential of Mixed Ionic Electronic Conducting (MIEC) perovskites. These complex materials, characterized by their unique redox-active nature and adaptability in stoichiometry, present a promising frontier for efficient solar thermochemical hydrogen production. Firstly, the research enhanced the science by utilizing state-of-the-art computational methodologies to unravel the nuanced chemical potentials of MIEC perovskites. By simulating various off-stoichiometric scenarios and redox conditions, the team was able to predict material behaviors under diverse environmental conditions, a feat unachievable through conventional experimental methodologies alone. This approach not only fast-tracks the material screening process, significantly reducing the time from laboratory re-search to practical application, but also uncovers trends and correlations that are pivotal for future materials innovation. Regarding technical effectiveness, the project stands out in its economic feasibility. Traditional methods of materials discovery are often marred by high costs and extensive timeframes, owing to the iterative nature of experimental processes. However, by employing theoretical computations and validating these findings with targeted experiments, the project introduced a cost-effective paradigm for materials discovery and the first ever prediction, synthesis, and preliminary validation of a material solely from computational and theoretical considerations. This synergy between computation and experimentation expedites the discovery of optimal materials conducive to high-efficiency solar-to-hydrogen conversion processes. Furthermore, the public stands to benefit substantially from this research. The success of MIEC perovskites in solar thermochemical applications heralds a shift towards lower cost and lower electricity input for clean hydrogen production, hence potentially impacting climate and energy resilience. By improving the efficiency of solar-to-hydrogen conversions, the research paves the way for reduced dependency on fossil fuels, addressing the urgent global need for accessible and renewable energy sources. Moreover, the project's advancements contribute to scientific literacy in renewable energy technologies, empowering society through knowledge and spurring future innovations. In essence, this research project demonstrates significant progress in the realm of advanced water splitting through solar thermochemistry. Through its groundbreaking approaches in computational materials science and its implications for real-world applications, it holds the promise of a cleaner, more energy-resilient future.

08 HYDROGEN↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Spent-fuel recycling molecule degradation product standards can be produced with preparative liquid chromatography

Solvent systems used for spent nuclear fuel separation schemes are subject to intense radiation fields from the spent fuel, resulting in a degradation of separation performance over time from both the radiolytic destruction of active compounds (extractants, holdback agents, etc.) and the production of degradation compounds (compounds produced from the destruction of the active compounds). Development of a quantitative understanding of the effects of radiolysis on separations is impeded by a near-complete lack of availability of degradation products from chemical manufacturers. Synthesis of these degradation products through traditional means is both cost and time prohibitive, inhibiting advancement of new fuel separation processes. We hypothesize that comprehensive sets of degradation products can be synthesized using preparative radiolysis, and purified using high performance liquid chromatography in quantities sufficient for unequivocal identification and subsequent use as quantitative analytical studies. Achieving this objective will facilitate development of a much more accurate understanding of radiolysis reactions and their effects on solvent extraction processes, positioning Idaho National Laboratory (INL) in a leadership role in the science of fuel cycle separations. We propose producing these degradation compounds by irradiating concentrated samples of solvent ligands in the INL gamma irradiator, separating the resulting mixture with preparative chromatography, and removing the mobile phase in the separated fractions with a vacuum concentrator. This will yield milligram to gram quantities of purified degradation products, sufficient for fundamental research, at a fraction of the time and cost of synthesis. Facile production of separation molecule degradation products at minimal cost will enable the fundamental research that will accelerate the development of fuel cycles that will ensure the competitiveness of nuclear energy.

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

A method to load tellurium in liquid scintillator for the study of neutrinoless double beta decay

Herein, a method has been developed to load tellurium into liquid scintillator so as to permit searches for neutrinoless double beta decay with high sensitivity. The approach involves the synthesis of an oil-soluble tellurium compound from telluric acid and an organic diol. The process utilises distillable chemicals that can be safely handled underground and affords low radioactive backgrounds, low optical absorption and high light yields at loading levels of at least several percent Te by weight.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Crystal and Electronic Structures of A 2 NaIO 6 Periodate Double Perovskites (A = Sr, Ca, Ba): Candidate Wasteforms for I-129 Immobilization

The synthesis, structure, and thermal stability of the periodate double perovskites A 2 NaIO 6 (A= Ba, Sr, Ca) were investigated in the context of potential application for the immobilization of radioiodine. A combination of X-ray diffraction and neutron diffraction, Raman spectroscopy, and DFT simulations were applied to determine accurate crystal structures of these compounds and understand their relative stability. The compounds were found to exhibit rock-salt ordering of Na and I on the perovskite B-site; Ba 2 NaIO 6 was found to adopt the Fm- 3 m aristotype structure, whereas Sr 2 NaIO 6 and Ca 2 NaIO 6 adopt the P 2 1 / n hettotype structure, characterized by cooperative octahedral tilting. DFT simulations determined the Fm- 3 m and P 2 1 / n structures of Ba 2 NaIO 6 to be energetically degenerate at room temperature, whereas diffraction and spectroscopy data evidence only the presence of the Fm- 3 m phase at room temperature, which may imply an incipient phase transition for this compound. The periodate double perovskites were found to exhibit remarkable thermal stability, with Ba 2 NaIO 6 only decomposing above 1050 °C in air, which is apparently the highest recorded decomposition temperature so far recorded for any iodine bearing compound. As such, these compounds offer some potential for application in the immobilization of iodine-129, from nuclear fuel reprocessing, with an iodine incorporation rate of 25–40 wt%. The synthesis of these compounds, elaborated here, is also compatible with both current conventional and future advanced processes for iodine recovery from the dissolver off-gas.

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

Stoichiometric Lanthanide Compounds with Diglycolamides: A Synthetic Approach toward Understanding Rare-Earth Speciation in Solution

A fundamental understanding of coordination chemistry across the lanthanide series is essential for explaining the chemical behavior of rare-earth metals in complex liquid–liquid extraction processes. Probing the exact bonding between the extractant and the metal is sometimes done through the synthesis of solid-state compounds that can serve as models for metal speciation in solution. In the case of diglycolamide (DGA), a commonly used neutral diamide extractant, extensive studies identify the stepwise formation of 1:1 [Ln(DGA)(H 2 O) 6 ] 3+ , 1:2 [Ln(DGA) 2 (H 2 O) 3 ] 3+ , and 1:3 [Ln(DGA) 3 ] 3+ complexes in solution. The crystallographic reports, however, exclusively show a 1:3 [Ln(DGA) 3 ] 3+ moiety in the solid state, while the structures of 1:1 and 1:2 complexes are yet to be isolated and comprehensively studied. In this work, we report the synthesis and characterization of three new families of stoichiometric N,N,N′,N’ -tetramethyldiglycolamide (TMDGA) compounds: [Ln(TMDGA)(H 2 O) 5 Cl]Cl 2 ·2H 2 O, [Ln(TMDGA) 2 (H 2 O) 3 ]Cl 3 ·3H 2 O, and [Ln(TMDGA) 3 ]Cl 3 ·7H 2 O, where Ln = Nd, Eu, Gd, with Ln:TMDGA ratios of 1:1, 1:2, and 1:3, respectively. Further, the compounds have been analyzed using vibrational spectroscopy (both Raman and FT-IR), as well as variable temperature fluorescence spectroscopy. A spectrophotometric titration of Eu(III) was performed to confirm the presence of the [Eu(TMDGA) n ] 3+ ( n = 1, 2, and 3) species in solution and to compare the individual solid-state emission spectra to their respective analogues in solution.

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

Accurate Prediction of pKb in Amines: Validation of the CAM-B3LYP/6-311+G(d,p)/SMD Model

Amines play several key roles in chemistry and biology and are involved in numerous industrial processes, often with significant economic impacts. Recently, amines are also garnering interest as catalysts for polymer synthesis and for CO 2 fixation, incentivizing the need to rapidly design and screen new amino compounds. Hence, developing reliable methods to predict their physicochemical properties, e.g., the base dissociation constant (pKb), is pivotal. Here, a density functional theory (DFT)-based approach was employed to compute the pKb of substituted amines, exploring the impact of several key parameters, including (i) the number of explicit water molecules at the reaction center, (ii) the van der Waals (vdW) surface, and (iii) solvent polarizability. In previous work, it was determined that including two explicit water molecules at the reaction center resulted in highly accurate pKb estimates for primary amines. Here, we find that including a third water molecule at the reaction center is essential for accurate pKb for secondary and tertiary amines. The revised methodology was then applied to a wider selection of amines, obtaining a minimum average error (MAE) < 0.4. In conclusion, this result represents an extension of our “easy-to-use method,” a simple and direct DFT approach exploiting CAM-B3LYP/SMD/6-311G+(d,p) to compute pKb without post facto modifications.

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

Emerging materials intelligence ecosystems propelled by machine learning

We report that the age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its successes and promises, several AI ecosystems are blossoming, many of them within the domain of materials science and engineering. These materials intelligence ecosystems are being shaped by several independent developments. Machine learning (ML) algorithms and extant materials data are utilized to create surrogate models of materials properties and performance predictions. Materials data repositories, which fuel such surrogate model development, are mushrooming. Automated data and knowledge capture from the literature (to populate data repositories) using natural language processing approaches is being explored. The design of materials that meet target property requirements and of synthesis steps to create target materials appear to be within reach, either by closed-loop active-learning strategies or by inverting the prediction pipeline using advanced generative algorithms. AI and ML concepts are also transforming the computational and physical laboratory infrastructural landscapes used to create materials data in the first place. Surrogate models that can outstrip physics-based simulations (on which they are trained) by several orders of magnitude in speed while preserving accuracy are being actively developed. Automation, autonomy and guided high-throughput techniques are imparting enormous efficiencies and eliminating redundancies in materials synthesis and characterization. The integration of the various parts of the burgeoning ML landscape may lead to materials-savvy digital assistants and to a human-machine partnership that could enable dramatic efficiencies, accelerated discoveries and increased productivity. Here, we review these emergent materials intelligence ecosystems and discuss the imminent challenges and opportunities. The materials research landscape is being transformed by the infusion of approaches based on machine learning. This Review discusses the emerging materials intelligence ecosystems and the potential of human-machine partnerships for fast and efficient virtual materials screening, development and discovery.

36 MATERIALS SCIENCE↗