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DOE OSTI2024

Towards predictive control of reversible nanoparticle assembly with solid-binding proteins

Although a broad range of ligand-functionalized nanoparticles and physico-chemical triggers have been exploited to create stimuli-responsive colloidal systems, little attention has been paid to the reversible assembly of unmodified nanoparticles with non-covalently bound proteins. Previously, we reported that a derivative of green fluorescent protein engineered with oppositely located silica-binding peptides mediates the repeated assembly and disassembly of 10-nm silica nanoparticles when pH is toggled between 7.5 and 8.5. We captured the subtle interplay between interparticle electrostatic repulsion and their protein-mediated short-range attraction with a multiscale model energetically benchmarked to collective system behavior captured by scattering experiments. Here, in this work, we show that both solution conditions (pH and ionic strength) and protein engineering (sequence and position of engineered silica-binding peptides) provide pathways for reversible control over growth and fragmentation, leading to clusters ranging in size from 25 nm protein-coated particles to micrometer-size aggregate. We further find that the higher electrolyte environment associated with successive cycles of base addition eventually eliminates reversibility. Our model accurately predicts these multiple length scales phenomena. The underpinning concepts provide design principles for the dynamic control of other protein- and particle-based nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

ELVES-Dwarf. I. Satellite Systems of Eight Isolated Dwarf Galaxies in the Local Volume

The satellite populations of Milky Way (MW)–mass systems have been extensively studied, significantly advancing our understanding of galaxy formation and dark matter physics. In contrast, the satellites of lower-mass dwarf galaxies remain largely unexplored, despite hierarchical structure formation predicting that dwarf galaxies should host their own satellites. We present the first results of the ELVES-Dwarf survey, which aims to statistically characterize the satellite populations of isolated dwarf galaxies in the Local Volume (4 < D < 10 Mpc). We identify satellite candidates in integrated light using Legacy Surveys data and achieve completeness down to M g ≈ −9 mag. We then confirm the association of satellite candidates with host galaxies using surface-brightness fluctuation distances measured from Hyper Suprime-Cam data. We surveyed eight isolated dwarf galaxies with stellar masses ranging from sub-Small Magellanic Cloud to Large Magellanic Cloud scales $(10^{7.8} < M^{\textrm{host}}_{\star} < 10^{9.5} M_⊙)$, and confirmed six satellites with stellar masses between 10 5.6 and 10 8 M ⊙ . Most confirmed satellites are star-forming, in contrast to the primarily quiescent satellites observed around MW-mass hosts. By comparing observed satellite abundances and stellar mass functions with theoretical predictions, we find no evidence of a “missing satellite problem” in the dwarf galaxy regime.

Li, Jiaxuan 嘉轩李 [Princeton University, NJ (United ↗

DOE OSTI2022

Life Cycle Assessment for Closed-Loop Pumped Hydropower Energy Storage in the United States

The federal government has initiated an aggressive set of policies to achieve a net-zero carbon emission goal for the electricity sector by 2050. As a result, rapid growth in deployment of renewable energy technologies is expected. Most commercially mature technologies are temporally variable and do not provide grid inertia, while renewable technologies with high projected deployment have intermittent generation methods. Energy storage technologies are needed to both dispatch power on-demand and help provide the needed grid inertia. Pumped storage hydro (PSH) is a well-established technology that has gained renewed interest in recent years offering energy-balancing, grid stability, control of electrical network frequency, and large-scale storage capacity. For widespread adoption of PSH, more information is needed regarding its current life cycle environmental impacts. The objective of this study is to perform a full life cycle assessment (LCA) of new closed-loop PSH in the U.S. The functional unit for this study is 1 kWh of electrical power delivered to the grid and the base case project lifetime is 80 years. The life cycle inventory for this project accounts for all material and energy flows associated with the green-field construction, operation, maintenance, and decommissioning of a closed-loop PSH plant in the U.S. Collected data represents a range of potential PSH specifications and geographic locations coming from all prospective closed-loop PSH installations in the U.S. with data available. In addition, existing PSH installations are used to provide assumptions for inventory inputs. Results presented will include the global warming potential (GWP IPCC 100a) and Energy Return on Investment (EROI) from our base case (average PSH installation) as well as from scenario analyses and model sensitivity. These results will be compared to the impacts from existing PSH sites and alternate storage technologies. Methods align with the assumptions and guidelines put in place by previous PSH LCAs to ensure an accurate comparison with the results from this report.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗

DOE OSTI2022

Determination of Infinite Dilution Activity Coefficients of Molecular Solutes in Ionic Liquids and Deep Eutectic Solvents by Factorization-Machine-Based Neural Networks

Widely known as “green solvents,” ionic liquids (ILs) and deep eutectic solvents (DESs) have been used as substitutes for traditional organic solvents in separation science. To achieve better separations using ILs and DESs, this work aimed to predict the infinite dilution activity coefficients (IDACs) of molecular solutes in these solvents with the state-of-the-art factorization-machine-based neural network (DeepFM). DeepFM combines the benefits of factorization machines and deep neural networks to learn both low-order and high-order interactions among features. The IDAC prediction model was established with 52,372 experimental IDAC datapoints including 260 solvents (252 ILs and 8 DESs) and 112 molecular solutes collected at various temperatures from 288.15 to 428.15 K. Chemical information describing the ILs, DESs, and molecular solutes was included in the IDAC prediction model, including chemical functional groups, molecular weights, and Abraham solvation parameters. The IDAC prediction model showed an improved accuracy compared with alternative models; additionally, DESs were included in the IDAC prediction model for the first time. Here, the model will reduce the energy and resources needed to optimize the selection of ILs and DESs for specific separations, which will promote the development of these green solvents for sustainable chemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Tuning the Properties of Lignin‐Derived Deep Eutectic Solvents for Biomass Processing

Lignin-derived deep eutectic solvents (DESs) have been investigated as sustainable green media for biomass processing. However, the properties and processability of DESs have not been fully understood with the chemical structures of their constituents for biomass fractionation. Here, in this article, the properties of the phenolic DESs are discussed with different numbers of functional groups, such as –OCH 3 and –CHO in their hydrogen bond donor (HBD) structures. The formation of DES is significantly related to the hydrogen bond between its constituents, identified by nuclear magnetic resonance (NMR) analysis and density functional theory calculation (DFT). Lower viscosity and net basicity of DES are achieved with fewer –OCH 3 on HBD structures, resulting in enhanced processability and fractionation efficiency. The thermal stability of the DES is also influenced by the –OCH 3 and –CHO of HBD, as indicated by its onset temperature. The recyclability of the phenolic DES is confirmed by the fractionation performance of the recycled DES. Understanding the structural impacts of DES constituents on the properties and performance is crucial for designing solvents in biorefinery applications.

Ryu, Jiae [State University of New York (SUNY), Sy↗

DOE OSTI2024

Plant Metabolic Network 16: expansion of underrepresented plant groups and experimentally supported enzyme data

Abstract The Plant Metabolic Network (PMN) is a free online database of plant metabolism available at https://plantcyc.org. The latest release, PMN 16, provides metabolic databases representing >1200 metabolic pathways, 1.3 million enzymes, >8000 metabolites, >10 000 reactions and >15 000 citations for 155 plant and green algal genomes, as well as a pan-plant reference database called PlantCyc. This release contains 29 additional genomes compared with PMN 15, including species listed by the African Orphan Crop Consortium and nonflowering plant species. Furthermore, 52 new enzymes with experimentally supported function information have been included in this release. The single-species databases contain a combination of experimental information from the literature and computationally predicted information obtained through PMN’s database generation pipeline for a single species, while PlantCyc contains only experimental information but for any species within Viridiplantae. PMN is a comprehensive resource for querying, visualizing, analyzing and interpreting omics data with metabolic knowledge. It also serves as a useful and interactive tool for teaching plant metabolism.

Hawkins, Charles (ORCID:0000000312849047)↗

DOE OSTI2024

Corrosion Engineering of Part‐Per‐Million Single Atom Pt 1 /Ni(OH) 2 Electrocatalyst for PET Upcycling at Ampere‐Level Current Density

The plastic waste issue has posed a series of formidable challenges for the ecological environment and human health. While conventional recycling strategies often lead to plastic down-cycling, the electrochemical strategy of recovering valuable monomers enables an ideal, circular plastic economy. Here a corrosion synthesized single atom Pt 1 /Ni(OH) 2 electrocatalyst with part-per-million noble Pt loading for highly efficient and selective upcycling of polyethylene terephthalate (PET) into valuable chemicals (potassium diformate and terephthalic acid) and green hydrogen is reported. Electro-oxidation of PET hydrolysate, ethylene glycol (EG), to formate is processed with high Faraday efficiency (FE) and selectivity (>90%) at the current density close to 1000 mA cm −2 (1.444 V vs RHE). The in situ spectroscopy and density functional theory calculations provide insights into the mechanism and the understanding of the high efficiency. Remarkably, the electro-oxidation of EG at the ampere-level current density is also successfully illustrated by using a membrane-electrode assembly with high FEs to formate integrated with hydrogen production for 500 h of continuous operation. In conclusion, this process allows valuable chemical production at high space-time yield and is highly profitable (588–700 $\$$ ton −1 PET), showing an industrial perspective on single-atom catalysis of electrochemical plastic upcycling.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Room‐Temperature Phosphorescent Platinum(II) Alkynyls with Microsecond Lifetimes Bearing a Strong‐Field Pincer Ligand

Abstract The use of organometallic triplet emitters in organic light emitting diodes (OLEDs) is motivated by the premise of efficient intersystem crossing leading to unit internal quantum efficiencies. However, since most devices are based on solid‐state components, an inherent limitation to square‐planar platinum(II) phosphors is their tendency toward aggregation‐based quenching. Here, a new class of emissive, four‐coordinate Pt II species based on the bisimidazolyl carbazolide (BIMCA) ligand is introduced, which displays highly efficient, long‐lived solid‐state phosphorescence at room temperature. A set of four BIMCAPt phenyl acetylides were synthesized that emit in the green ( λ max =507–540 nm) with >60 % quantum yield and millisecond lifetimes. The structures of the resulting species reveal a non‐planar structure imposed by steric clashes between BIMCA and the iodo or alkynyl co‐ligand. Ground‐state and photophysical characterization are presented. Density functional theory calculations indicate that the BIMCA ligand dominates the frontier orbitals along with the first Franck–Condon singlet and triplet excited states.

Liska, Tadeas↗

DOE OSTI2025

Inkless, dry printing nanographene via in-Situ Coordinated laser ablation and sintering processes

Printing carbon, such as graphene and other carbon structures, for flexible and printed electronics currently relies on either ink-based printing, laser-induced forward transfer (LIFT), or laser-induced graphitization (LIG) to convert carbon-rich precursor materials, such as polymers, to graphene-like carbon structures. Liquid inks contain toxic solvents, surfactants, and stabilizing additives that degrade electrical conductivity and require high-temperature post-processing. On the other hand, LIG is limited by the substrate. Here, this study introduces an additive manufacturing method for dry-printing carbon nanomaterials, ranging from amorphous carbon to crystalline graphene-like structures, on various substrates. The system utilizes laser ablation of a solid graphite target to create pure carbon nanoparticles in situ and on demand. An inert gas carries the nanoparticles onto the substrate, where they can be deposited either as amorphous structures or laser-sintered in real time to form various graphitic structures. The study of laser processing parameters, specifically fluence and pulse repetition frequency, revealed three unique regimes of nanostructure evolution that influence the morphological and electrical properties of these printed structures. Raman spectroscopy confirmed graphitization with a resistivity slightly higher than that of the bulk graphite target. The conductivity/resistivity could be tuned as a function of sintering laser power. Scanning transmission electron microscopy (STEM) revealed that turbostratic nanographene formed with an interlayer spacing of 0.40 nm. Despite ink-based printing methods, such as screen printing, inkjet printing (IJP), and aerosol jet printing (AJP), this eco-friendly and green manufacturing technique could eliminate toxic chemicals, reduce environmental impact, and enable single-step fabrication of carbon-based devices for applications in wearable sensors, energy storage, flexible electronics, and Internet of Things (IoT) devices.

Additive nanomanufacturing↗

DOE OSTI2021

Microbial Membranes: A Challenge for Bioenergy

The production of bioenergy and bioproducts from lignocellulosic biomass promises to contribute significantly to the establishment of a clean, green economy. However, obstacles remain to making this industry economically viable. Among these is achieving high production rates and titers of target molecules through fermentation: microorganisms used in bioprocesses are inhibited by the toxic effects of biomass pretreatment and biofuel solvents which degrade the overall function of biological membranes. Here, we review historical research on the structure of the plasma membrane before detailing some progress on understanding the effects of amphiphilic solvents relevant to biofuel production on microbial membranes at the nanoscale.

09 BIOMASS FUELS↗

DOE OSTI2024

Assessment of Cementitious Composites for High-Temperature Geothermal Wells

High-temperature (HT) geothermal wells can provide green power 24 hours a day, 7 days a week. Under harsh environmental and operational conditions, the long-term durability requirements of such wells require special cementitious composites for well construction. This paper reports a comprehensive assessment of geothermal cement composites in cyclic pressure function laboratory tests and field exposures in an HT geothermal well (300–350 °C), as well as a numerical model to complement the experimental results. Performances of calcium–aluminate cement (CAC)-based composites and calcium-free cement were compared against the reference ordinary Portland cement (OPC)/silica blend. The stability and degradation of the tested materials were characterized by crystalline composition, thermo-gravimetric and elemental analyses, morphological studies, water-fillable porosity, and mechanical property measurements. All CAC-based formulations outperformed the reference blend both in the function and exposure tests. The reference OPC/silica lost its mechanical properties during the 9-month well exposure through extensive HT carbonation, while the properties of the CAC-based blends improved over that period. The Modified Cam-Clay (MCC) plasticity parameters of several HT cement formulations were extracted from triaxial and Brazilian tests and verified against the experimental results of function cyclic tests. These parameters can be used in well integrity models to predict the field-scale behavior of the cement sheath under geothermal well conditions.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Pectic-AGP is a major form of Arabidopsis AGPs

As a key component in cell walls of numerous organisms ranging from green algae to higher plants, AGPs play principal roles in many biological processes such as cell-cell adhesion and regulating Ca 2+ signaling pathway as a Ca 2+ -capacitor. Consistently, AGP structures vary from species to species and from tissue to tissue. To understand the functions of AGPs, it is vital to know their structural differences relative to their location in the plant. Thus, AGPs were purified from different Arabidopsis tissues. Analyses of these AGPs demonstrated that the AGPs comprised covalently linked pectin and AGP, referred to as pectic-AGPs. Importantly, these pectic-AGPs were glycosylated with a remarkable variety of polysaccharides including homogalacturonan, rhamnogalacturonan-I, and type II arabinogalactan at different ratios and lengths. Furthermore, this result not only suggests that pectic-AGP is a major form of Arabidopsis AGPs, but also supports AGPs serve as crosslinkers covalently connecting pectins with structures tailored for tissue-specific functions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Intermediate polaronic charge transport in organic crystals from a many-body first-principles approach

Abstract Charge transport in organic molecular crystals (OMCs) is conventionally categorized into two limiting regimes − band transport, characterized by weak electron-phonon (e-ph) interactions, and charge hopping due to localized polarons formed by strong e-ph interactions. However, between these two limiting cases there is a less well understood intermediate regime where polarons are present but transport does not occur via hopping. Here we show a many-body first-principles approach that can accurately predict the carrier mobility in this intermediate regime and shed light on its microscopic origin. Our approach combines a finite-temperature cumulant method to describe strong e-ph interactions with Green-Kubo transport calculations. We apply this parameter-free framework to naphthalene crystal, demonstrating electron mobility predictions within a factor of 1.5−2 of experiment between 100 and 300 K. Our analysis reveals the formation of a broad polaron satellite peak in the electron spectral function and the failure of the Boltzmann equation in the intermediate regime.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning

Abstract Green hydrogen production is crucial for a sustainable future, but current catalysts for the oxygen evolution reaction (OER) suffer from slow kinetics, despite many efforts to produce optimal designs, particularly through the calculation of descriptors for activity. In this study, we develop a dataset of density functional theory calculations of bulk and surface perovskite oxides, and adsorption energies of OER intermediates, which includes compositions up to quaternary and facets up to (555). We demonstrate that per-site properties of perovskite oxides such as Bader charge or band center can be tuned through element substitution and faceting, and develop a machine learning model that accurately predicts these properties directly from the local chemical environment. We leverage these per-site properties to identify promising perovskites with high theoretical OER activity. The identified design principles and promising materials provide a roadmap for closing the gap between current artificial catalysts and biological enzymes such as photosystem II.

Chemistry↗

DOE OSTI2022

On the equivalence of nonequilibrium and equilibrium measurements of slip in molecular dynamics simulations

Here, we show that nonequilibrium and equilibrium measurements of slip are consistent, provided the hydrodynamic wall location associated with the equilibrium measurement is properly taken into account. The latter is a strong function of the fluid state and wall-fluid interaction and cannot be neglected as it typically has been. Our results are based on an alternative approach for calculating the hydrodynamic wall location which alleviates most of the difficulties associated with its calculation via a Green-Kubo integral that appear to have contributed to its neglect. Extensive molecular dynamics simulations are used to validate our approach including a model for calculating the slip length that does not involve a Green-Kubo integral.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Root genetics in the field to understand drought adaptation and carbon sequestration (Final Scientific/Technical Report)

For all crop plants, roots play a critical role in growth. Roots anchor the plants, and are the primary site of nutrient and water uptake. Roots are also the main source of C to soil in the form of root tissues and exudates, and thus greatly influence SOM stocks. To perform these functions, primary roots extend into soil, producing a network of branching roots of characteristic form, known as its root system architecture (RSA). RSA varies among species, and among varieties within a species that are adapted to different environments. Root traits are major targets for the second green revolution because of their potential to improve crop productivity, increase drought tolerance and nutrient acquisition, and increase C capture of soil. Improving the quality of roots in maize will be particularly valuable, since this crop is planted on over 92 million acres annually in the US. The future sustainability of agricultural systems relies on their ability to enhance soil organic matter (SOM) storage and reduce GHG emissions, while maintaining or enhancing productivity. This program had two components, Sensors and Models. For the first component, we designed and built a high-throughput phenotyping platform for root pulling of maize plants. This eliminated the physical labor of manually pulling up plants and reduced the number of personnel required down to one. The standardized pulling mechanism allowed recording force curves during the pulling process, providing additional information. We validated that the maximum force for pulling the root system was well-correlated with the root system mass and provided root crowns for further RSA analysis. These root crowns identified significant correlations with 2D root area and root depth, along with 3D root volume, total root length and number of root tips. We then used this system for field-based studies in maize on the genetics of root system architecture and its relation to nitrogen-use efficiency (NUE), including using lines relevant to the Corteva breeding program. Varieties were also evaluated at Corteva sites in the cornbelt and Danforth farm in Missouri, to establish responses across sites. From these studies we have identified genetic loci associated with root traits and created mutant lines for these loci and correlations of root traits with NUE. For the Models component, we worked to incorporate root and soil characteristics into the MEMS 2.0 soil and ecosystem biogeochemical model. Existing soil C models, such as Century, are unable to represent specific root trait interactions with the soil environment and therefore to accurately forecast the potential C sequestration benefits of root breeding under different climatic and soil type conditions. We have developed the MEMS 2.0 ecosystem biogeochemical model to improve quantification of farm-scale soil carbon and greenhouse gas emissions. The new knowledge and large datasets produced by this project will be used to develop and drive an innovative model capable of forecasting the impacts on soil C stocks and nutrient dynamics. An innovation was to use the empirical data from the field studies (in 1, above) to model genetic variation in nitrogen use efficiencies and soil C input. Our work demonstrated that maize root-derived C rapidly replaces existing soil C and after 3 years of continuous maize, up to 20% of soil organic C in the topsoil (0-15cm) and 3% in the subsoil (15-30cm) was contributed by maize. However, this contribution did not entirely represent a net increase. Root C contribution to soil was affected by maize genetics. We have analyzed soils derived from the CSU field trials for C and N stocks, in the different soil physical fractions represented by the MEMS model, using both physical fractionation with elemental analyses, and Fourier transformed infrared spectroscopy. Data will be used to link crop nitrogen use efficiencies with soil C sequestration and provide data to bridge the field trials with the model development, for verification of model predictions. The project had a number of successful outcomes: we have used the new phenotyping platform to identify new genetic loci that can enhance root phenotypes; we have partnered with multiple maize seed companies phenotype varieties in their breeding programs; we have developed the MEMS model that can help inform industry on the potential for carbon sequestration in the agricultural sector, and which is now available at the CSU Soil Carbon Solutions Center for use.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Leaf microscopy applications in photosynthesis research: identifying the gaps

Abstract Leaf imaging via microscopy has provided critical insights into research on photosynthesis at multiple junctures, from the early understanding of the role of stomata, through elucidating C4 photosynthesis via Kranz anatomy and chloroplast arrangement in single cells, to detailed explorations of diffusion pathways and light utilization gradients within leaves. In recent decades, the original two-dimensional (2D) explorations have begun to be visualized in three-dimensional (3D) space, revising our understanding of structure–function relationships between internal leaf anatomy and photosynthesis. In particular, advancing new technologies and analyses are providing fresh insight into the relationship between leaf cellular components and improving the ability to model net carbon fixation, water use efficiency, and metabolite turnover rate in leaves. While ground-breaking developments in imaging tools and techniques have expanded our knowledge of leaf 3D structure via high-resolution 3D and time-series images, there is a growing need for more in vivo imaging as well as metabolite imaging. However, these advances necessitate further improvement in microscopy sciences to overcome the unique challenges a green leaf poses. In this review, we discuss the available tools, techniques, challenges, and gaps for efficient in vivo leaf 3D imaging, as well as innovations to overcome these difficulties.

Plant Sciences↗

DOE OSTI2025

Dateset for Zeolite-confined organolanthanide catalysts for C-H borylation of hydrocarbons

This dataset supports a publication, "Trimethylaluminum Activates Zeolite-Confined Lanthanum Borohydrides to Enhance Catalytic C–H Borylation", in the Journal of the American Chemical Society which describes the lanthanum borohydride catalyzed reaction of pinacolborane and aromatic, heteroaromatic and aliphatic hydrocarbons. The chemical affects of AlMe3 treatment on the precatalyst are explored in detail. The dataset includes characterization of the precatalyst using solid-state nuclear magnetic resonance spectroscopy, X-ray adsorption spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and density functional theory.

F-block chemistry↗