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DOE OSTI2024

Climate, Hydrology, and Nutrients Control the Seasonality of Si Concentrations in Rivers

Abstract The seasonal behavior of fluvial dissolved silica (DSi) concentrations, termedDSi regime, mediates the timing of DSi delivery to downstream waters and thus governs river biogeochemical function and aquatic community condition. Previous work identified five distinct DSi regimes across rivers spanning the Northern Hemisphere, with many rivers exhibiting multiple DSi regimes over time. Several potential drivers of DSi regime behavior have been identified at small scales, including climate, land cover, and lithology, and yet the large‐scale spatiotemporal controls on DSi regimes have not been identified. We evaluate the role of environmental variables on the behavior of DSi regimes in nearly 200 rivers across the Northern Hemisphere using random forest models. Our models aim to elucidate the controls that give rise to (a) average DSi regime behavior, (b) interannual variability in DSi regime behavior (i.e., Annual DSi regime), and (c) controls on DSi regime shape (i.e., minimum and maximum DSi concentrations). Average DSi regime behavior across the period of record was classified accurately 59% of the time, whereas Annual DSi regime behavior was classified accurately 80% of the time. Climate and primary productivity variables were important in predicting Average DSi regime behavior, whereas climate and hydrologic variables were important in predicting Annual DSi regime behavior. Median nitrogen and phosphorus concentrations were important drivers of minimum and maximum DSi concentrations, indicating that these macronutrients may be important for seasonal DSi drawdown and rebound. Our findings demonstrate that fluctuations in climate, hydrology, and nutrient availability of rivers shape the temporal availability of fluvial DSi.

Environmental Sciences & Ecology↗

DOE OSTI2020

Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides

The ability to predict the likelihood of impurity incorporation and their electronic energy levels in semiconductors is crucial for controlling its conductivity, and thus the semiconductor's performance in solar cells, photodiodes, and optoelectronics. The difficulty and expense of experimental and computational determination of impurity levels makes a data-driven machine learning approach appropriate. In this work, we show that a density functional theory-generated dataset of impurities in Cd-based chalcogenides CdTe, CdSe, and CdS can lead to accurate and generalizable predictive models of defect properties. By converting any semiconductor + impurity system into a set of numerical descriptors, regression models are developed for the impurity formation enthalpy and charge transition levels. These regression models can subsequently predict impurity properties in mixed anion CdX compounds (where X is a combination of Te, Se and S) fairly accurately, proving that although trained only on the end points, they are applicable to intermediate compositions. We make machine-learned predictions of the Fermi-level-dependent formation energies of hundreds of possible impurities in 5 chalcogenide compounds, and we suggest a list of impurities which can shift the equilibrium Fermi level in the semiconductor as determined by the dominant intrinsic defects. Machine learning predictions for the dominating impurities compare well with DFT predictions, revealing the power of machine-learned models in the quick screening of impurities likely to affect the optoelectronic behavior of semiconductors.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Tracking carrier and exciton dynamics in mixed-cation lead mixed-halide perovskite thin films

Mixed-cation lead mixed-halide perovskites simultaneously possess structural stability and high power conversion efficiency. A thorough study of both carrier and exciton dynamics is needed to understand the photophysical properties that underpin its superior photovoltaic performance. By utilizing a broadband transient absorption spectroscopy, we observe the carrier and exciton dynamics in a FA 0.85 Cs 0.15 Pb(I 0.97 Br 0.03 ) 3 (FCPIB) perovskite by simultaneously resolving the carrier and exciton contribution to the transient change of the absorption spectra, from which the carrier density and exciton oscillator strength can be determined. Our data reveal a quick and significant conversion of the photogenerated carriers to excitons, on top of the usual carrier recombination process. Moreover, the decay of carrier density shows a change of kinetics from a second-order recombination at high pump fluence to a third-order recombination at low pump fluence. Our analysis utilizes band anharmonicity, presents an independent determination of electronic temperature and quasi-Fermi energy, and reveals an interesting interplay among the processes of carrier cooling, exciton formation/decay and carrier recombination, all as a function of time after photoexcitation. Our work demonstrates the use of pump fluence as a knob to tune the relative populations of carriers and excitons in halide perovskite materials.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Molecular dynamics simulations of alkaline earth metal ions binding to DNA reveal ion size and hydration effects

The identity of metal ions surrounding DNA is key to its biological function and materials applications. In this work, we compare atomistic molecular dynamics simulations of double strand DNA (dsDNA) with four alkaline earth metal ions (Mg 2+ , Ca 2+ , Sr 2+ , and Ba 2+ ) to elucidate the physical interactions that govern DNA–ion binding. Simulations accurately model the ion–phosphate distance of Mg 2+ and reproduce ion counting experiments for Ca 2+ , Sr 2+ , and Ba 2+ . Our analysis shows that alkaline earth metal ions prefer to bind at the phosphate backbone compared to the major groove and negligible binding occurs in the minor groove. Larger alkaline earth metal ions with variable first solvation shells (Ca 2+ , Sr 2+ , and Ba 2+ ) show both direct and indirect binding, where indirect binding increases with ion size. Mg 2+ does not fit this trend because the strength of its first solvation shell predicts indirect binding only. Ions bound to the phosphate backbone form fewer contacts per ion compared to the major groove. Within the major groove, metal ions preferentially bind to guanine–cystosine base pairs and form simultaneous contacts with the N7 and O6 atoms of guanine. Overall, we find that the interplay among ion size, DNA–ion interaction, and the size and flexibility of the first solvation shell are key to predicting how alkaline earth metal ions interact with DNA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Kinetics and mechanisms of polycondensation reactions between aryl halides and bisphenol A

Aryl chlorides (ArCl) or aryl fluorides (ArF) were used in polycondensation reactions to form poly(arylene ether sulfone)s (PAES). Interestingly, the kinetics of the ArF reaction fit a third-order rate law, which is attributed to the activation of the carbon–fluorine bond by two potassium cations (at least one bound to phenolate), which form a three-body complex. Here, the ArCl monomer follows a second-order rate law, where a two-body complex forms at the initial state of the aromatic nucleophilic substitution (S N Ar) pathway. These metal cation-activated complexes act as intermediates during the attack by the nucleophile. This finding was reproduced with either the potassium or the sodium counterion (introduced via potassium carbonate or sodium carbonate). Through a combination of experimental analysis of reaction kinetics and computational calculations with density functional theory (DFT) methods, the present work extends the fundamental understanding of polycondensation mechanisms for two aryl halides and highlights the importance of the CX–metal interaction(s) in the S N Ar reaction, which is translational to other ion-activated substitution reactions.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Diacylglycerol enantiomer selectivity of diacylglycerol acyltransferases highlights metabolic specialization in triacylglycerol synthesis across the tree of life

Triacylglycerols are the major energy storage lipids in plants, animals, and microorganisms, and are predominantly produced by acyl-CoA:diacylglycerol (DAG) acyltransferases (DGATs). Two enantiomers of the DAG substrate, sn -1,2 and sn -2,3, can be produced by different biological mechanisms; however, little is known about which species produce each enantiomer, the selectivity of DGAT isoforms for either enantiomer, or whether DGAT enantiomer selectivity varies across organisms. Here, DAG enantiomer selectivity of DGAT1 and DGAT2 was measured from eight seed plants, two mammals, one oleaginous yeast, and one photosynthetic microalga using enantiomer-specific in vitro DGAT assays. Across most plants, DGAT1 favored sn -1,2-DAG, whereas DGAT2 preferentially utilized sn -2,3-DAG. However, there were several exceptions. Mammalian DGAT1, DGAT2, and microbial DGAT1s efficiently used both DAG enantiomers, while microbial DGAT2s had unique selectivity. The selectivity of several DGATs for combined acyl-CoA and DAG enantiomer molecular species were also evaluated for biotechnical applications. Therefore, DGAT DAG enantiomer selectivity is common yet strongly dependent on lineage and isoform and likely shaped in part by species-specific metabolic context of triacylglycerol synthesis, turnover, and remodeling. This work expands our understanding of DGAT function and establishes a foundation for leveraging enantiomer-selective acyltransferases in metabolic engineering of tailored lipid products.

Arabidopsis thaliana↗

DOE OSTI2020

First-principles study and experimental characterization of metal incorporation in germanium telluride

Germanium telluride is a well-known phase change material (PCM) used in non-volatile memory cells and radio frequency switches. Controlling the properties of GeTe for improved PCM device performance has sometimes been achieved by doping and/or alloying with metals, often at concentrations greater than 10 at. % and using non-equilibrium methods. Here, since switching PCMs between the low-resistance crystalline and high-resistance amorphous states requires a heating cycle, the stability of metal-incorporated GeTe (Ge 0.5–x M x Te 0.5 ) films is also critical to practical implementation of these materials in electronic and optoelectronic devices. In this work, we use both density-functional theory and experimental characterization methods to probe the solubility and critical properties of Ge 0.5–x M x Te 0.5 films. Using first-principles calculations, we determine the enthalpy of formation for GeTe with 2.08, 4.17, and 6.25 at. % of Cu, Fe, Mn, Mo, and Ti and show trends between the stability of the Ge 0.5–x M x Te 0.5 systems and the atomic position, composition, and distribution of the metal atoms in the GeTe matrix.

36 MATERIALS SCIENCE↗

DOE OSTI2025

High-rate magnetron sputter deposition of low-stress boron carbide films on tilted substrates

Boron carbide is attractive for several applications, including nuclear fuel capsules for inertial confinement fusion (ICF). The fabrication of ICF capsules involves the deposition of ultrathick coatings with density and thickness uniformity on submicron length scales on non-planar (spherical) substrates. Such a deposition requires control of the deposition rate, residual stress, and film microstructure. Here, we systematically study the direct-current magnetron sputter deposition of B 4 C coatings with a full-face-erosion magnetron source as a function of substrate tilt and Ar working gas pressure. Film properties are correlated with results of plasma diagnostics and predictions of Monte Carlo simulations of ballistic sputtering and gas-phase transport. The fabrication of low-stress amorphous B 4 C films with deposition rates of 7μm/h is demonstrated.

Kawasaki, K. [Lawrence Livermore National Laborato↗

DOE OSTI2025

Leaky ribosomal scanning enables tunable translation of bicistronic ORFs in green algae

Advances in sequencing technology have unveiled examples of nucleus-encoded polycistrons, once considered rare. Exclusively polycistronic transcripts are prevalent in green algae, although the mechanism by which multiple polypeptides are translated from a single transcript is unknown. Here, we used bioinformatic and in vivo mutational analyses to evaluate competing mechanistic models for translation of bicistronic mRNAs in green algae. High-confidence manually curated datasets of bicistronic loci from two divergent green algae, Chlamydomonas reinhardtii and Auxenochlorella protothecoides, revealed a preference for weak Kozak-like sequences for ORF 1 and an underrepresentation of potential initiation codons before the ORF 2 start codon, which are suitable conditions for leaky ribosome scanning to allow ORF 2 translation. We used mutational analysis in A. protothecoides to test the mechanism. In vivo manipulation of the ORF 1 Kozak-like sequence and start codon altered reporter expression at ORF 2, with a weaker Kozak-like sequence enhancing expression and a stronger one diminishing it. A synthetic bicistronic dual reporter demonstrated inversely adjustable activity of green fluorescent protein expressed from ORF 1 and luciferase from ORF 2, depending on the strength of the ORF 1 Kozak-like sequence. Our findings demonstrate that translation of multiple ORFs in green algal bicistronic transcripts is consistent with episodic leaky scanning of ORF 1 to allow translation at ORF 2. This work has implications for the potential functionality of upstream open reading frames (uORFs) found across eukaryotic genomes and for transgene expression in synthetic biology applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Probing the limits of cosmological information from the Lyman- α forest 2-point correlation functions

The standard cosmological analysis with the Lyα forest relies on a continuum fitting procedure that suppresses information on large scales and distorts the three-dimensional correlation function on all scales. In this work, we present the first cosmological forecasts without continuum fitting distortion in the Lyα forest, focusing on the recovery of large-scale information. Using idealized synthetic data, we compare the constraining power of the full shape of the Lyα forest auto-correlation and its cross-correlation with quasars using the baseline continuum fitting analysis versus the true continuum. We find that knowledge of the true continuum enables a ∼ 10% reduction in uncertainties on the Alcock-Paczyński (AP) parameter and the matter density, Ω m . We also explore the impact of large-scale information by extending the analysis up to separations of 240 h -1 Mpc along and across the line of sight. The combination of these analysis choices can recover significant large-scale information, yielding up to a ∼ 15% improvement in AP constraints. This improvement is analogous to extending the Lyα forest survey area by ∼ 40%.

Lyman alpha forest↗

DOE OSTI2020

Vectorization techniques for probability distribution functions using VecCore

Probability distribution functions (PDFs) are very used in modeling random processes and physics simulations. Improving the performance of algorithms that generate many random numbers under complex PDFs is often a very challenging task when methods as direct functions are not available. In this work we present general strategies on how to vectorize some PDFs using VecCore library. We show the results for the Exponential, Gaussian, discrete Poisson and Gamma probability distributions.

Chaparro Amaro, Oscar R.↗

DOE OSTI2020

Theory of strain-induced magnetic order and splitting of $T_c$ and $T_{\text{TRSB}}$ in Sr 2 RuO 4

The internal structure of the superconducting state in Sr 2 RuO 4 remains elusive at present, and exhibits evidence for time-reversal symmetry breaking. Recent muon spin relaxation measurements under uniaxial strain have revealed an increasing splitting between the superconducting critical temperature $T_c$ and the onset of time-reversal symmetry breaking $T_{\text{TRSB}}$ with applied strain. In addition, static magnetic order is induced by the uniaxial strain beyond ~1 GPa, indicating that unstrained Sr 2 RuO 4 is close to a magnetic quantum critical point. Here we perform a theoretical study of the magnetic susceptibility and the associated pairing structure as a function of uniaxial strain. In this work, it is found that the recent muon relaxation data can be qualitatively explained from the perspective of spin-fluctuation mediated pairing and the associated strain dependence of accidentally degenerate pair states in unstrained Sr 2 RuO 4 . In addition, while unstrained Sr 2 RuO 4 features mainly (2π /3, 2π /3) magnetic fluctuations, uniaxial strain promotes (π, ±π /2) magnetic order.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Effect of localization on photoluminescence and zero-field splitting of silicon color centers

The study of defect centers in silicon has been recently reinvigorated by their potential applications in optical quantum information processing. A number of silicon defect centers emit single photons in the telecommunication O-band, making them promising building blocks for quantum networks between computing nodes. The two-carbon G-center, self-interstitial W-center, and spin-1/2 T-center are the most intensively studied silicon defect centers, yet despite this, there is no consensus on the precise configurations of defect atoms in these centers, and their electronic structures remain ambiguous. Here, in this work, we employ ab initio density functional theory to characterize these defect centers, providing insight into the relaxed structures, band structures, and photoluminescence spectra, which are compared to experimental results. Motivation is provided for how these properties are intimately related to the localization of electronic states in the defect centers. In particular, we present the calculation of the zero-field splitting for the excited triplet state of the G-center defect as the structure is linearly interpolated from the A-configuration to the B-configuration, showing a sudden increase in the magnitude of the D zz component of the zero-field-splitting tensor. By performing projections onto the local orbital states of the defect, we analyze this transition in terms of the symmetry and bonding character of the G-center defect, which sheds light on its potential application as a spin-photon interface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Targeted Dy intercalation under graphene/SiC for tuning its electronic band structure

Metal intercalation of graphene is a promising method to tune its electronic band structure and generate novel electronic and topological phases. The tuning depends critically on the ability to bond the intercalated atoms at predesigned, subsurface interlayer locations because the emerging band structure depends on metal location. In this work, we have studied Dy intercalation under single-layer graphene (SLG) on SiC using spot profile analysis–low-energy electron diffraction and scanning tunneling microscopy (STM). The experimental work is complemented with density-functional theory (DFT) analysis. Because different diffraction spots originate from different subsurface interlayer regions, it is possible to identify changes in the intercalation location by monitoring the spot intensity as a function of growth conditions. DFT calculations of the chemical potential as a function of intercalated Dy coverage support the variation of the stability of the intercalated phase at different intercalated locations. The preferred location is confirmed from STM studies showing the removal of the 6 × 6 moiré corrugation at the preferred location, observed at higher Dy coverage.

2-dimensional systems↗

DOE OSTI2023

Extracting model-independent nuclear level densities away from stability

The nuclear level density (NLD) is a fundamental measure of the complex structure of atomic nuclei at relatively high energies. Here, in this study, we present the first model-independent measurement of the absolute partial NLD for a short-lived nucleus. For this purpose we adapt the recently introduced “shape method” for β-decay experiments, providing the shape of the γ-ray strength function for exotic nuclei. In this work, we show that combining the shape method with the β-Oslo technique allows for the extraction of the NLD of the populated states without the need for theoretical input. This development opens the way for the extraction of experimental NLDs far from stability with major implications in astrophysical and other applications. We benchmark our approach using data for the stable 76 Ge nucleus, finding excellent agreement with previous experimental results. In addition, we present new experimental data and determine the absolute partial level density for the short-lived 88 Kr nucleus. Our results suggest a fivefold increase in the NLD for the case of 88 Kr, compared to the recommended values from semimicroscopic Hartree-Fock Bogoliubov calculations recommended by the RIPL3 nuclear data library. However, our results are in good agreement with other semimicroscopic level density models. We demonstrate the impact of our method on the 87 Kr(n, γ) neutron capture rate and show that our experimental uncertainties for NLDs fulfill the requirements needed for astrophysical calculations predicting r-process abundances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Factors influencing quantum evaporation of helium from polar semiconductors from first principles

While there is much indirect evidence for the existence of dark matter (DM), to date it has evaded detection. Current efforts focus on DM masses over ~GeV—to push the sensitivity of DM searches to lower masses, new DM targets and detection schemes are needed. In this work, we focus on the latter—a novel detection scheme recently proposed to detect 10–100 meV phonons in polar target materials. Previous work showed that well-motivated models of DM can interact with polar semiconductors to produce an athermal population of phonons. This new sensing scheme proposes that these phonons then facilitate quantum evaporation of 3 He from a van der Waals film deposited on the target material. However, a fundamental understanding of the underlying process is still unclear, with several uncertainties related to the precise rate of evaporation and how it can be controlled. In this work, we use ab initio density functional theory calculations to compare the adsorption energies of helium atoms on a polar target material, sodium iodide, to understand the underlying evaporation physics. We explore the role of surface termination, monolayer coverage, and elemental species on the rate of He evaporation from the target material. Using this, we discuss the optimal target features for He-evaporation experiments and their range of tunability through chemical and physical modifications such as applied field and surface termination.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Feynman path integrals for discrete-variable systems: Walks on Hamiltonian graphs

We propose a natural, parameter-free, discrete-variable formulation of Feynman path integrals. We show that for discrete-variable quantum systems, Feynman path integrals take the form of walks on the graph whose weighted adjacency matrix is the Hamiltonian. By working out expressions for the partition function and transition amplitudes of discretized versions of continuous-variable quantum systems, and then taking the continuum limit, we explicitly recover Feynman's continuous-variable path integrals. We also discuss the implications of our result.

Feynman diagrams↗

DOE OSTI2026

Validated ligand geometries for macromolecular refinement restraints and molecular-mechanics force fields

In macromolecular structure refinement, the low observation-to-parameter ratio and the lack of high-resolution data are countered by using a priori information in the form of restraints. Having accurate geometries of the chemical entities in the sample is paramount for generating accurate chemical restraints and, therefore, accurate macromolecular structures. In particular, it is desirable to have accurate restraints for known and novel ligand entities. Quantum mechanics (QM) can minimize the energy of a ligand by adjusting its geometry, and these geometries can be used to generate restraints for macromolecular refinement. This article describes a library of approximately 37 000 small molecules extracted from the Chemical Component Dictionary in the Protein Data Bank and minimized by density-functional QM. The library includes restraint files for use in crystallography or cryo-EM refinement, along with files suitable for molecular-dynamics simulation. Because the geometries are validated using the Cambridge Structural Database, the restraints library provides users with both functional restraints and minimized geometries. This work also provides procedures for generating new and accurate restraints.

Amber↗