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At least 1,729 records · Page 96

Isotopic determination of uranium in soil by laser induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) operated under ambient pressure has been evaluated for isotopic analysis of uranium in real-world samples such as soil, with U concentrations in the single digit percentage levels. The study addresses the requirements for spectral decomposition of 235 U and 238 U atomic emission peaks that are only partially resolved. Although non-linear least-square fitting algorithms are typically able to locate the optimal combination of fitting parameters that best describes the experimental spectrum even when all fitting parameters are treated as free independent variables, the analytical results of such an unconstrained free-parameter approach are ambiguous. In this work, five spectral decomposition algorithms were examined, with different known physical properties (e.g., isotopic splitting, hyperfine structure) of the spectral lines sequentially incorporated into the candidate algorithms as constraints. It was found that incorporation of such spectral-line constraints into the decomposition algorithm is essential for the best isotopic analysis. The isotopic abundance of 235 U was determined from a simple two-component Lorentzian fit on the U II 424.437 nm spectral profile. For six replicate measurements, each with only fifteen laser shots, on a soil sample with U concentration at 1.1% w/w, the determined 235 U isotopic abundance was (64.6 ± 4.8)%, and agreed well with the certified value of 64.4%. Another studied U line - U I 682.691 nm possesses hyperfine structure that is comparatively broad and at a significant fraction as the isotopic shift. Thus, 235 U isotopic analysis with this U I line was performed with spectral decomposition involving individual hyperfine components. For the soil sample with 1.1% w/w U, the determined 235 U isotopic abundance was (60.9 ± 2.0)%, which exhibited a relative bias about 6% from the certified value. The bias was attributed to the spectral resolution of our measurement system - the measured line width for this U I line was larger than its isotopic splitting. In conclusion, although not the best emission line for isotopic analysis, this U I emission line is sensitive for element analysis with a detection limit of 500 ppm U in the soil matrix; the detection limit for the U II 424.437 nm line was 2000 ppm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Separation of sugars and phenolics from the heavy fraction of bio-oil using polymeric resin adsorbents

This work describes the equilibrium and kinetic adsorption of levoglucosan and a mixture of phenolic species from an aqueous solution on two polymeric resin adsorbents, SP207 and XAD4. The separation of sugars from phenolic species is of interest as these species comprise a product stream from a unique fractionating bio-oil recovery system. Levoglucosan is the major sugar present in this product stream, with mannose, xylose, galactose, and cellobiosan present in minor extents. The phenolic species are a complex mixture of mono- and di-substituted phenols; however, we treat them as a single group of similar chemical species that must be removed before the aqueous sugar solution can be used as fermentation substrate. Adsorption isotherms and mass transfer coefficients were determined at 22 °C. Levoglucosan isotherms were fit with linear and Langmuir models. Phenolic species isotherms were fit with both Langmuir and Freundlich models although they more clearly exhibited Langmuir adsorption behavior. Adsorption equilibria show that both polymeric resins have an order of magnitude greater mass adsorption capacity for phenolic species compared to levoglucosan when the mixture is used as the applied solution. However, the kinetics of adsorption are approximately an order of magnitude slower for phenolic species versus levoglucosan. Here, the equilibrium-dispersive model for column chromatography was applied using the determined adsorption equilibria and kinetic parameters and compared to column elution experiments. The model provided a good fit to the column data; however, the fit was improved by replacing the single component isotherms with competitive Langmuir isotherm expressions and modestly lowering the phenolics mass transfer coefficient.

09 BIOMASS FUELS↗

Performance characterization of nanofiltration, reverse osmosis, and ion exchange technologies for acetic acid separation

A major obstacle to widespread implementation of bio-based fuels and chemicals is the lack of efficient and costeffective separation methods. To purify acetic acid produced by biochemical conversion of biomass via anaerobic digestion, this work employs two commonly used separation technologies: (1) ion-exchange (IX) resin and (2) pressure-driven membranes. This study tested five commercially available strong- and weak-base anion-exchange resins and five commercially available nanofiltration (NF) and reverse osmosis (RO) membranes. The pH of the feed solution significantly affected adsorption capacity. At pH 6.3, a strong-base IX resin (IRN-78) performed best (95.1% acetate removal). With strong-base IX resins, the Langmuir isotherm model fit well, whereas for weak-base IX resins, the Freundlich isotherm provided a better fit. A pseudo-second-order kinetic model fit well for both IRN-78 and IRA-67. Regarding membrane separation, RO (BW30XFR membrane) achieved the highest rejection (98.6% acetate rejection), whereas an NF membrane (NF*) achieved the best combination of permeate flux (105 L/(h∙m 2 )) and rejection (83.1% acetate rejection). For membrane performance, the experimental data were fit using the solution diffusion model. Increased pH in the feed solution lowered permeate flux but increased acetic acid rejection. Finally, then the acetic acid concentration in the feed solution increased, both permeate flux and acetic acid rejection decreased for membrane NF*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring Activation and Luminescence Time Scales of Upconverting NaYF 4 :Yb,Er Nanocrystals

Accurate determination of upconversion and luminescence lifetimes requires kinetic modeling of the complete time-resolved response for upconversion luminescence of NaYF4:Yb,Er nanocrystals. Prior investigations typically perform exponential fitting of the tail in the time profile or employ complex systems of differential equations to extract lifetimes. To simplify analysis while fitting the entire time-resolved response, this work introduces a set of simplified models that model the response as a convolution of upconversion and fluorescence processes. Models for two- and three-photon upconversion processes are developed and tested for NaYF4:Yb,Er nanocrystals excited by a 980 nm laser. The results are presented for the transitions 2 H 11/2 , 4 S 3/2 → 4 I 15/2 (530 nm, green emission), 4 F 9/2 → 4 I 15/2 (650 nm, red emission), and 2 H 9/2 → 4 I 15/2 (400 nm, blue emission). Even with the same number of fitting parameters, the two- and three-photon models resulted in better fitting than the simpler models of single and two convolved exponentials for 30 nm, 400 nm, and silica-coated 30 nm nanoparticles. We provide evidence that the longest time scales (0.5–4 ms) are due to the luminescence of the final state, that the energy transfer waiting times leading to upconversion are shorter (<0.1 ms), and that more than two waiting times are required to explain the entire time response. The long-time response deviates from single-exponential behavior more strongly in uncoated and silica-coated 30 nm particles than for 400 nm particles. This deviation may result from heterogeneity of the local environment of ions within the 30 nm particles.

36 MATERIALS SCIENCE↗

LASSO for CALPHAD Model Selection Enables Data-Efficient Thermodynamic Modeling: An Application in Thermochemical Hydrogen Production Materials

Phenomenological CALPHAD (CALculation of PHAse Diagrams) models, widely used for multicomponent materials, often contain a considerable number of parameters and require fitting using data from a relatively small number of experimental measurements or theoretical calculations. Sometimes these parameters are introduced for the purpose of improving model fits but without clear physical justification, which leads to overparametrized models with poor generalization performance. Automated approaches for optimal model selection based on the available data therefore become critical. Here, in this work, a least absolute shrinkage and selection operator (LASSO)-based approach is developed for model selection by leveraging the linearity of the CALPHAD model with respect to its parameters to convert the model selection and fitting to a LASSO minimization problem. We demonstrate its utility for thermodynamic modeling of thermochemical hydrogen (TCH) production materials using lanthanum strontium manganite (LSM) as an example. Various TCH-relevant properties, including oxygen stoichiometry as a function of oxygen partial pressure, enthalpy of reduction, and entropy of reduction, are successfully predicted with reasonable accuracy using a minimal set of model parameters. Importantly, the model selection and fitting involve minimal human decision; it can therefore be applied to high-throughput DFT defect calculations and yield efficient workflows for TCH material modeling and optimization.

CALPHAD↗

evSeq: Cost-Effective Amplicon Sequencing of Every Variant in a Protein Library

Widespread availability of protein sequence-fitness data would revolutionize both our biochemical understanding of proteins and our ability to engineer them. Unfortunately, even though thousands of protein variants are generated and evaluated for fitness during a typical protein engineering campaign, most are never sequenced, leaving a wealth of potential sequence-fitness information untapped. Primarily, this is because sequencing is unnecessary for many protein engineering strategies; the added cost and effort of sequencing is thus unjustified. It also results from the fact that, even though many lower cost sequencing strategies have been developed, they often require at least some sequencing or computational resources, both of which can be barriers to access. In this work, we present every variant sequencing (evSeq), a method and collection of tools/standardized components for sequencing a variable region within every variant gene produced during a protein engineering campaign at a cost of cents per variant. evSeq was designed to democratize low-cost sequencing for protein engineers and, indeed, anyone interested in engineering biological systems. Execution of its wet-lab component is simple, requires no sequencing experience to perform, relies only on resources and services typically available to biology labs, and slots neatly into existing protein engineering workflows. Analysis of evSeq data is likewise made simple by its accompanying software (found at github.com/fhalab/evSeq, documentation at fhalab.github.io/evSeq), which can be run on a personal laptop and was designed to be accessible to users with no computational experience. Here, low-cost and easy to use, evSeq makes collection of extensive protein variant sequence-fitness data practical.

59 BASIC BIOLOGICAL SCIENCES↗

Systematic Assessment of Retrieval Methods for Canopy Far-Red Solar-Induced Chlorophyll Fluorescence Using High-Frequency Automated Field Spectroscopy

Remote sensing of solar-induced chlorophyll fluorescence (SIF) offers potential to infer photosynthesis across scales and biomes. Many retrieval methods have been developed to estimate top-of-canopy SIF using ground-based spectroscopy. However, inconsistencies among methods may confound interpretation of SIF dynamics, eco-physiological/environmental drivers, and its relationship with photosynthesis. Using high temporal- and spectral resolution ground-based spectroscopy, we aimed to (1) evaluate performance of SIF retrieval methods under diverse sky conditions using continuous field measurements; (2) assess method sensitivity to fluctuating light, reflectance, and fluorescence emission spectra; and (3) inform users for optimal ground-based SIF retrieval. Analysis included field measurements from bi-hemispherical and hemispherical-conical systems and synthetic upwelling radiance constructed from measured downwelling radiance, simulated reflectance, and simulated fluorescence for benchmarking. Fraunhofer-based differential optical absorption spectroscopy (DOAS) and singular vector decomposition (SVD) retrievals exhibit convergent SIF-PAR relationships and diurnal consistency across different sky conditions, while O2A-based spectral fitting method (SFM), SVD, and modified Fraunhofer line discrimination (3FLD) exhibit divergent SIF-PAR relationships across sky conditions. We find that such behavior holds across system configurations, though hemispherical-conical systems diverge less across sky conditions. O 2 A retrieval accuracy, influenced by atmospheric distortion, improves with a narrower fitting window and when training SVD with temporally local spectra. This may impact SIF-photosynthesis relationships interpreted by previous studies using O 2 A-based retrievals with standard (759–767.76 nm) fitting windows. Fraunhofer-based retrievals resist atmospheric impacts but are noisier and more sensitive to assumed SIF spectral shape than O 2 A-based retrievals. We recommend SVD or SFM using reduced fitting window (759.5–761.5 nm) for robust far-red SIF retrievals across sky conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Quantifying the local adaptive landscape of a nascent bacterial community

Abstract The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes (“L” and “S”) shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

59 BASIC BIOLOGICAL SCIENCES↗

Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning

Characterization of material structure with X-ray or neutron scattering using e.g. Pair Distribution Function (PDF) analysis most often rely on refining a structure model against an experimental dataset. However, identifying a suitable model is often a bottleneck. Recently, automated approaches have made it possible to test thousands of models for each dataset, but these methods are computationally expensive and analysing the output, i.e. extracting structural information from the resulting fits in a meaningful way, is challenging. Our Machine Learning based Motif Extractor (ML-MotEx) trains an ML algorithm on thousands of fits, and uses SHAP (SHapley Additive exPlanation) values to identify which model features are important for the fit quality. We use the method for 4 different chemical systems, including disordered nanomaterials and clusters. ML-MotEx opens for a type of modelling where each feature in a model is assigned an importance value for the fit quality based on explainable ML.

36 MATERIALS SCIENCE↗

CRISPRi-ART enables functional genomics of diverse bacteriophages using RNA-binding dCas13d

Bacteriophages constitute one of the largest reservoirs of genes of unknown function in the biosphere. Even in well-characterized phages, the functions of most genes remain unknown. Experimental approaches to study phage gene fitness and function at genome scale are lacking, partly because phages subvert many modern functional genomics tools. Here we leverage RNA-targeting dCas13d to selectively interfere with protein translation and to measure phage gene fitness at a transcriptome-wide scale. We find CRISPR Interference through Antisense RNA-Targeting (CRISPRi-ART) to be effective across phage phylogeny, from model ssRNA, ssDNA and dsDNA phages to nucleus-forming jumbo phages. Using CRISPRi-ART, we determine a conserved role of diverse rII homologues in subverting phage Lambda RexAB-mediated immunity to superinfection and identify genes critical for phage fitness. CRISPRi-ART establishes a broad-spectrum phage functional genomics platform, revealing more than 90 previously unknown genes important for phage fitness.

59 BASIC BIOLOGICAL SCIENCES↗

High-resolution lineage tracking reveals travelling wave of adaptation in laboratory yeast

In rapidly adapting asexual populations, including many microbial pathogens and viruses, numerous mutant lineages often compete for dominance within the population. These complex evolutionary dynamics determine the outcomes of adaptation, but have been difficult to observe directly. Previous studies have used whole-genome sequencing to follow molecular adaptation; however, these methods have limited resolution in microbial populations. Here we introduce a renewable barcoding system to observe evolutionary dynamics at high resolution in laboratory budding yeast. We find nested patterns of interference and hitchhiking even at low frequencies. These events are driven by the continuous appearance of new mutations that modify the fates of existing lineages before they reach substantial frequencies. We observe how the distribution of fitness within the population changes over time, and find a travelling wave of adaptation that has been predicted by theory. We show that clonal competition creates a dynamical ‘rich-get-richer’ effect: fitness advantages that are acquired early in evolution drive clonal expansions, which increase the chances of acquiring future mutations. However, less-fit lineages also routinely leapfrog over strains of higher fitness. Finally, our results demonstrate that this combination of factors, which is not accounted for in existing models of evolutionary dynamics, is critical in determining the rate, predictability and molecular basis of adaptation.

59 BASIC BIOLOGICAL SCIENCES↗

Potentiating antibiotic efficacy via perturbation of non-essential gene expression

Proliferation of multidrug-resistant (MDR) bacteria poses a threat to human health, requiring new strategies. Here we propose using fitness neutral gene expression perturbations to potentiate antibiotics. We systematically explored 270 gene knockout-antibiotic combinations in Escherichia coli, identifying 90 synergistic interactions. Identified gene targets were subsequently tested for antibiotic synergy on the transcriptomic level via multiplexed CRISPR-dCas9 and showed successful sensitization of E. coli without a separate fitness cost. These fitness neutral gene perturbations worked as co-therapies in reducing a Salmonella enterica intracellular infection in HeLa. Finally, these results informed the design of four antisense peptide nucleic acid (PNA) co-therapies, csgD, fnr, recA and acrA, against four MDR, clinically isolated bacteria. PNA combined with sub-minimal inhibitory concentrations of trimethoprim against two isolates of Klebsiella pneumoniae and E. coli showed three cases of re-sensitization with minimal fitness impacts. Our results highlight a promising approach for extending the utility of current antibiotics.

60 APPLIED LIFE SCIENCES↗

Tracing the outflow kinematics in Type 2 active galactic nuclei

Here, we used a sample of 577 spectra of active galactic nuclei Type 1.8-2 (z < 0.25) taken from the Sloan Digital Sky Survey to trace the influence of the outflow kinematics on the profiles of different emission lines (Hβ, [O III], Hα, [N II], [S II]). All considered lines were fitted with two Gaussian components: one that fits the core of the line, and another that fits the wings. We provide a procedure for decomposition of the Hα+[N II] wavelength band for spectra where these lines overlap. The influence of the gravitational and non-gravitational kinematics on the line components is investigated by comparing the dispersions of the line components with stellar velocity dispersion. We find that wing components of all the considered emission lines have pure non-gravitational kinematics. The core components are consistent with gravitational kinematics for the Hα, [N II], and [S II] lines, while in the [O III] there is evidence for contribution from non-gravitational kinematics. We adopted the wing components as a proxy for the outflow contribution and investigated the outflow kinematics by analysing the correlations between the widths and shifts of the wing components of different lines. For this purpose, we used the subsets in which wing components are detected in both compared lines, and can be fitted independently. We find strong correlations between wing component shifts, as well as between wing component widths of all considered lines, with the exception of the Hβ wing component width. These correlations indicate that outflow dynamics systemically affect all emission lines in the spectrum. However, it reflects with a different strength in their profiles, which is observed as different widths of the wing components. This is investigated by comparison of the mean widths of the wing components in subsets where wing components are present in all lines. The strongest outflow signature is observed in the [O III] lines, which have the broadest wing components; weaker outflow signatures are found in Hα and [N II], and the weakest is found for [S II]. These results imply that the considered lines arise in different parts of an outflowing region.

79 ASTRONOMY AND ASTROPHYSICS↗

Star formation rate and stellar mass calibrations based on infrared photometry and their dependence on stellar population age and extinction

The stellar mass (M $\star$ ) and the star formation rate (SFR) are among the most important features that characterize galaxies. Measuring these fundamental properties accurately is critical for understanding the present state of galaxies, their history, and future evolution. Infrared (IR) photometry is widely used to measure the M $\star$ and SFR of galaxies because the near-IR traces the continuum emission of the majority of their stellar populations (SPs), and the mid/far-IR traces the dust emission powered by star-forming activity. This work explores the dependence of the IR emission of galaxies on their extinction, and the age of their SPs. It aims to provide accurate and precise IR-photometry SFR and M $\star$ calibrations that account for SP age and extinction while providing quantification of their scatter. We used the CIGALE spectral energy distribution (SED) fitting code to create model SEDs of galaxies with a wide range of star formation histories, dust content, and interstellar medium properties. We fit the relations between M $\star$ and SFR with IR and optical photometry of the model-galaxy SEDs with the Markov chain Monte Carlo (MCMC) method. As an independent confirmation of the MCMC fitting method, we performed a machine-learning random forest (RF) analysis on the same data set. The RF model yields similar results to the MCMC fits, thus validating the latter. This work provides calibrations for the SFR using a combination of the WISE bands 1 and 3, or the JWST NIR-F200W and MIRI-F2100W. It also provides mass-to-light ratio calibrations based on the WISE band-1, the JWST NIR-F200W, and the optical u - r or g - r colors. These calibrations account for the biases attributed to the SP age, while they are given in the form of extinction-dependent and extinction-independent relations. The proposed calibrations show robust estimations while minimizing the scatter and biases throughout a wide range of SFRs and stellar masses. The SFR calibration offers better results, especially in dust-free or passive galaxies where the contributions of old SPs or biases from the lack of dust are significant. Similarly, the M $\star$ calibration yields significantly better results for dusty and high-SFR galaxies where dust emission can otherwise bias the estimations.

79 ASTRONOMY AND ASTROPHYSICS↗

The DESI DR1 peculiar velocity survey: Growth rate measurements from the galaxy power spectrum

The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios in which the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as fσ 8 , was extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models, and parameter-fitting framework were tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques were then applied to analyse the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey. The fit result of the growth rate is fσ8 = 0.440$^{+0.080}_{−0.096}$ at effective redshift zeff = 0.07. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation, and the power spectrum, a consensus value is yielded of fσ 8 (z eff = 0.07) = 0.450$^{+0.055}_{−0.055}$, and correspondingly we obtain γ = 0.580$^{+0.110}_{−0.110}$, Ω m = 0.301$^{+0.011}_{−0.011}$, and σ 8 = 0.834$^{+0.032}_{−0.032}$. The measured fσ8 and γ are consistent with the prediction of the Λ cold dark matter model and general relativity.

79 ASTRONOMY AND ASTROPHYSICS↗

Improved spectral analysis for the motional Stark effect diagnostic

The magnetic pitch angle and the magnitude from reversed field pinch plasmas in the Madison symmetric torus (MST) have been routinely obtained from fully resolved motional Stark effect (MSE) spectrum analyses. Recently, the spectrum fit procedure has been improved by initializing and constraining the fit parameters based on the MSE model in the atomic data and analysis structure. A collisional-radiative model with level populations nlm-resolved up to n= 4 and a simple Born approximation for ion-impact cross sections is used for this analysis. Measurement uncertainty is quantified by making MSE measurements with multiple views of a single spatial location, ranging 5%-15% for typical MST operation conditions. A multi-view fit improves the goodness of fit of MSE spectral features and background.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Linear-scaling explicitly correlated treatment of solids: Periodic local MP2-F12 method

Theory and implementation of the periodic local MP2-F12 method in the 3*A fixed-amplitude ansatz is presented. The method is formulated in the direct space, employing local representation for the occupied, virtual, and auxiliary orbitals in the form of Wannier functions (WFs), projected atomic orbitals (PAOs), and atom-centered Gaussian-type orbitals, respectively. Local approximations are introduced, restricting the list of the explicitly correlated pairs, as well as occupied, virtual, and auxiliary spaces in the strong orthogonality projector to the pair-specific domains on the basis of spatial proximity of respective orbitals. The 4-index two-electron integrals appearing in the formalism are approximated via the direct-space density fitting technique. In this procedure, the fitting orbital spaces are also restricted to local fit-domains surrounding the fitted densities. The formulation of the method and its implementation exploits the translational symmetry and the site-group symmetries of the WFs. Test calculations are performed on LiH crystal. The results show that the periodic LMP2-F12 method substantially accelerates basis set convergence of the total correlation energy, and even more so the correlation energy differences. The resulting energies are quite insensitive to the resolution-of-the-identity domain sizes and the quality of the auxiliary basis sets. The convergence with the orbital domain size is somewhat slower, but still acceptable. Moreover, inclusion of slightly more diffuse functions, than those usually used in the periodic calculations, improves the convergence of the LMP2-F12 correlation energy with respect to both the size of the PAO-domains and the quality of the orbital basis set. At the same time, the essentially diffuse atomic orbitals from standard molecular basis sets, commonly utilized in molecular MP2-F12 calculations, but problematic in the periodic context, are not necessary for LMP2-F12 treatment of crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Schottky barrier height measurements of Cu/Si(001), Ag/Si(001), and Au/Si(001) interfaces utilizing ballistic electron emission microscopy and ballistic hole emission microscopy

The Schottky barrier heights of both n and p doped Cu/Si(001), Ag/Si(001), and Au/Si(001) diodes were measured using ballistic electron emission microscopy and ballistic hole emission microscopy (BHEM), respectively. Measurements using both forward and reverse ballistic electron emission microscopy (BEEM) and (BHEM) injection conditions were performed. The Schottky barrier heights were found by fitting to a linearization of the power law form of the Bell-Kaiser BEEM model. The sum of the n-type and p-type barrier heights are in good agreement with the band gap of silicon and independent of the metal utilized. The Schottky barrier heights are found to be below the region of best fit for the power law form of the BK model, demonstrating its region of validity.

36 MATERIALS SCIENCE↗