Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “work functions”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,405 records · Page 78

Multiple redox mechanisms for water-gas shift reaction on Fe 3 O 4 (1 1 1) surface: A density functional theory and mean-field microkinetic modeling study

In this work, we investigated redox mechanisms for the high temperature (HT) water–gas shift reaction (WGSR) on the Fe 3 O 4 (1 1 1) surface using density functional theory (DFT) calculations and mean-field microkinetic modeling (MKM). The redox pathways branched into three Langmuir-Hinshelwood processes (LH1, LH2 and LH3) and one Mars-van-Krevelen (MVK) process (in the presence of oxygen vacancy) from multidentate binding of CO and CO 2 over four available reactive sites (Fe oct2 , Fe tet1 , Fe bridge, and O1). We found that the LH1 and LH2 processes have CO adsorption at a single iron site (Fe oct2 or Fe tet1 ), while the LH3 and MVK processes have stronger chemisorption of CO or CO 2 by both the Fe oct2 site and the O 1 site. From the mechanistic study of these reaction path, we recognized that availability of O 1 sites was key to proceed to either CO oxidation by the single site (LH1, LH2) or by the dual site (LH3, MVK). We observed that the reaction energetics were significantly different in the CO oxidation steps, where the single or dual site results in markedly different apparent activation energy (73–281 kJ/mol) and reaction rates (10 -3 –10 -10 mol∙m -2 ∙s -1 ) among the four reaction mechanisms. The utilization of mean field MKM with DFT reaction energetics helps explain the experimental debates for the catalytic reaction details as well as providing a possible direction to engineer the catalyst with higher activity.

42 ENGINEERING↗

Near Neutral pH Redox Flow Battery with Low Permeability and Long-Lifetime Phosphonated Viologen Active Species

A highly stable phosphonate-functionalized viologen is introduced in this work as the redox-active material in a negative potential electrolyte for aqueous redox flow batteries (ARFBs) operating at nearly neutral pH. The solubility is 1.23 m and the reduction potential is the lowest of any substituted viologen utilized in a flow battery, reaching –0.462 V versus SHE at pH = 9. The negative charges in both the oxidized and the reduced states of 1,1'-bis(3-phosphonopropyl)-[4,4'-bipyridine]-1,1'-diium dibromide ( BPP–Vi ) effect low permeability in cation exchange membranes and suppress a bimolecular mechanism of viologen decomposition. A flow battery pairing BPP–Vi with a ferrocyanide-based positive potential electrolyte across an inexpensive, non-fluorinated cation exchange membrane at pH = 9 exhibits an open-circuit voltage of 0.9 V and a capacity fade rate of 0.016% per day or 0.00069% per cycle. Overcharging leads to viologen decomposition, causing irreversible capacity fade. Our research introduces extremely stable, extremely low-permeating and low reduction potential redox active materials into near neutral ARFBs.

25 ENERGY STORAGE↗

Instability and treatments of the coupled discrete element and lattice Boltzmann method by the immersed moving boundary scheme

The immersed moving boundary (IMB) scheme has been extensively used to couple the discrete element method (DEM) with the lattice Boltzmann method (LBM). In the literature, only the formulation of IMB for lattice nodal cells covered by a single-solid particle was given. The treatment of situations where a nodal cell is covered by two or more solid particles is seldom discussed. It is found that some numerical instability can occur for such situations due to an inappropriate computation of the weighting function in the IMB formulation. This work presents an enhanced treatment that can resolve the issue and validates it using some benchmark tests. Furthermore, to avoid the extra costs associated with the treatment and simplify the complicated procedure introduced, a simplified IMB scheme is proposed. The accuracy of both enhanced and simplified IMB schemes are validated by test cases including single-particle sedimentation, two-particle drafting-kissing-tumbling phenomenon, and multiple-particle sedimentation. Then, the robustness of both schemes is examined and discussed using a specially designed flow past cylinders test. Overall, the simplified IMB scheme is proved to be robust and sufficiently accurate and simpler and more effective than the enhanced scheme.

42 ENGINEERING↗

Electropolymerized-molecularly imprinted polymers (E-MIPS) as sensing elements for the detection of dengue infection

Here, a straightforward in situ detection method for dengue infection was demonstrated through the molecular imprinting of a dengue nonstructural protein 1 (NS1) epitope into an electropolymerized molecularly imprinted polyterthiophene (E-MIP) film sensor. The key enabling step in the sensor fabrication is based on an epitope imprinting strategy, in which short peptide sequences derived from the original target molecules were employed as the main template for detection and analysis. The formation of the E-MIP sensor films was facilitated using cyclic voltammetry (CV) and monitored in situ by electrochemical quartz crystal microbalance (EC-QCM). Surface properties were analyzed using different techniques including atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and polarization modulation-infrared reflection-adsorption (PM-IRRAS). The standard calibration curve (R = 0.9830) was generated for the detection of the epitope, Ac-VHTWTEQYKFQ-NH 2 , with a linear range of 0.2 to 30 μg/mL and detection limit of 0.073 μg/mL. A separate calibration curve (R = 0.9786) was obtained using spiked buffered solutions of dengue NS1 protein, which resulted in a linear range of 0.2 to 10 μg/mL and a detection limit of 0.056 μg/mL. The fabricated E-MIP sensor exhibited long-term stability, high sensitivity, and good selectivity towards the targeted molecules. These results indicated that the formation of the exact and stable cavity imprints in terms of size, shape, and functionalities was successful. In our future work, we aim to use our E-MIP sensors for NS1 detection in real-life samples such as serum and blood.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pretreatment of lignocellulosic feedstocks for cellulose nanofibril production

Cellulose nanofibrils (CNFs) have attracted a great deal of research interest in recent years attributable to the low cost and abundance of lignocellulosic biomass from which they can be extracted. These materials have potential applications in a wide array of areas because of their unique properties such as ultra-high aspect ratios and specific strengths. However, the high energy required to extract CNFs from biomass through fibrillation often makes them prohibitively expensive or negates their inherent sustainability. As such, a variety of biomass treatments prior to fibrillation have been investigated by researchers to reduce the energy requirements of CNF extraction, improve the efficacy of biomass fibrillation and subsequent processes, and/or impart functionality in resulting nanofibrils. In this work, both widely used and emerging mechanical, chemical, and enzymatic pretreatments used prior to fibrillation of lignocellulosic biomass for CNF extraction are reviewed. Attention is given to the effect of these various pretreatments on the properties of the resulting CNFs. Finally, the energy consumption in fibrillation processes with and without the use of pretreatments is compared, and future perspectives on challenges and opportunities in lignocellulosic feedstock pretreatments are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

SuperCam Calibration Targets: Design and Development

Abstract SuperCam is a highly integrated remote-sensing instrumental suite for NASA’s Mars 2020 mission. It consists of a co-aligned combination of Laser-Induced Breakdown Spectroscopy (LIBS), Time-Resolved Raman and Luminescence (TRR/L), Visible and Infrared Spectroscopy (VISIR), together with sound recording (MIC) and high-magnification imaging techniques (RMI). They provide information on the mineralogy, geochemistry and mineral context around the Perseverance Rover. The calibration of this complex suite is a major challenge. Not only does each technique require its own standards or references, their combination also introduces new requirements to obtain optimal scientific output. Elemental composition, molecular vibrational features, fluorescence, morphology and texture provide a full picture of the sample with spectral information that needs to be co-aligned, correlated, and individually calibrated. The resulting hardware includes different kinds of targets, each one covering different needs of the instrument. Standards for imaging calibration, geological samples for mineral identification and chemometric calculations or spectral references to calibrate and evaluate the health of the instrument, are all included in the SuperCam Calibration Target (SCCT). The system also includes a specifically designed assembly in which the samples are mounted. This hardware allows the targets to survive the harsh environmental conditions of the launch, cruise, landing and operation on Mars during the whole mission. Here we summarize the design, development, integration, verification and functional testing of the SCCT. This work includes some key results obtained to verify the scientific outcome of the SuperCam system.

Manrique, J. A. (ORCID:0000000220532819)↗

Atomic structure and grain shape evolution of nanodiamond during annealing in oxidizing atmosphere from neutron diffraction and MD simulations

In this work, real space pair-distribution function (PDF) analysis in conjunction with molecular dynamics (MD) simulations was applied to characterize crystal structure, shape and surface structure of diamond nanoparticles annealed in air up to 880 °C. MD simulated models of individual nanodiamond particles of various shapes and sizes were used to calculate theoretical radial distribution functions G(r) for powders with different grain size distributions. The calculated curves, showing distinct differences for the explored parameter space, were compared to the experimental G(r) functions obtained from neutron scattering for annealed detonated nanodiamond samples in a search for a model best describing the actual powders. It was found that as-synthesized nanodiamond grains are terminated by equally abundant (100), (110) and (111) crystallographic faces and their structure does not change upon annealing in air up to 280 °C. The shape and size of grains annealed above 480 °C changes due to surface etching. The etching rate differs between crystals faces and depends on temperature, resulting in the observed differences in grain shape. Below 680 °C the share of the (110) facets gradually increases and at 680 °C the grains become rhombic dodecahedra terminated solely by (110) surfaces. Further increase of the annealing temperature promotes formation of (111) surfaces and at 880 °C the preferred grain shape becomes an octahedron terminated by a variant of (111) surfaces possessing three dangling sp3 bonds per atom. At lower temperatures all grains become smaller and the size distribution moves towards the lower values. Furthermore, as the annealing temperature increases, the smallest grains disappear entirely and the average grain size grows back.

36 MATERIALS SCIENCE↗

Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy

Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.

Crystallization↗

Deciphering the Cofilin Oligomers via Intermolecular Disulfide Bond Formation: A Coarse-Grained Molecular Dynamics Approach to Understanding Cofilin’s Regulation on Actin Filaments

Cofilin, a key actin-binding protein, orchestrates the dynamics of the actomyosin network through its actin-severing activity and by promoting the recycling of actin monomers. Recent experimental work suggests that cofilin also forms functionally distinct oligomers through thiol post-translational modification (PTM) that encourages actin nucleation and assembly. Despite these advances, the structural conformations of cofilin oligomers that modulate actin activity remain elusive because there are combinatorial ways to oxidize thiols in cysteines to form disulfide bonds rapidly. This study employs molecular dynamics simulations to investigate human cofilin 1 as a case study for exploring cofilin dimers via disulfide bond formation. Using the free energy profiling, our simulations unveil a range of probable cofilin dimer structures not represented in current Protein Data Bank entries. These candidate dimers are characterized by their distinct population distributions and relative free energies. Of particular note is a dimer featuring an interface between cysteines 139 and 147 residues, which demonstrates stable free energy characteristics and intriguingly symmetrical geometry. In contrast, the experimentally proposed dimer structure exhibits a less stable free energy profile. Here, we also evaluate frustration quantification based on the energy landscape theory in the protein-protein interactions at the dimer interfaces. Notably, the 39-39 dimer configuration emerges as a promising candidate for forming cofilin tetramers, as substantiated by frustration analysis. Additionally, docking simulations with actin filaments further evaluate the stability of these cofilin dimer-actin complexes. Our findings thus offer a computational framework for understanding the role of thiol post-translational modification cofilin proteins in regulating oligomerization, and the subsequent cofilin-mediated actin dynamics in the actomyosin network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long-Lived Excited State in a Solubilized Graphene Nanoribbon

Graphene nanoribbons have excellent light-absorbing properties, but often exhibit short excited-state lifetimes that prevent their applications in photocatalysis. Here, we report a long-lived charge-transfer triplet excited state in a well solubilized, chlorinated graphene nanoribbon (Cl-GNR) with edges modified by bipyrimidine (bpm) moieties. The photophysical behavior of Cl-GNR was observed and characterized by steady-state UV-vis absorption and emission spectroscopy, transient absorption spectroscopy on the ps-ms timescale, and density functional theory (DFT) calculations. In this work, both the Cl-GNR and its monomeric subunit, chlorinated graphene quantum dot (Cl-GQD), were synthesized using bottom-up techniques to produce the H- analogs of the compounds followed by edge-chlorination to achieve soluble products. The absorption spectra of Cl-GQD and Cl-GNR appear in the UV-vis range with lowest-energy peaks at 375 and 600 nm, respectively. The excitons in Cl-GNR were found to exhibit charge-transfer character with the bpm edges serving as electron acceptors. DFT calculations indicate that the excitons are relatively localized, spreading over at most two monomeric units of the GNR. Transient absorption spectroscopy shows that singlet excited states of Cl-GQD and Cl-GNR undergo intersystem crossing with ~300 ps lifetime to form triplet states that last for 15.7 μs (Cl-GQD) and 106 μs (Cl-GNR). These properties, combined with the ability of the bpm sites to coordinate transition metals, make Cl-GNRs promising light-harvesting motifs for photocatalytic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vibrational Fermi Resonance in Atomically Thin Black Phosphorus

Fermi resonance is a phenomenon involving the hybridization of two coincidentally quasi-degenerate states that is observed in the vibrational or electronic spectra of molecules. Despite numerous examples in molecular systems, vibrational Fermi resonances in dispersive semiconducting systems remain largely unexplored due to the rarity of occurrence. Here we report a vibrational Fermi resonance in atomically thin black phosphorus. The Fermi resonance arises via anharmonic mixing of a fundamental Raman mode and a Davydov component of an infrared mode, leading to a doublet with mixed character. The extent of Fermi coupling can be modulated by the application of external biaxial strain. The consequences of Fermi hybridization are revealed by electronic resonance effects in the thickness-dependent and excitation-wavelength-dependent Raman spectrum, which is predicted by ab initio hybrid functional simulations including excitonic interactions. This work reveals new insight into electron–phonon coupling in black phosphorus and demonstrates a novel method for modulating Fermi resonances in 2D semiconductors.

74 ATOMIC AND MOLECULAR PHYSICS↗

Chemically and Mechanically Recyclable Vitrimers from Carbon Dioxide-Based Polycarbonates

Designing thermoset materials with dynamic crosslinks is an important strategy to mitigate rising global carbon dioxide emission levels. The development of polymers from sustainable feedstocks, with efficient manufacturing methods, for high-value applications, and with circular end-of-use solutions is essential for advancing material technologies. One approach involves exploiting carbon dioxide itself as feedstock to create high performance, sustainable materials, by enchaining 50 mol% CO2 via copolymerization with epoxides to yield polycarbonates. This work describes the synthesis, end-functionalization, and curing of poly(propylene carbonate) (PPC) and poly(cyclohexene carbonate) (PCHC) into beta-hydroxy ester vitrimers. These vitrimers demonstrate the ability to be mechanically reprocessed up to 3 times with retention of the material’s properties through dynamic transesterification exchange reactions. The polycarbonate vitrimers with gel fractions exceeding 90 % exhibit high tensile strength (> 50 MPa) and Young’s modulus (> 2 GPa), achieved by varying repeat unit structure in the polymer backbone from the low Tg PPC to the more rigid high Tg PCHC structures. Owing to an entropically favorable chain back-biting mechanism, the network chains can be cleaved and depolymerized into cyclic small molecules. In the case of PCHC, this process enables repolymerization back to polycarbonates with 69 wt.% CO2 retention through life-cycles. The promising mechanical performance and recyclability of these CO2-based polycarbonate vitrimers indicate their potential for sustainable, high-performance materials, paving the way for future innovations in circular polymer technologies and carbon capture utilization.

36 MATERIALS SCIENCE↗

Predicting a Key Catalyst-Performance Descriptor for Supported Metal Nanoparticles: Metal Chemical Potential

The chemical potential of metal atoms in supported nanoparticles provides a convenient descriptor of their performance as heterogeneous catalysts that captures the effects of particle size, support and alloying. Based on microcalorimetric measurements, the chemical potential is shown in this work to be predictable as a function of monometallic particle diameter and the adhesion energy of the particle to the support, and, for oxide supports, this adhesion energy correlates predictably with metal oxophilicity. These correlations provide predictions of metal chemical potential that can enable catalyst design. They also suggest an improvement in the Gibbs-Thomson relation for free-standing nanoparticles, whether metals or molecular solids.

metal/oxide interface↗

Mechanistic Insights into CO 2 Electroreduction on Ni 2 P: Understanding Its Selectivity toward Multicarbon Products

Recently, nickel phosphides (Ni x P y ) have been reported to enable selective electrochemical formation of multicarbon products (C 3 and C 4 ) via the CO 2 reduction reaction (CO 2 RR); nevertheless, their activities remain low. In order to understand the roots of their high selectivity and low activity and to direct the design of more active Ni x P y -based CO 2 RR catalysts, we investigate the CO 2 RR mechanism on Ni 2 P using density functional theory (DFT) calculations. Iin this work, we reveal that the reaction proceeds through the formate pathway, followed by formaldehyde (H 2 CO*) formation and self-condensation. Moreover, we demonstrate that surface hydride transfer steps, along with surface-mediated C–C coupling, are essential in order to avoid C 1 product formation and boost selectivity toward multicarbon products. In addition, we find that the thermal surface hydride transfer from the surface to the physisorbed CO 2 is one of the key rate-limiting steps, and since it is not electroactive, it cannot be accelerated by applying an overpotential. Finally, our results also show that the hydrogen affinity of the surface and the dynamic surface reconstruction via H adsorption facilitate selective CO 2 reduction and C–C coupling on Ni 2 P. These findings provide an impetus for exploring materials design space to identify the physical principles that govern the thermodynamics of rate-limiting thermal steps in electrocatalytic processes.

36 MATERIALS SCIENCE↗

In Situ Phosphatizing of Triphenylphosphine Encapsulated within Metal–Organic Frameworks to Design Atomic Co 1 –P 1 N 3 Interfacial Structure for Promoting Catalytic Performance

The engineering coordination environment offers great opportunity in performance tunability of isolated metal single-atom catalysts. For the most popular metal–N x (MN x ) structure, the replacement of N atoms by some other atoms with relatively weak electronegativity has been regarded as a promising strategy for optimizing the coordination environment of an active metal center and promoting its catalytic performance, which is still a challenge. Herein, we proposed a new synthetic strategy of an in situ phosphatizing of triphenylphosphine encapsulated within metal–organic frameworks for designing atomic Co 1 –P 1 N 3 interfacial structure, where a cobalt single atom is costabilized by one P atom and three N atoms (denoted as Co-SA/P-in situ). In the acidic media, the Co-SA/P-in situ catalyst with Co 1 –P 1 N 3 interfacial structure exhibits excellent activity and durability for the hydrogen evolution reaction (HER) with a low overpotential of 98 mV at 10 mA cm –2 and a small Tafel slope of 47 mV dec –1 , which are greatly superior to those of catalyst with Co 1 –N 4 interfacial structure. We discover that the bond-length-extended high-valence Co 1 –P 1 N 3 atomic interface structure plays a crucial role in boosting the HER performance, which is supported by in situ X-ray absorption fine structure (XAFS) measurements and density functional theory (DFT) calculation. With this work, we hope to promote the development of high performance metal single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Engineering of Emissive Molecular Qubits Based on Spin-Correlated Radical Pairs

Spin chemistry of photogenerated spin-correlated radical pairs (SCRPs) offers a practical approach to control chemical reactions and molecular emissions by using weak magnetic fields. This capability to harness magnetic field effects (MFEs) paves the way for developing SCRPs-based molecular qubits. Here, in this work, we introduce a new series of donor–chiral bridge–acceptor (D–χ–A) molecules that demonstrate significant MFEs on fluorescence intensity and lifetime in solution at room temperature—critical for quantum sensing. By precisely tuning the donor site through torsional locking, distance extension, and planarization, we achieved remarkable control over key quantum properties, including field-response range and line width. In the most responsive systems, emission lifetimes increased by over 200%, and the total emission intensity was modulated by up to 30%. This level of tunability shows the power of synthetic spin chemistry. The rational design principle of optically addressable SCRP-based molecular systems, presented in this work, represents a major leap toward functional synthetic molecular qubits, advancing the field of molecular quantum technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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↗

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↗