Dan C. Sorescu’s research while affiliated with University of Pittsburgh and other places

Distinct from the proton defect, the hydride defect species may be present in certain perovskite materials in reducing environments such as in fuel electrodes of solid oxide cells (SOCs) or on the reducing side of ceramic membranes. A generalized defect thermodynamic model was developed for the triple-conducting perovskites (La,Ba)Fe1−xMxO3−δ (M = Y and Zr) to allow inclusion of the hydride defect formation reaction in addition to the other three main defect reactions, namely, the oxygen vacancy formation, hydration, and charge disproportionation reactions. This comprehensive defect model also allows the incorporation of polynomial functional forms of oxygen nonstoichiometry δ to describe the defect reaction energies and entropies and to enable refinements of the defect reaction equilibrium constants in the defect thermodynamic analysis. As a first step, the developed model is applied to the Ba0.95La0.05FeO3−δ material as an illustrative system to obtain its Brouwer diagrams with both the proton and hydride defects in relevant SOC conditions, particularly for more reducing environments. The results provide direct guidance on the influence of electronic and ionic defect concentrations upon thermodynamic properties and ultimately on the performance of Ba0.95La0.05FeO3−δ and potentially other (La,Ba)Fe1−xMxO3−δ perovskite materials involved in SOC applications.

Polymeric graphitic carbon nitride (gCN) materials have received great attention in the fields of photo and electrocatalysis due to their distinct properties in metal-free systems with high physicochemical stability. Nevertheless, the activity of undoped gCN is limited due to its relatively low specific surface area, low conductivity, and poor dispersibility. Doping Gd atoms in a gCN matrix is an efficient strategy to fine-tune its catalytic activity and its electronic structure. Herein, the influence of various wt% of gadolinium (Gd) doped in melon-type carbon nitride was systematically investigated. Gadolinium-doped graphitic carbon nitride (GdgCN) was synthesized by adding gadolinium nitrate to dicyandiamide during polymerization. The X-ray diffraction (XRD) and transmission electron microscopy (TEM) results revealed that the crystallinity and the morphological properties are influenced by the % of Gd doping. Furthermore, X-ray photoelectron spectroscopy (XPS) studies revealed that the gadolinium ions bonded with nitrogen atoms. Complementary density functional theory (DFT) calculations illustrate possible bonding configurations of Gd ions both in bulk material and on ultrathin melon layers and provide evidence for the corresponding bandgap modifications induced by gadolinium doping.

We combined ultrahigh vacuum (UHV) surface science techniques, electrochemical measurements, and computational modeling to investigate electrocatalytic systems that are crucial components of the carbon management effort, including oxygen evolution reactions (OER) and CO2 reduction reactions (CO2RR). Well-defined Model catalysts were grown on substrates in the UHV chamber and characterized with X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM). Selected model electrocatalysts were then tested in electrochemical cells to establish the structure-property relationships in OER and CO2RR. Our results showed that the edge sites of Fe2O3 grown on Au(111) were the most active toward OER and incorporation of Ni at the edge sites (NiFeOx) further boosted their OER activity. We also resolved the size-dependent electrocatalytic CO2-to-CO conversion of the Ag nanoparticle electrocatalysts with average particle diameter between 2 to 6 nm: smaller diameter (< 3 nm) particles favored H2 evolution reaction (HER) due to a high population of Ag edge sites, whereas larger diameter particles favored CO2RR as the population of Ag(100) surface sites grew. We further discovered that electronic interactions between small diameter Ag particles and highly defective carbon supports could break the size-dependent CO2RR selectivity, resulting in highly selective (CO Faradaic Efficiency > 90%) and active Ag nanoparticle electrocatalysts with sizes < 2 nm diameter.

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid‐related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug‐testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)‐decorated single‐walled carbon nanotube (SWCNT)‐based field‐effect transistors (FETs) are utilized for machine learning‐assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave‐one‐out cross‐validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au‐SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au‐SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL⁻¹.

We investigated nanoparticle electrocatalysts in oxygen evolution reaction (OER) and CO 2 reduction reaction (CO 2 RR) via an approach coupling electrochemistry with ultra-high vacuum (UHV) surface science and computational modeling. Well-defined nanoparticle electrocatalysts such as Fe 2 O 3 , NiFeO x , and Ag, were prepared in the UHV chamber via physical vapor deposition (PVD) and characterized with surface science techniques including X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM), followed by electrochemistry measurements to establish the structure-property relationships in OER and CO 2 RR. Calculations based on density functional theory (DFT) and microkinetic modeling (MKM) were then implemented to gain fundamental insight into these systems. We observed the edge-enhanced OER activity of Au-supported, ultra-thin Fe 2 O 3 electrocatalysts and revealed incorporation of Ni at the edge sites (NiFeO x ) further boosting their OER activity. We also resolved the size-dependent transition between CO 2 RR and H 2 evolution reaction (HER) selectivity in sub-5 nm Ag electrocatalysts and identified an effective minimum size limit of ∼4 nm for active and selective Ag catalysts: particle diameters below this range experienced increased H 2 evolutions due to a high population of Ag edge sites; and larger diameter particles favored CO 2 RR as the population of Ag(100) surface sites grew but will begin to lose catalyst utilization based on total metal masses.

Density functional theory (DFT) based modeling was performed to investigate the defect energetics of the proton conducting oxides BaFe 1-x M x O 3-δ (with M=Zr, Y, and Zn at the B-site). High-throughput defect modeling was carried out to obtain the defect energetics ensembles as a function of B-site x (0 – 0.25) and oxygen δ (0 – 0.5) compositions for assessment of oxygen vacancy formation (E vac ) and hydration reaction (E hyd ) energies in complex defect-dopant configurations. The modeling effort aims to elucidate the complex coupling among oxygen vacancies, the protons and metal dopants in various concentrations and their combined effect upon defect energetics in BaFe 1-x M x O 3-δ perovskite. This information complements the current experimental measurements with essential data related to the energetics of various defect configurations that can play a role in solid-oxide-cell (SOC) applications. Preliminary results among more than 3,000 configurations investigated are summarized in Figure 1. All calculations were performed with the Perdew-Burke-Ernzerhof (PBE) functional in charge neutral 2 × 2 × 2 perovskite supercells. An effective Hubbard U eff correction of 4 eV was applied to the Fe 3d shell, with all the Fe atoms being in a high-spin state and having a ferromagnetic ordering. Stability analysis of each of the BaFe 1-x M x O 3-δ systems investigated at specified x and δ composition values reveals that the oxygen vacancy (V O ) is energetically unfavorable when placed adjacent to the M dopant. Overall, the Fe-V O -Fe configurations are identified to be more stable than the Fe-V O -M and M-V O -M configurations, while one with a M-V O -M cluster arrangement is the least stable. Such a short-range ordering leads to the blocking of the oxygen vacancy migration toward the oxygen sites around the M dopant, whereas the proton hopping between the oxygens around the M dopants is energetically not hindered. Based on the stability of various defect-dopant configurations of the BaFe 0.75 M 0.25 O 2.875 systems with or without hydration, it is revealed that the stability range of analogous configurations with varying dopant types can be an indicator of the defect-dopant ordering strength and can be correlated with the ionic radii of the dopants in the BaFe 1-x M x O 3-δ systems. Taking the energy of the most stable BaFe 1-x M x O 3-δ structures at various x and δ values analyzed as representative for the respective compositions, the corresponding derivations of the E vac and E hyd energies as a function of δ (and x) are summarized in Figures 1(a) and 1(b), respectively. Overall, the results indicate a stronger oxygen non-stoichiometry (δ) dependence in the E vac values of the BaFeO 3-δ and BaFe 1-x M x O 3-δ systems (M=Zr, Y, and Zn at x=0.125 and x=0.25), whereas the E hyd data exhibit a much weaker δ dependence. This contrasting behavior in the δ dependences between E vac and E hyd values may be attributed to the charge transfer characteristics of the oxygen vacancy formation reaction, which is associated with the Fe 3d and the O 2p energy levels of the materials at various δ values while the charge transfer involved in the hydration reaction is relatively minimal. The effect of dopant concentration (x) further shows an opposite trend in the E vac values vs. x with the dopant types, with an increase of E vac upon increasing the Zr doping concentration and a decrease of E vac upon increasing the Y and Zn doping content. Due to the strong oxygen non-stoichiometry dependence in the E vac values, the results indicate an increased proton affinity of the BaFe 1-x M x O 3-δ oxides. Further assessments of the E vac and E hyd data on δ values and their impact upon the defect equilibria of the BaFe 1-x M x O 3-δ systems under the SOC operating conditions will be discussed. Disclaimer This project was funded by the U.S. Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. Figure 1

Both the experimental and first-principles modeling results revealed the dependence of defect energetics on oxygen non-stoichiometry and magnetic coupling of Fe in the Fe-based perovskite oxides. A generalized defect thermodynamic model of the proton-conducting (La,Ba)Fe 1-x M x O 3-δ perovskite oxide is developed to allow inclusion of nonlinear δ dependent terms in three key defect reaction energies, namely, the oxygen vacancy formation, hydration, and charge disproportionation reactions. A transition from a large polaron description at lower δ values to a small polaron expression at higher δ is also considered in our analysis. Based on the functional forms of defect energetics on δ as guided by first principles modeling and literature data, the Brouwer diagrams of BaFe 0.9 Y 0.1 O 3-δ are assessed to provide information on electronic and ionic defect concentration (including the proton species) as a function of O 2 and H 2 O pressure at different temperatures for solid-oxide cell applications.