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At least 955 records · Page 53

Pentaquarks made of light quarks and their admixture to baryons

This paper is a continuation of our studies of multiquark hadrons. The antisymmetrization of their wave functions required by Fermi statistics is nontrivial, as it mixes orbital, color, spin, and flavor structures. In our previous papers we developed a method to find them based on the representations of the permutation group, and derived the explicit wave functions for baryons excited to the first and second shells (L = 1, 2), tetraquarks $qq$$\overline{q}$$\overline{q}$ and hexaquarks (6q). Now we apply it to light pentaquarks ($qqq$$\overline{q}$), in the S- and P-shells (L = 0, 1). Using Jacobi coordinates, one can use the hyperdistance approximation in 12-dimensional space. We further address the issue of “unquenching” of baryons, by considering their mixing with pentaquarks, via two channels, through the addition of σ-like or π-like $\overline{q}$$q$ pairs. This mixing is central for understanding of the observed flavor asymmetry of the antiquark sea, the amount of orbital motion issue as well as other nucleon properties.

Baryons↗

Classical symmetries and the Quantum Approximate Optimization Algorithm

Here, we study the relationship between the Quantum Approximate Optimization Algorithm (QAOA) and the underlying symmetries of the objective function to be optimized. Our approach formalizes the connection between quantum symmetry properties of the QAOA dynamics and the group of classical symmetries of the objective function. The connection is general and includes but is not limited to problems defined on graphs. We show a series of results exploring the connection and highlight examples of hard problem classes where a nontrivial symmetry subgroup can be obtained efficiently. In particular, we show how classical objective function symmetries lead to invariant measurement outcome probabilities across states connected by such symmetries, independent of the choice of algorithm parameters or number of layers. To illustrate the power of the developed connection, we apply machine learning techniques toward predicting QAOA performance based on symmetry considerations. We provide numerical evidence that a small set of graph symmetry properties suffices to predict the minimum QAOA depth required to achieve a target approximation ratio on the MaxCut problem, in a practically important setting where QAOA parameter schedules are constrained to be linear and hence easier to optimize.

97 MATHEMATICS AND COMPUTING↗

r 2 SCAN-D4: Dispersion corrected meta-generalized gradient approximation for general chemical applications

We combine a regularized variant of the strongly constrained and appropriately normed semilocal density functional with the latest generation semi-classical London dispersion correction. The resulting density functional approximation r 2 SCAN-D4 has the speed of generalized gradient approximations while approaching the accuracy of hybrid functionals for general chemical applications. We demonstrate its numerical robustness in real-life settings and benchmark molecular geometries, general main group and organo-metallic thermochemistry, and non-covalent interactions in supramolecular complexes and molecular crystals. Main group and transition metal bond lengths have errors of just 0.8%, which is competitive with hybrid functionals for main group molecules and outperforms them for transition metal complexes. The weighted mean absolute deviation (WTMAD2) on the large GMTKN55 database of chemical properties is exceptionally small at 7.5 kcal/mol. This also holds for metal organic reactions with an MAD of 3.3 kcal/mol. The versatile applicability to organic and metal–organic systems transfers to condensed systems, where lattice energies of molecular crystals are within the chemical accuracy (errors <1 kcal/mol).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved Predictive Tools for Structural Properties of Metal–Organic Frameworks

The accurate determination of structural parameters is necessary to understand the electronic and magnetic properties of metal–organic frameworks (MOFs) and is a first step toward accurate calculations of electronic structure and function for separations and catalysis. Theoretical structural determination of metal-organic frameworks is particularly challenging because they involve ionic, covalent, and noncovalent interactions, which must be treated in a balanced fashion. Here, we apply a diverse group of local exchange-correlation functionals (PBE, PBEsol, PBE-D2, PBE-D3, vdW-DF2, SOGGA, MN15-L, revM06-L, SCAN, and revTPSS) to a broad test set of MOFs to seek the most accurate functionals to study various structural aspects of porous solids, in particular to study lattice constants, unit cell volume, two types of pore size characteristics, bond lengths, bond angles, and torsional angles). The recently developed meta functionals revM06-L and SCAN, without adding any molecular mechanics terms, are able to predict more accurate structures than previously recommended functionals, both those without molecular mechanics terms (PBE, PBEsol, vdW-DF2, and revTPSS) and those with them (PBE-D2 and PBE-D3). To provide a broader test, these two functionals are also tested for lattice constants and band gaps of unary, binary, and ternary semiconductors.

36 MATERIALS SCIENCE↗

Introducing a New Spitzer Master BLISS Map to Remove the Instrument Systematic Phase-curve-parameter Degeneracy, as Demonstrated by a Reanalysis of the 4.5 μm WASP-43b Phase Curve

While Spitzer Infrared Array Camera (IRAC) systematics are generally well understood, each data set can provide its own challenges that continue to teach us about the underlying functional form of these systematics. Multiple groups have analyzed the phase curves of WASP-43b with varying detrending techniques, each obtaining different results. In this work, we take another look at WASP-43b while exploring the degenerate relation between Bilinearly Interpolated Subpixel Sensitivity (BLISS) mapping, point response function (PRF)–FWHM detrending, and phase curve parameters. We find that there is a strong correlation between the detrending parameters in the two models, and best-fit phase curve amplitudes vary strongly when the data are temporally binned. To remove this degeneracy, we present a new Gaussian centroided intrapixel sensitivity map (hereafter fixed sensitivity map), generated using 3,712,830 exposures spanning 5 yr, for a variety of aperture sizes at 4.5 μm. We find evidence for time variability in the sensitivity at 3.6 μm and do not generate a visit-independent map for this channel. With the fixed 4.5 μm intrapixel sensitivity map, the best fits for WASP-43b no longer vary strongly with bin size and PRF–FWHM detrending is no longer required to remove correlated noise. For data sets that do not fall completely within the sweet spot, temporal binning should not be used in the analysis of Spitzer phase curves. We confirm nightside emission for WASP-43b with a disk-integrated nightside temperature of 806 ± 48 K at 4.5 μm. The 4.5 μm maps are available at github.com/kevin218/POET.

79 ASTRONOMY AND ASTROPHYSICS↗

Design Rules for Open-Shell Molecular Wires: Insights from Correlated Many-Body Transport

Open-shell π-conjugated systems have emerged as promising molecular wires that can sustain unusually high low-bias conductance over tens of nanometers. However, predictive design rules remain limited because near-degeneracy and spin polarization give rise to correlated electronic states that are not reliably captured by standard density functional theory and Landauer transport descriptions. Here, we establish physically transparent design rules for long-range, weakly length-dependent charge transport based on the interplay between bond-length alternation and electron–electron interactions. Using a fully correlated transport framework that combines density matrix renormalization group calculations with nonequilibrium Green’s function embedding, we show that weak dimerization maintains spatially extended edge states, while moderate on-site interaction stabilizes open-shell character without excessively separating transport-relevant resonances. This balance yields zero-bias transmission that is largely insensitive to molecular length, providing a route to connect chemically tunable structure to correlated transport beyond mean-field descriptions.

Charge transport↗

NS5-brane backgrounds and coset CFT partition functions

Worldsheet string theory is solvable for a variety of backgrounds involving Neveu-Schwarz fivebranes, in terms of gauged nonlinear sigma models on group manifolds. We compute the worldsheet torus partition function of these models, and propose gauging of null isometries as a unifying principle and conceptual framework for this large family of string backgrounds. In the process, we explain how partition functions of asymmetrically gauged Wess-Zumino-Witten models can be computed from the path integral, and organize and systematize various results scattered throughout the literature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Metal–Organic Framework-Based Microfluidic Impedance Sensor Platform for Ultrasensitive Detection of Perfluorooctanesulfonate

The growing global concerns to public health from human exposure to perfluorooctanesulfonate (PFOS) requires rapid, sensitive, in-situ detection where current, state-of-the-art techniques are yet to adequately meet sensitivity and selectivity standards of the real-world. This work presents, for the first time, a synergistic approach for the targeted affinity-based capture of PFOS using a porous sorbent probe that enhances detection sensitivity by embedding it on a microfluidic conductive platform. This novel sorbent-containing platform functions as an electrochemical sensor to directly measure PFOS concentration through a proportional change in electrical response (increase in impedance). The extremely high surface area and pore volume of mesoporous metal-organic framework (MOF) Cr-MIL-101 is used as the probe for targeted PFOS capture based on the affinity of the chromium center towards both the fluorine tail groups as well as the sulfonate functionalities as demonstrated by spectroscopic (NMR and XPS) and microscopic (TEM) studies. Answering the need for an ultrasensitive PFOS detection technique, we are embedding these MOF capture probes inside a microfluidic channel, sandwiched between interdigitated microelectrodes (IDµE). The nanoporous geometry increases the signal to noise ratio of interdigitated microelectrodes tremendously increasing sensitivity; this in combination with the ability of the capture probes to interact with the PFOS at the molecular level and effectively transduce that response electrochemically has allowed us achieve a PFOS detection limit of 0.5 ng/L, which is unprecedented for in-situ analytical PFOS sensors and even comparable to quantification limits achieved using state-of-the-art ex situ techniques.

36 MATERIALS SCIENCE↗

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

Rahman, Md Habibur (ORCID:000000027705984X)↗

Polynorbornene-based polycations

A statistical, cationic-functionalized norbornene copolymer is formed by a process including performing a vinyl addition polymerization in the presence of a metal catalyst of a first norbornene monomer substituted with a first alkyl group and at least a second norbornene monomer substituted with a second alkyl group, to form an intermediate norbornene copolymer. The second alkyl group includes a substituent which undergoes a substitution reaction with a precursor of a cationic group. The process further includes adding the precursor for the cationic group to the intermediate norbornene copolymer to form the cationic functionalized norbornene copolymer. The cationic group has a volume of 0.25 cm 3 /mol or greater (for example, a phosphonium group or an imidazolium group).

Noonan, Kevin↗

Mechanistic Insights into the Demethylation of Lignin‐Derived Structures Using Protic Ionic Liquids: A Density Functional Theory Study

Lignin valorization is restricted by the stability of its methoxy groups, creating a critical need for efficient demethylation strategies. Here, in this study, density functional theory (DFT) is employed to dissect the mechanistic pathways of demethylation in lignin model compounds, guaiacol and syringol, using protic ionic liquids (PILs) that act as both solvent and catalyst. Conductor‐like Screening Model for Real Solvents (COSMO‐RS) analysis identifies monoethanolammonium acetate ([MEOA][Ace]) as the most promising medium, attributed to its strong hydrogen bonding network and solvation ability. By integrating implicit and explicit solvation models, it is revealed that an acid‐catalyzed hydrolytic mechanism governs demethylation, with PILs stabilizing crucial transition states and intermediates. Complementary electronic structure evaluations, including highest occupied molecular orbital–lowest unoccupied molecular orbital (HOMO‐LUMO) gap analysis, charge distribution, and electrostatic potential mapping, demonstrate how PILs lower energetic barriers and enhance reactivity. To simulate realistic environments, this study is extended to lignin dimer complexes with varying water content, uncovering how water‐bridged solvation reverses demethylation preference from guaiacyl to syringyl units. This mechanistic shift aligns with experimental observations showing faster S‐unit reactivity in hydrated systems. Together, these findings provide atomic‐level insight into lignin demethylation dynamics and highlight how tuning acid concentration in PILs can accelerate kinetics, enabling a rational pathway toward next‐generation biomass conversion technologies.

COSMO-RS↗

Facile Fabrication of Self‐Assembly Functionalized Polythiophene Hole Transporting Layer for High Performance Perovskite Solar Cells

Abstract Crystallinity and crystal orientation have a predominant impact on a materials’ semiconducting properties, thus it is essential to manipulate the microstructure arrangements for desired semiconducting device performance. Here, ultra‐uniform hole‐transporting material (HTM) by self‐assembling COOH‐functionalized P3HT (P3HT‐COOH) is fabricated, on which near single crystal quality perovskite thin film can be grown. In particular, the self‐assembly approach facilitates the P3HT‐COOH molecules to form an ordered and homogeneous monolayer on top of the indium tin oxide (ITO) electrode facilitate the perovskite crystalline film growth with high quality and preferred orientations. After detailed spectroscopy and device characterizations, it is found that the carboxylic acid anchoring groups can down‐shift the work function and passivate the ITO surface, retarding the interface carrier recombination. As a result, the device made with the self‐assembled HTM show high open‐circuit voltage over 1.10 V and extend the lifetime over 4,300 h when storing at 30% relative humidity. Moreover, the cell works efficiently under much reduced light power, making it useful as power source under dim‐light conditions. The demonstration suggests a new facile way of fabricating monolayer HTM for high efficiency perovskite devices, as well as the interconnecting layer needed for tandem cell.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The skin microbiome of elasmobranchs follows phylosymbiosis, but in teleost fishes, the microbiomes converge

Background: The vertebrate clade diverged into Chondrichthyes (sharks, rays, and chimeras) and Osteichthyes fishes (bony fishes) approximately 420 mya, with each group accumulating vast anatomical and physiological differences, including skin properties. The skin of Chondrichthyes fishes is covered in dermal denticles, whereas Osteichthyes fishes are covered in scales and are mucous rich. The divergence time among these two fish groups is hypothesized to result in predictable variation among symbionts. Here, using shotgun metagenomics, we test if patterns of diversity in the skin surface microbiome across the two fish clades match predictions made by phylosymbiosis theory. In this work, we hypothesize (1) the skin microbiome will be host and clade-specific, (2) evolutionary difference in elasmobranch and teleost will correspond with a concomitant increase in host-microbiome dissimilarity, and (3) the skin structure of the two groups will affect the taxonomic and functional composition of the microbiomes. Results: We show that the taxonomic and functional composition of the microbiomes is host-specific. Teleost fish had lower average microbiome within clade similarity compared to among clade comparison, but their composition is not different among clade in a null based model. Elasmobranch’s average similarity within clade was not different than across clade and not different in a null based model of comparison. In the comparison of host distance with microbiome distance, we found that the taxonomic composition of the microbiome was related to host distance for the elasmobranchs, but not the teleost fishes. In comparison, the gene function composition was not related to the host-organism distance for elasmobranchs but was negatively correlated with host distance for teleost fishes. Conclusion: Our results show the patterns of phylosymbiosis are not consistent across both fish clades, with the elasmobranchs showing phylosymbiosis, while the teleost fish are not. The discrepancy may be linked to alternative processes underpinning microbiome assemblage, including possible historical host-microbiome evolution of the elasmobranchs and convergent evolution in the teleost which filter specific microbial groups. Our comparison of the microbiomes among fishes represents an investigation into the microbial relationships of the oldest divergence of extant vertebrate hosts and reveals that microbial relationships are not consistent across evolutionary timescales.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of Pd alloying on structural, electronic and magnetic properties of L1 0 Fe–Ni

We present a systematic study of the effect of Pd-alloying on phase stability, electronic structure, and elastic properties in L1 0 Fe–Ni using density-functional theory. Being from the same group of the periodic table, Pd is the best candidate for chemical alloying. The Fe–Ni/Fe–Pd/Ni–Pd bond-length increases with increasing Pd-concentration, which weakens the hybridization between low lying energy states below Fermi-level. The reduced hybridization decreases the relative thermodynamic stability of L1 0 Fe(Ni 1–x Pd x ) until x = 0.75. Beyond this concentration, the relative stability gets enhanced, which is attributed to a unique change in the lattice distortion (c/a). The elastic properties show a non-monotonous behavior as a function of x, which is again due to a specific change-over in the uniaxial strain. We found that Pd alloying increases the local Fe moment and structural anisotropy of L1 0 FeNi, which are important for applications such as microwave absorption, refrigeration systems, recording devices, imaging and sensors. Here, we believe that the present study for the chemical alloying effect can provide critical insights toward the understanding of electronic-structure and elastic behavior of other technologically important materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Engineering acid-base active sites on an N-doped biochar catalyst for microwave-assisted biodiesel production from waste cooking oil

Acid-base bifunctional catalysts play a crucial role in converting high-free fatty acid (FFA) feedstocks into biodiesel by enabling the simultaneous esterification and transesterification of triglycerides in a single step, thereby minimizing saponification and streamlining the process. In this study, we report the design and development of a novel N-doped acid-base bifunctional biochar catalyst synthesized from renewable biomass precursors- glucose and chitosan. The catalyst’s acidic sites were introduced via surface functionalization with o-sulfobenzoic acid cyclic anhydride, grafting -SO₃H groups onto the carbon framework, while basic sites were generated from amine functionalities (-NH) derived from chitosan, yielding a robust and truly bifunctional surface. The catalyst was characterized and used for the microwave-assisted transesterification of waste cooking oil, and process optimization using response surface methodology (RSM-CCD) yielding a maximum biodiesel yield of 98.8 ± 0.4% under optimal conditions (methanol-to-oil molar ratio 20:1, catalyst loading 5.7 wt%, temperature 99 °C, and reaction time 46.6 min). The catalyst demonstrated good stability, maintaining a yield of 92.2 ± 0.4% after eight reuse cycles. A Life Cycle Assessment (LCA) conducted for 1 kg of biodiesel production revealed a global warming potential of 0.85 kg CO 2 eq and human toxicity potential of 1.59 kg 1,4-DB eq, with the largest environmental contributions arising from catalyst preparation and reuse. In conclusion, this work highlights a green and circular approach to biodiesel production, combining renewable catalyst design, waste feedstock utilization, and quantitative sustainability assessment to guide future developments in sustainable catalysis and biofuel engineering.

Bifunctional catalyst↗

Continuous MOF Membrane-Based Sensors via Functionalization of Interdigitated Electrodes

Three M-MOF-74 (M = Co, Mg, Ni) metal-organic framework (MOF) thin film membranes have been synthesized through a sensor functionalization method for the direct electrical detection of NO 2 . The two-step surface functionalization procedure on the glass/Pt interdigitated electrodes resulted in a terminal carboxylate group, with both steps confirmed through infrared spectroscopic analysis. This surface functionalization allowed the MOF materials to grow largely in a uniform manner over the surface of the electrode forming a thin film membrane over the Pt sensing electrodes. The growth of each membrane was confirmed through scanning electron microscopy (SEM) and X-ray diffraction analysis. The Ni and Mg MOFs grew as a continuous but non-defect free membrane with overlapping polycrystallites across the glass surface, whereas the Co-MOF-74 grew discontinuously. To demonstrate the use of these MOF membranes as an NO 2 gas sensor, Ni-MOF-74 was chosen as it was consistently fabricated as the best thin and homogenous membrane, as confirmed by SEM. The membrane was exposed to 5 ppm NO 2 and the impedance magnitude was observed to decrease 123× in 4 h, with a larger change in impedance and a faster response than the bulk material. Importantly, the use of these membranes as a sensor for NO 2 does not require them to be defect-free, but solely continuous and overlapping growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning Catalytic Sites on Zr 6 O 8 Metal–Organic Framework Nodes via Ligand and Defect Chemistry Probed with tert -Butyl Alcohol Dehydration to Isobutylene

Metal–organic frameworks (MOFs) have drawn wide attention as candidate catalysts, but some essential questions about their nature and performance have barely been addressed. (1) How do OH groups on MOF nodes act as catalytic sites? (2) What are the relationships among these groups, node defects, and MOF stability, and how do reaction conditions influence them? (3) What are the interplays between catalytic properties and transport limitations? To address these questions, we report an experimental and theoretical investigation of the catalytic dehydration of tert -butyl alcohol (TBA) used to probe the activities of OH groups of Zr 6 O 8 nodes in the MOFs UiO-66 and MOF-808, which have different densities of vacancy sites and different pore sizes. The results show that (1) terminal node OH groups are formed as formate and/or acetate ligands present initially on the nodes react with TBA to form esters, (2) these OH groups act as catalytic sites for TBA dehydration to isobutylene, and (3) TBA also reacts to break node–linker bonds to form esters and thereby unzip the MOFs. The small pores of UiO-66 limit the access of TBA and the reaction with the formate/acetate ligands bound within the pores, whereas the larger pores of MOF-808 facilitate transport and favor reaction in the MOF interior. However, after removal of the formate and acetate ligands by reaction with methanol to form esters, interior active sites in UiO-66 become accessible for the reaction of TBA, with the activity depending on the density of defect sites with terminal OH groups. The number of vacancies on the nodes is important in determining a tradeoff between the catalytic activity of a MOF and its resistance to unzipping. Computations at the level of density functional theory show how the terminal OH groups on node vacancies act as Brønsted bases, facilitating TBA dehydration via a carbocation intermediate in an E1 mechanism; the calculations further illuminate the comparable chemistry of the unzipping.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Powder X-ray diffraction of altrenogest, C 21 H 26 O 2

The crystal structure of altrenogest has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Altrenogest crystallizes in space group P2 1 2 1 2 1 (#19) with a = 7.286 916(16), b = 10.580 333(19), c = 22.266 08(7) Å, V = 1716.671(6) Å 3 , and Z = 4 at 295 K. Thermal expansion between 113 and 295 K is anisotropic. An O–H···O hydrogen bond links the molecules into chains along the c-axis. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗