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51 records · Page 3

Covalent Organic Frameworks with Irreversible Linkages via Reductive Cyclization of Imines

Covalent organic frameworks (COFs) show great potential for many advanced applications on account of their structural uniqueness. To address the synthetic challenges, facile chemical routes to engineer the porosity, crystallinity, and functionality of COFs are highly sought after. Herein, we report a synthetic approach that employs the Cadogan reaction to introduce nitrogen-containing heterocycles as the linkages in the framework. Irreversible indazole and benzimidazolylidene (BIY) linkages are introduced into COFs for the first time via phosphine-induced reductive cyclization of the common imine linkages following either stepwise or one-pot reaction protocols. Further, the successful linkage transformation introduces new functionalities, as demonstrated in the case of BIY-COF, which displays excellent intrinsic proton conductivity without the need of impregnation with external proton transfer reagents. Such a general strategy will open the window to a broader class of functional porous crystalline materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography

Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation Neutron Source. NeuDiff Agent takes instrument data through reduction, integration, refinement and validation to a validated crystal structure and a publication-ready CIF. NeuDiff Agent coordinates established crystallographic tools under explicit governance by restricting actions to allowlisted tools, enforcing fail-closed verification gates at key workflow boundaries, and capturing complete provenance for inspection, auditing and controlled replay. The present benchmark is limited to structural crystallography for periodic structures; magnetic structure analysis and incommensurate or superspace refinement are outside the scope of the current workflow. Performance is assessed using a fixed prompt protocol and repeated end-to-end runs with two large language model backends, with user and machine time partitioned and intervention burden and recovery behaviors quantified under gating. In a reference-case benchmark, NeuDiff Agent reduces wall time from 435 min (manual) to 86.5 ± 4.7 to 94.4 ± 3.5 min (4.6–5.0× faster) while producing a validated CIF with no checkCIF level A or B alerts. These results establish a practical route to deploy agentic AI in facility crystallography while preserving traceability and publication-facing validation requirements.

Xiao, Zhongcan [ORNL] (ORCID:0000000220761961)↗

Reliable p K a Prediction through Efficient Incorporation of Anharmonicity within the Nuclear–Electronic Orbital Framework

Accurate pK a prediction is critical for understanding chemical reactivity and molecular properties across a wide range of applications. Computational approaches usually invoke a harmonic treatment of the vibrational modes for zero-point energies, as well as thermal and entropic contributions. Herein, we present a general protocol for relative pK a prediction that incorporates the significant anharmonic effects using nuclear–electronic orbital (NEO) theory. This protocol is validated against experimental data for a range of molecules in acetonitrile, including protonated nitrogen bases, nitrophenols, anilines, and diamines, as well as cobalt electrocatalysts. For simple acids, the NEO approach offers only a slight improvement over conventional density functional theory with the standard harmonic vibrational treatment, whereas for hydrogen-bonded acids, the NEO approach offers more significantly improved performance at a comparable computational cost. This accessible methodology provides a practical route for accurate pKa prediction in challenging systems and is extendable to related thermodynamic properties such as hydricities and proton-coupled redox potentials.

Density functional theory↗

Exact Fock-State Preparation with $n^{1/4}$ Circuit Depth

Efficient, deterministic, and high-fidelity preparation of large Fock states is essential for scaling bosonic quantum technologies and exploring quantum phenomena at large excitation energies. We introduce a deterministic one-parameter (D1p) protocol that maps Fock-state preparation in an infinite-dimensional Hilbert space onto two-dimensional amplitude amplification. Starting from a coherent state with $|α|\simeq\sqrt{n}$, the initial target-state population scales as $n^{-1/2}$, yielding an iteration count and circuit depth of $\mathcal{O}(n^{1/4})$. Phase matching guarantees unit fidelity in the ideal model; remarkably, preparing $|{10^6}\rangle$ requires only 39 iterations. The protocol uses only displacements and number-selective phase operations, requires no numerical optimization, and further extends to state transfer, general superpositions, finite-dimensional systems, and multipartite entangled states. In the large-amplitude regime, its multi-target form prepares $L$-legged cat states with an iteration count determined only by $L$; cats with up to ten legs require only two iterations, independent of the coherent-state amplitude. This framework provides a broadly applicable route to highly excited bosonic states on platforms supporting these elementary controls.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗

Post synthetic amine functionalization of MOF-808 for CO 2 sorption via ligand exchange and Michael addition

Post synthetic modification of metal organic frameworks presents a viable route for amine functionalization which can significantly enhance CO 2 sorption capacity. We present a facile means of amine incorporation using limited synthetic steps and low-cost reagents that results in a high density of primary alkyl amines distributed through a zirconium-based metal organic framework (MOF). Both the MOF synthesis and the post synthetic modification take place under aqueous conditions and result in strongly bound molecular amines available for sorbate interaction throughout the MOF pores. Furthermore, this amine incorporation protocol results in a significantly increased CO 2 capacity compared with the unmodified MOF-808. Specifically, CO 2 isotherms collected at 298 K for the unmodified MOF-808 show uptakes of 0.06, 0.2, and 1.2 mmol/g at 4, 15, and 100 kPa, respectively, which can be compared with 0.3, 0.7, and 2.5 mmol/g for the glycine grafted MOF-808 and 0.5, 0.9, and 2.3 mmol/g for ethylenediamine grafted MOF-808.

Amine sorbent↗

Photochemical spin-state control of binding configuration for tailoring organic color center emission in carbon nanotubes

Abstract Incorporating fluorescent quantum defects in the sidewalls of semiconducting single-wall carbon nanotubes (SWCNTs) through chemical reaction is an emerging route to predictably modify nanotube electronic structures and develop advanced photonic functionality. Applications such as room-temperature single-photon emission and high-contrast bio-imaging have been advanced through aryl-functionalized SWCNTs, in which the binding configurations of the aryl group define the energies of the emitting states. However, the chemistry of binding with atomic precision at the single-bond level and tunable control over the binding configurations are yet to be achieved. Here, we explore recently reported photosynthetic protocol and find that it can control chemical binding configurations of quantum defects, which are often referred to as organic color centers, through the spin multiplicity of photoexcited intermediates. Specifically, photoexcited aromatics react with SWCNT sidewalls to undergo a singlet-state pathway in the presence of dissolved oxygen, leading to ortho binding configurations of the aryl group on the nanotube. In contrast, the oxygen-free photoreaction activates previously inaccessible para configurations through a triplet-state mechanism. These experimental results are corroborated by first principles simulations. Such spin-selective photochemistry diversifies SWCNT emission tunability by controlling the morphology of the emitting sites.

36 MATERIALS SCIENCE↗

Native Chemical Ligation of Peptoid Oligomers

Bioorganic chemists are inspired by natural biopolymers to design peptidomimetic oligomers that can exhibit sequence-structure-function relationships. Biomimetic polymers can be synthesized to incorporate a specific sequence of nonbiological monomer units using a variety of iterative solution-phase or solid-phase reaction schemes. These protocols generally provide access to a vast diversity of oligomeric compounds but are limited with respect to their ability to attain protein-like chain lengths. This constraint can preclude access to sequence-defined synthetic macromolecules with sufficient sizes required to exhibit tertiary structure and other protein-mimetic attributes. In contrast, peptide chemists have overcome this limitation by developing convergent synthetic methods, such as native chemical ligation, to join individual, smaller peptide chains together to make larger peptides or full proteins. A similar convergent approach is needed to establish efficient synthetic routes to non-natural sequence-defined macromolecules. Herein, we adapt the peptide native chemical ligation method to peptoid oligomers, demonstrating how short chains can be conjoined to create sequence-defined peptoid macromolecules. Nanosheet-forming peptoid polymers with distinct surface loop display domains were generated by sequential ligation of several discrete fragments. This method provides a reliable convergent ligation route for sequence-defined polypeptoids that results in a native amide bond joining the fragments. We envision that this strategy will be useful in synthesizing peptoid-based proteomimetics that incorporate diverse chemical features.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerating actinium-225 purification by high-pressure ion chromatography

Actinium-225 (t1/2 = 9.92 days) is an important radioisotope for targeted alpha therapy applications. The limited supply obtained through the decay of thorium-229 has motivated accelerator-based production routes, including irradiation of thorium targets. Irradiated targets can produce useful quantities of actinium-225, but the product requires final purification from chemically similar lanthanide contaminants. This work describes an automated high-pressure ion chromatography method for this final polishing step. The method uses a reusable strong-acid cation-exchange column bearing sulfonic acid functional groups. α-Hydroxyisobutyric acid (α-HIBA), adjusted to pH 4.3 with lithium hydroxide, complexes and elutes lanthanides, a dilute hydrochloric acid matrix-exchange step removes residual α-HIBA, and concentrated hydrochloric acid then elutes retained actinium(III). The protocol purified actinium-225 to >99% radiopurity across tracer-level samples and samples containing >150 µCi (5.6 MBq) of activity. A 10 min, 0.1 M hydrochloric acid matrix exchange substantially reduced organic eluent carryover, and in-line sodium iodide detection enabled real-time monitoring of actinium and lanthanide elution. The developed method can be completed in <1 h and provides a basis for automated purification workflows for accelerator-produced actinium-225.

Gaddis, Kevin [ORNL] (ORCID:0000000183398314)↗

Seed-Mediated Colloidal Synthesis of Multimetallic and High-Entropy Alloy Nanocrystal Libraries with Enhanced Catalytic Performance

Engineering colloidally stable multimetallic nanocrystals offers many benefits in a wide range of applications and allows manipulation of physical, chemical, and electronic properties of materials at the nanoscale. Synthesis routes are challenged by the chemical complexity required to temporally and spatially coordinate the reduction and alloying of multiple metal species, which has hampered the development of tunable libraries of colloidal materials to date. Here, in this work, we demonstrate a seed-mediated synthesis method to incorporate five or more metal elements into uniform, colloidally stable nanocrystals. By integrating machine learning-accelerated simulations, the synthesis of shortlisted high-entropy alloy nanocrystals was demonstrated. Multiple seed materials can be used, leading to a library of multimetallic nanocrystals with tunable electronic, physical, and alloy structures. The advantage of this synthetic protocol is highlighted in the preparation of catalytic materials that showed 2 orders of magnitude higher reaction rates than monometallic catalysts and outstanding thermal stability, thus highlighting the promise of this approach for high-performance materials in many areas.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Trigonometric continuous-variable gates and hybrid quantum simulations of the sine-Gordon model

Hybrid qubit-qumode quantum computing platforms provide a natural setting for simulating interacting bosonic quantum field theories. However, existing continuous-variable gate constructions rely predominantly on polynomial functions of canonical quadratures. In this work, we introduce a complementary universality paradigm based on trigonometric continuous-variable gates, which enable a Fourier-like representation of bosonic operators and are particularly well suited for periodic and non-perturbative interactions. We present an ancilla-based framework for implementing trigonometric gates with arguments given by arbitrary Hermitian functions of qumode quadratures. The protocol yields unitary gates deterministically, and non-unitary gates through probabilistic post-selection. As a concrete application, we develop a hybrid qubit-qumode quantum simulation of the lattice sine-Gordon model. Using these gates, we prepare ground states via quantum imaginary-time evolution, simulate real-time dynamics, compute time-dependent vertex two-point correlation functions, and extract quantum kink profiles under topological boundary conditions. Our results demonstrate that trigonometric continuous-variable gates provide a physically natural framework for simulating interacting field theories on near-term hybrid quantum hardware, while establishing a parallel route to universality beyond polynomial gate constructions. We expect that the trigonometric gates introduced here to find broader applications, including quantum simulations of condensed matter systems, quantum chemistry, and biological models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Constant-Overhead Fault-Tolerant Bell-Pair Distillation Using High-Rate Codes

We present a fault-tolerant Bell-pair distillation scheme achieving constant overhead through high-rate quantum low-density parity-check (qLDPC) codes. Our approach maintains a constant distillation rate equal to the code rate while requiring no additional overhead beyond the physical qubits of the code. Full circuit-level analysis demonstrates fault-tolerance for input Bell-pair infidelities below a threshold ∼10%, readily achievable with near-term capabilities. Unlike previous proposals, our scheme keeps the output Bell pairs encoded in qLDPC codes at each node, eliminating unencoding overhead and enabling direct use in distributed quantum applications through recent advances in qLDPC computation. These results establish qLDPC-based distillation as a practical route toward resource-efficient quantum networks and distributed quantum computing.

quantum communication, protocols & technology↗

Determining the Solubility Behavior of Kogarkoite in Simulated Nuclear Waste

Kogarkoite (Na 3 FSO 4 ) is a sparingly soluble fluoride–sulfate double salt that has been identified in high level nuclear waste sludge at the Hanford Site and, more recently, in sludge batch compilation samples at the Savannah River Site (SRS). Due to its complex dissolution behavior, which exhibits an inverse dependence on sodium ion activity, the presence of this mineral poses significant challenges to waste retrieval and processing. Incomplete dissolution during sludge washing can lead to the retention of fluoride and sulfate in the high-level waste feed, potentially causing the formation of corrosive, immiscible molten salt layers, known as "glass gall,” in vitrification melters. Current efforts to optimize flowsheet parameters and wash-water volumes are hindered by the absence of a commercially available, certified reference material, which prevents the accurate calibration of analytical methods and the verification of dissolution kinetics. To address this critical gap, this research focuses on the laboratory synthesis of pure Kogarkoite to serve as a standard for comprehensive solubility and washing performance testing. A coupled synthesis and simulant campaign was executed using an evaporative crystallization protocol designed to replicate the dynamic concentration effects observed in tank farm operations. Thirteen simulant matrices were prepared by dissolving systematically varied ratios of sodium fluoride (NaF) and sodium sulfate (Na 2 SO 4 ) in deionized water under three distinct caustic regimes: 0.0 g (control), 4.0 g (~1 M), and 12.0 g (~3 M) sodium hydroxide (NaOH). While thermodynamic equilibrium models suggest that high-caustic environments should favor the stability of the double salt7, results from this evaporative study at 25 0 C revealed a distinct kinetic divergence. Simulants with high hydroxide loading predominantly yielded large, blocky crystals of sodium sulfate decahydrate (Na 2 SO 4 .10H 2 O). Successful synthesis of pure Kogarkoite was achieved exclusively in specific NaOH-free compositional windows, where the precipitate manifested as fine, opaque granular aggregates. Ion chromatography (IC) analysis confirmed phase purity through the simultaneous stoichiometric depletion of both fluoride and sulfate from the supernatant. This successful synthesis establishes a reproducible route to generate bulk Kogarkoite, enabling the subsequent phase of quantitative dissolution testing using inhibited water to optimize sludge-batch assembly.

Sarker, Md Sharif [Florida International Univ. (FI↗

Probing elemental speciation in hydrochar produced from hydrothermal liquefaction of anaerobic digestates using quantitative X-ray diffraction

Valorization of hydrochar, a solid byproduct from hydrothermal liquefaction (HTL) of anaerobically-digested agriculture wastes (digestates), requires fundamental knowledge of elemental speciation. This study investigated the effects of reaction temperatures (320–360 °C), digestate pH (3.5–8), and digestate cellulose-to-lignin ratios (0.2–1.8) on the speciation (chemical form) and composition of organics and inorganics in hydrochars produced during hydrothermal treatment. Quantitative X-ray diffraction (XRD) method was the primary technique used to characterize hydrochars. The comprehensive XRD pattern processing including the Rietveld refinement protocols demonstrated that the organic phase was comprised of mostly crystalline monocyclic, heterocyclic, and polycyclic aromatics with diverse aliphatic and aromatic substituents, while the inorganic mineral phase consisted of calcium-phosphates, magnesium-phosphates, calcium-carbonates, and magnesium-carbonates. Further, XRD results were validated by the elemental yields of products and the distribution of chemical functionalities measured using solid-state nuclear magnetic resonance (NMR) spectroscopy. The characterization data were used to evaluate proposed mechanistic pathways using compositional analysis of biocrude and aqueous-phase coproducts. Mechanistic pathways developed in the study suggested that benzoic acids, phenols, benzaldehydes, phenolic aldehydes, α-dicarbonyls, and α-hydroxycarbonyls were responsible for the precipitation of organics through various reactions depending on operating conditions. Meanwhile, the formation of inorganic compounds appeared to be consistently represented by reactions including dehydration, hydrolysis, endergonic reduction, and structure rearrangement of native minerals in the digestates. This study provides basic knowledge needed to create and assess potential elemental speciation pathways. In addition, the results of the study facilitate the specification of process conditions to optimize targeted utilization routes of hydrochar for more economically-feasible and sustainable HTL processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Type-II superconductivity at 9K in Pb–Bi alloy

In the present work, we report the synthesis of Pb–Bi alloy with enhanced Tc of up to 9K, which is higher than that of Pb. The alloy is synthesized via a solid-state reaction route in the vacuum-encapsulated quartz tube at 700°C in an automated furnace. The synthesized sample is characterized by X-ray Diffraction(XRD) and Energy dispersive X-ray analysis(EDAX) for its phase purity and elemental composition. Rietveld refinement of XRD reveals that the end product is a majority hexagonal Pb 7 Bi 3 , with minor rhombohedral Bi. The electronic transport measurement shows metallic behavior with the Debye temperature of 108K and a superconductivity transition temperature (T c ) below 9K, which is the maximum to date for any reported Pb–Bi alloy, Pb or Bi at ambient pressure. Partial substitution of Bi at the Pb site may modify the free density of electronic states within the BCS model to attain the optimum T c , which is higher by around 2K from the reported T c of Pb. The superconductor phase diagram derived from magneto-transport measurements reveals that the synthesized alloy is a conventional superconductor with an upper critical field (H c2 ) of 3.9 T, which lies well within the Pauli paramagnetic limit. The magnetization measurements carried out following ZFC(Zero Field Cool) protocols infer that the synthesized alloy is a bulk superconductor below 9K. The isothermal M-H(Magnetization vs. Field) measurements performed below T c establish it as a type-II superconductor. Furthermore, the specific heat capacity measurements show that the Pb–Bi alloy is a strongly coupled bulk superconductor below around 9K with possibly two superconducting gaps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Centralized AI Lakehouse Framework for Brain Tumor MRI Classification and Segmentation, University KPI Forecasting, and Water Potability Prediction

In many university and healthcare projects, models are built for very different data types such as tables, institutional time series, and medical images, but they are deployed as separate applications. In this work, that separation made testing and maintenance difficult because each module had its own pipeline and runtime requirements. This paper presents an integrated AI lakehouse-style implementation that runs three model pipelines inside one containerized backend. For medical imaging, we used MRI datasets from IEEE DataPort: a four-class classification set with 7012 images (5708 train/1304 test) and a segmentation set with 3063 image–mask pairs. The classification model (ResNet50 transfer learning) is evaluated using a proper train–validation–test protocol across multiple splits (80/10/10, 70/10/20, 60/10/30, and 10/30/60), achieving a test accuracy of 99.00% under the standard 80/10/10 split. Additionally, a patient-level evaluation is conducted using an external glioma dataset to provide a more realistic assessment without data leakage. The segmentation model (DeepLabV3-ResNet50) achieved 83.09% validation mIoU and 88.79% Dice score. For university KPI forecasting, we used annual IPEDS and NSF HERD data from 2010 to 2023 for three universities (BSU, EOU, and UAB). To examine the effect of preprocessing on forecasting performance, two case studies are conducted. In the first case, linear interpolation is applied to generate semester-level data. In the second case, the original annual data is used directly without interpolation. Random Forest regression and ARIMA models are evaluated using MAE, RMSE, MAPE, and R 2 . The results showed that interpolation improved apparent forecasting performance due to smoothing, while evaluation on the original annual data provided a more realistic assessment of model behavior. To further validate the framework on a larger dataset, an additional case study is conducted using a student dropout dataset. For water potability, we trained and compared multiple tabular classifiers on a large dataset (1,048,575 samples). A Random Forest model (100 trees, max depth 10) achieved 85.86% test accuracy and high recall for unsafe samples (0.8447). All modules are served via FastAPI and deployed together using Docker, with workflow automation routing requests to the correct endpoint. System-level benchmarking indicates that the backend maintains stable throughput and latency under concurrent requests.

97 MATHEMATICS AND COMPUTING↗