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At least 433 records · Page 24

StructuredFuzzer: Fuzzing Structured Text-Based Control Logic Applications

Rigorous testing methods are essential for ensuring the security and reliability of industrial controller software. Fuzzing, a technique that automatically discovers software bugs, has also proven effective in finding software vulnerabilities. Unsurprisingly, fuzzing has been applied to a wide range of platforms, including programmable logic controllers (PLCs). However, current approaches, such as coverage-guided evolutionary fuzzing implemented in the popular fuzzer American Fuzzy Lop Plus Plus (AFL++), are often inadequate for finding logical errors and bugs in PLC control logic applications. They primarily target generic programming languages like C/C++, Java, and Python, and do not consider the unique characteristics and behaviors of PLCs, which are often programmed using specialized programming languages like Structured Text (ST). Furthermore, these fuzzers are ill suited to deal with complex input structures encapsulated in ST, as they are not specifically designed to generate appropriate input sequences. This renders the application of traditional fuzzing techniques less efficient on these platforms. To address this issue, this paper presents a fuzzing framework designed explicitly for PLC software to discover logic bugs in applications written in ST specified by the IEC 61131-3 standard. The proposed framework incorporates a custom-tailored PLC runtime and a fuzzer designed for the purpose. We demonstrate its effectiveness by fuzzing a collection of ST programs that were crafted for evaluation purposes. We compare the performance against a popular fuzzer, namely, AFL++. The proposed fuzzing framework demonstrated its capabilities in our experiments, successfully detecting logic bugs in the tested PLC control logic applications written in ST. On average, it was at least 83 times faster than AFL++, and in certain cases, for example, it was more than 23,000 times faster.

47 OTHER INSTRUMENTATION↗

Enabling Ethanol Dehydrogenation Catalysis by Postsynthetic Anion Exchange of Triazolate-Based Metal–Organic Frameworks

Materials containing soft, polarizable elements are expanding the boundaries of catalytic properties, offering unique electronic communication and stability characteristics compared with their harder counterparts due to the enhanced covalent nature of metal–ligand interactions. However, integrating soft components like sulfur into metal–organic frameworks (MOFs) for catalytic applications remains a largely underexplored challenge. Here, we report the synthesis of a family of triazole-based MOFs and expand upon established postsynthetic anion exchange methods to incorporate sterically encumbered polarizable elements, such as alkyl thiolates. Single-crystal X-ray diffraction, coupled with elemental analysis, confirms the successful anion exchange within M 2 X 2 BBTA (M = Co, Ni; X = μ-Cl, μ-OH, μ-SH, μ-SMe, μ-SEt; H 2 BBTA = 1H,5H-benzo(1,2-d:4,5-d′)bistriazole). We found that the anion identity significantly impacts the catalytic activity and selectivity of the MOFs, especially in nonoxidative ethanol dehydrogenation. Temperature-programmed experiments indicated that the metal single sites act as catalytically active sites below 250 °C. This work not only expands the synthetic toolbox for incorporating polarizable components into MOFs but also provides critical insights into their catalytic potential.

Anions↗

Energy Storage Impacts in Resilience Hubs and Other Critical Infrastructure: An Assessment Guide for Developers and Practitioners

Battery energy storage systems (BESS) deployed behind the meter at resilience hubs and other critical infrastructure can provide economic and operational value during normal operations—such as lower and more predictable energy costs—as well as resilience and security benefits during power disruptions by maintaining essential services. However, existing evaluation approaches tend to focus narrowly on engineering performance or rely on broad socio-economic frameworks that are not well suited to behind-the-meter storage. As a result, developers, utilities, and funders often lack consistent methods for defining success, quantifying benefits, and comparing outcomes across projects. This report presents a practitioner-oriented impact assessment framework for evaluating behind-the-meter BESS at resilience hubs and critical infrastructure facilities. The framework is organized into five iterative components—developing an action plan, defining project goals, identifying metrics, collecting data and measuring outcomes, and reporting and using results—and includes a structured metric architecture spanning six impact categories. Designed for real-world constraints such as limited staffing and uneven data availability, the framework was developed, applied, and refined through real projects, and is illustrated with case studies across diverse deployment contexts.

Impact Assessment↗

Tuning Internal Strain in Metal–Organic Frameworks via Vapor Phase Infiltration for CO 2 Reduction

Abstract A gas‐phase approach to form Zn coordination sites on metal–organic frameworks (MOFs) by vapor‐phase infiltration (VPI) was developed. Compared to Zn sites synthesized by the solution‐phase method, VPI samples revealed approximately 2.8 % internal strain. Faradaic efficiency towards conversion of CO 2 to CO was enhanced by up to a factor of four, and the initial potential was positively shifted by 200–300 mV. Using element‐specific X‐ray absorption spectroscopy, the local coordination environment of the Zn center was determined to have square‐pyramidal geometry with four Zn−N bonds in the equatorial plane and one Zn‐OH 2 bond in the axial plane. The fine‐tuned internal strain was further supported by monitoring changes in XRD and UV/Visible absorption spectra across a range of infiltration cycles. The ability to use internal strain to increase catalytic activity of MOFs suggests that applying this strategy will enhance intrinsic catalytic capabilities of a variety of porous materials.

Yang, Fan↗

Ethylene Dehydroaromatization over Ga‐ZSM‐5 Catalysts: Nature and Role of Gallium Speciation

Abstract Bifunctional catalysis in zeolites possessing both Brønsted and Lewis acid sites offers unique opportunities to tailor shape selectivity and enhance catalyst performance. Here, we examine the impact of framework and extra‐framework gallium species on enriched aromatics production in zeolite ZSM‐5. We compare three distinct methods of preparing Ga‐ZSM‐5 and reveal direct (single step) synthesis leads to optimal catalysts compared to post‐synthesis methods. Using a combination of state‐of‐the‐art characterization, catalyst testing, and density functional theory calculations, we show that Ga Lewis acid sites strongly favor aromatization. Our findings also suggest Ga(framework)–Ga(extra‐framework) pairings, which can only be achieved in materials prepared by direct synthesis, are the most energetically favorable sites for reaction pathways leading to aromatics. Calculated acid site exchange energies between extra‐framework Ga at framework sites comprised of either Al or Ga reveal a site‐specific preference for stabilizing Lewis acids, which is qualitatively consistent with experimental measurements. These findings indicate the possibility of tailoring Lewis acid siting by the placement of Ga heteroatoms at distinct tetrahedral sites in the zeolite framework, which can have a marked impact on catalyst performance relative to conventional H‐ZSM‐5.

Zhou, Yunwen↗

Carbon Capture Beyond Amines: CO 2 Sorption at Nucleophilic Oxygen Sites in Materials

Carbon capture and utilization or sequestration and direct air capture will be needed to reduce atmospheric levels of greenhouse gases over the next century. Current amine-based technologies bind CO 2 with high selectivities but suffer from poor oxidative and thermal stabilities. Herein, we discuss understudied sorbents based on oxygen nucleophiles, including metal oxides and hydroxides, hydroxide-containing polymers, and hydroxide-based metal–organic frameworks. In general, these materials display improved oxidative stabilities compared to traditional amine-based sorbents. Here, we outline the challenges and opportunities offered by these alternative sorbents for carbon capture applications.

36 MATERIALS SCIENCE↗

Modeling diffusion and types I-V sorption of water vapor in heterogeneous systems

Here, a sorption and diffusion model is developed using a mobile-immobile decomposition of the vapor concentration. Henry’s mode represents the mobile species which diffuses through the solid, while Langmuir and pooling modes represent possible immobilization processes that cause nonlinearities in sorption capacity. The model can simulate the five classical sorption types and can incorporate additional dynamics compared to models based on thermodynamic equilibrium. Additionally, the framework allows for discontinuities in material properties encountered in multi-material systems. The resulting non-linear coupled equations are solved by employing a finite element method to discretize in space, and a backward Euler method to discretize in time. The discretized system of equations is solved via a Newton-type iteration scheme at each time-step. Four different materials are parameterized for the model, which are then used in examples to demonstrate the model’s ability to capture complex sorption processes in multi-material systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Porous materials for hydrogen storage

Hydrogen is a clean energy carrier and a promising candidate to realize carbon-neutral systems for a sustainable future because the combustion of hydrogen produces only water. The large-scale implementation of hydrogen, particularly in zero-emission hydrogen-powered fuel-cell automobiles, requires efficient hydrogen storage systems; however, the current on-board hydrogen storage technologies mainly rely on costly and potentially unsafe high-pressure compression strategies that reach pressures of up to 700 bar. Recently, solid-state porous materials, such as metal-organic frameworks, have emerged as sorbents that can conceivably store comparable amounts of hydrogen in a safer and more efficient manner relative to the current high-pressure storage technologies. Here this review summarizes the current progress on the development of state-of-the-art porous materials and their composites for hydrogen storage. We hope this work will inspire efforts toward creating next-generation hydrogen storage materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gaussian process regression constrained by boundary value problems

We develop a framework for Gaussian processes regression constrained by boundary value problems. The framework may be applied to infer the solution of a well-posed boundary value problem with a known second-order differential operator and boundary conditions, but for which only scattered observations of the source term are available. Scattered observations of the solution may also be used in the regression. The framework combines co-kriging with the linear transformation of a Gaussian process together with the use of kernels given by spectral expansions in eigenfunctions of the boundary value problem. Furthermore, it benefits from a reduced-rank property of covariance matrices. We demonstrate that the resulting framework yields more accurate and stable solution inference as compared to physics-informed Gaussian process regression without boundary condition constraints.

42 ENGINEERING↗

Performance and transport in the ARC tokamak

The ARC TM tokamak, a high-field (𝐵 𝑇 = 11.4 T) fusion power plant, under development by Commonwealth Fusion Systems, is studied using a suite of integrated modelling tools to predict its fusion power generation (𝑃𝑓⁡𝑢⁢𝑠), transport and confinement properties. Analysis is based off an ARC operational point scoped first with zero-dimensional (0-D) plasma operational contour (POPCON) modelling to produce 1.13 GW of fusion power. A suite of integrated modelling tools (TRANSP, ASTRA and TORAX) were applied to predict the performance and kinetic profiles of the ARC design point, yielding a range of predicted performance spanning from ∼900 to 1300 MW in rough quantitative agreement with POPCON predictions. The sensitivity of these results to uncertain modelling inputs was probed using scans of pedestal boundary conditions around EPED-predicted values (total pressure and temperature ratios), tungsten concentration and seperatrix density around their nominal assumptions. Pedestal pressure and pedestal top (𝑇 𝑖 /𝑇 𝑒 ) play a large role in 1.5-dimensional performance predictions, able to modify the predicted 𝑃 𝑓⁡𝑢⁢𝑠 by a factor of 2 within reasonable assumptions. High-fidelity core nonlinear gyrokinetic profile predictions, performed using CGYRO (Candy et al. 2016 J. Comput. Phys., vol. 324, pp. 73–93) coupled with the PORTALS (Rodriguez-Fernandez et al. 2024 Nucl. Fusion, vol. 64, 076034; Phys. Plasmas, vol. 31, 2024, 062501) framework, yield substantially lower performance (𝑃 𝑓⁡𝑢⁢𝑠 =677 MW) compared with 0-D and medium-fidelity modelling for nominal assumptions, showing that there is non-negligible uncertainty between models and that future work on SPARC may help resolve discrepancies. Lower overall performance results from significantly reduced volume-averaged densities and temperatures, along with reduced levels of density and temperature peaking. Turbulence and transport are largely dominated by ion temperature gradient across the profile, confirmed by both linear stability and the response of the nonlinear fluxes to changes in gradients, with some impact of kinetic ballooning modes in the deep core. This work represents one of the most complete scoping of potential fusion power plant conditions performed to date. The extensive integrated modelling provides confidence in ARC performance approaching 1 GW, while nonlinear gyrokinetic modelling results in open questions into the physics of density and temperature peaking in fusion-power-plant-relevant operational space. A discussion of results and the role that the SPARC tokamak (Creely et al. 2020 J. Plasma Phys., vol. 86, 865860502) will play in informing ARC design, performance and operation is presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Robust, Accurate, and Efficient: Quantum Embedding Using the Huzinaga Level-Shift Projection Operator for Complex Systems

Using wave function (WF) in density functional theory (DFT) embedding methods provides a framework for performing localized, high-accuracy WF calculations on a system, while not incurring the full computational cost of the WF calculation on the full system. To effectively partition a system into localized WF and DFT subsystems, we utilize the Huzinaga level-shift projection operator within an absolutely localized basis. In this work, we study the ability of the absolutely localized Huzinaga level-shift projection operator method to study complex WF and DFT partitions, including partitions between multiple covalent bonds, a double bond, and transition-metal–ligand bonds. We find that our methodology can accurately describe all of these complex partitions. Additionally, we study the robustness of this method with respect to the WF method, specifically where the embedded systems were described using a multiconfigurational WF method. We found that the method is systematically improvable with respect to both the number of atoms in the WF region and the size of the basis set used, with energy errors less than 1 kcal/mol. Additionally, we calculated the adsorption energy of H2 to a model of an iron metal–organic framework (Fe-MOF-74) to within 1 kcal/mol compared to CASPT2 calculations performed on the full model while incurring only a small fraction of the full computational cost. In conclusion, this work demonstrates that the absolutely localized Huzinaga level-shift projection operator method is applicable to very complex systems with difficult electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Side-Chain and Ring-Size Effects on Permeability in Artificial Water Channels

Artificial water channels (AWCs) have emerged as a promising framework for stable water permeation, with water transport rates comparable to aquaporins (3.4–40.3 × 10 8 H 2 O/channel/s). In this study, we probe the influence of ring-size and side-chain length on the water permeability observed within a class of AWCs termed ligand-appended pillar[n]arenes (LAPs) that have an adjustable ring-size (m) and side-chain length (n). Through all-atom molecular dynamics simulations, we calculate the permeability of these channels using the collective diffusion model and find their permeabilities. We characterize the mechanistic influence of pillar[n]arene ring-size and side-chain length on the channel water permeability by analyzing the characteristics of the internal permeating water-wire and the surrounding channel structure. We observe that water permeability decreases as a function of increasing ring-size due to increases in hydrophilic contacts between the permeating water-wire and the oxygen groups on the channel wall. Further, we observe an increase in water permeability as a function of side-chain length due to increased partitioning of the channel terminal groups into the hydrophilic blocks of the surrounding bilayer. For the LAP6 channel, with increase in side-chain length, the distance between terminal groups increases and leads to an increase in pore size, thereby enhancing water permeability. In the case of LAP5, as side-chain length increases, the channel displays a compensatory effect between tilt and bend angle due to the flexible side-chains. Such flexibility leads to higher terminal group partitioning in the hydrophilic blocks of the bilayer and extends the permeating water-wire. Furthermore, this increase in water-wire length and hydrophilic block access overcomes the nonmonotonic pore size trend in pillar[5]arene channels.

36 MATERIALS SCIENCE↗

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗

Dynamic mode decomposition with core sketch

With the increase in collected data volumes, either from experimental measurements or high fidelity simulations, there is an ever-growing need to develop computationally efficient tools to process, analyze, and interpret these datasets. Modal analysis techniques have gained great interest due to their ability to identify patterns in the data and extract valuable information about the system being considered. Dynamic mode decomposition (DMD) relies on elements of the Koopman approximation theory to compute a set of modes, each associated with a fixed oscillation frequency and a decay/growth rate. Extracting these details from large datasets can be computationally expensive due to the need to implement singular value decomposition of the input data matrix. Sketching algorithms have become popular in numerical linear algebra where statistical theoretic approaches are utilized to reduce the cost of major operations. A sketch of a matrix is another matrix, which is significantly smaller, but still sufficiently approximates the original system. We put forth an efficient DMD framework, SketchyDMD, based on a core sketching algorithm that captures information about the range and corange (their mutual relationship) of input data. The proposed sketching-based framework can accelerate various portions of the DMD routines, compared to classical methods that operate directly on the raw input data. We conduct numerical experiments using the spherical shallow water equations as a prototypical model in the context of geophysical flows. In conclusion, we show that the proposed SketchyDMD is superior to existing randomized DMD methods that are based on capturing only the range of the input data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evidence for triaxial shape coexistence in 74 Ge

The deformation properties of the low-lying states in 74 Ge have been investigated using multistep Coulomb excitation. The measurements were carried out with the advanced 𝛾-ray tracking array, GRETINA, and the CHICO2 particle detector. A comprehensive set of 𝐸⁢2 transition and diagonal matrix elements was deduced following an analysis with the semiclassical coupled-channels code GOSIA. The data were compared with results of calculations carried out within the framework of the generalized triaxial rotor model as well as with the configuration interaction shell model and the symmetric rotor model. Results from calculations with covariant density functional theory were used to construct a five-dimensional collective Hamiltonian for further comparisons with the data. Collectively, the calculations provide an accurate reproduction of the experimental matrix elements and further support an understanding in terms of the coexistence of two axially asymmetric shapes. In conclusion, this leads to an overall interpretation of the underlying structure of 74 Ge requiring triaxiality, as is also the case in the neighboring even-mass Ge isotopes.

59 ≤ A ≤ 89↗

Possible wobbling phenomenon in 125 Xe

In the present paper, negative-parity bands based on the νh 11/2 configuration in 125 Xe have been revisited. This nucleus was populated through the reaction 82 Se( 48 Ca, 5n) 125 Xe at a beam energy of 205 MeV and the corresponding γ rays were observed using the Gammasphere spectrometer. Evidence for first and second phonon wobbling excitations has been established by measurements of directional correlation ratios and angular distributions of the involved γ rays. Here, the observed wobbling energy of the bands involved were compared with the recently published results obtained within the framework of triaxial projected shell-model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Lifetime measurements in 102 Mo interpreted in the interacting boson model and the X(5) symmetry

Lifetimes of low-lying excited states in 102 Mo populated in the two-neutron transfer reaction 100 Mo ⁢( 18 O, 16 O)⁢ 102 Mo were measured using the recoil distance Doppler shift method at the IFIN-HH Tandem accelerator. Lifetimes of the $2^+_1$, $0^+_2$, $4^+_1$, $2^+_2$, $2^+_3$, $3^+_1$, $6^+_1$, ($0^+_3$), $4^+_2$, ($3^−_1$), and ($5^−_1$) states were obtained. The deduced electromagnetic transition strengths have been compared to calculations performed in the interacting boson model framework including models representing the U(5) and X(5) symmetries. It is found that 102 Mo lies between the U(5) limit and the X(5) critical point symmetry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Generalized parton distributions from the pseudodistribution approach on the lattice

Generalized parton distributions (GPDs) are key quantities for the description of a hadron’s three-dimensional structure. They are the current focus of all areas of hadronic physics—phenomenological, experimental and theoretical, including lattice QCD. Synergies between these areas are desirable and essential to achieve precise quantification and understanding of the structure of, particularly, nucleons, as the basic ingredients of matter. In this paper, we investigate, for the first time, the numerical implementation of the pseudodistribution approach for the extraction of zero-skewness GPDs for unpolarized quarks. Pseudodistributions are Euclidean parton correlators computable in lattice QCD that can be perturbatively matched to the light-cone parton distributions of interest. Although they are closely related to the quasidistributions and come from the same lattice-extracted matrix elements, they are, however, subject to different systematic effects. We use the data previously utilized for quasi-GPDs and extend it with other momentum transfers and nucleon boosts, in particular a higher one ( P 3 = 1.67 GeV ) with eightfold larger statistics than the largest one used for quasidistributions ( P 3 = 1.25 GeV ). We renormalize the matrix elements with a ratio scheme and match the resulting Ioffe time distributions to the light cone in coordinate space. The matched distributions are then used to reconstruct the x dependence with a fitting . We investigate some systematic effects related to this procedure, and we also compare the results with the ones obtained in the framework of quasi-GPDs. Our final results involve the invariant four-momentum transfer squared ( − t ) dependence of the flavor nonsinglet ( u − d ) H and E GPDs. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗