Pathways to sustainability: a quantitative comparison of aerobic and anaerobic C1 bioconversion routes
Not Available
Gasparrini, William↗
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Quantitative multiplexed analysis of gene and protein expression patterns in Yarrowia lipolytica
In this report, we present coordinated observations of protein and mRNA transcript counts at the single-cell level in the oleaginous yeast model Yarrowia lipolytica. The transcription factor Xbp1p regulates entry into a quiescent state, representing a shift of resources to sequestration of nutrients rather than cell division. We observed the responses of wild-type and Δxbp1 cells to protein (by fluorescence) and transcript quantification and localization at both single-cell and population-averaged levels. Data were collected via single-molecule fluorescence in situ hybridization (smFISH) and qPCR under nitrogen depletion, a condition that drives lipid accumulation. These techniques reveal a complex and heterogeneous population of Xbp1p dynamics and downstream regulation. Our findings highlight the need for single-cell resolution analyses to describe cellular dynamics and regulatory processes.
Yarrowia lipolytica↗
The energy supply security pyramid: A quantitative framework for planning and policy making
Not Available
Sulzer, Matthias (ORCID:0000000320942460)↗
Quantitative SANS and multi-model analysis of spacer-dependent micellization of urea-based gemini surfactants
The micellization behavior of urea-based cationic gemini surfactants was investigated using small-angle neutron scattering (SANS) with multi-model form factor analysis. A homologous series of surfactants with urea group included in the hydrophobic tail and polymethylene spacers consisting of two to ten methylene units was analyzed using three form factor models: a core–shell ellipsoid and two variants of homogeneous ellipsoids. The results from all models show a consistent trend of the micelle structures, confirming that the spacer length critically influences micellar geometry, aggregation number, and hydration. The surfactant with four CH 2 groups in the spacer formed the largest micelles with the highest aggregation number, while longer spacers led to progressively smaller, more compact aggregates. The shell hydration—quantified as the volume fraction of heavy water within the hydrophilic region—decreased systematically with increasing spacer length due to enhanced hydrophobicity of the headgroup-spacer region. Intermicellar interactions, modeled as screened Coulomb interaction using the rescaled mean spherical approximation (RMSA), revealed the strongest electrostatic repulsion for the case of four methylene groups in the spacer, corresponding to the highest micellar charge and largest interparticle spacing. The observed spacer-dependent trends were robust across all modeling approaches, demonstrating that the spacer length serves as a key structural determinant of self-assembly in this type of urea-based gemini systems. These findings provide insight into the design of gemini surfactants with tailored aggregation behavior for applications in drug delivery, nanostructure templating, and solubilization technologies.
Core–shell ellipsoid model↗
Quantitative Structure–Activity Relationship Models to Predict Cardiac Adverse Effects
Not Available
Mou, Zhongyu↗
Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data
Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.
36 MATERIALS SCIENCE↗
First-Principles-Based Study of the Decomposition of Phenol and Hydroquinone on Pt(111) Combined with Quantitative Information from XPS Spectra to Address the Impact of Coverage and Number of Hydroxyl Functional Groups
A combined first-principles-based and experimental X-ray photoelectron spectroscopy approach was used to investigate the thermal decomposition of two model biofuel compounds, phenol and hydroquinone, on Pt(111) at both low and high coverages. The DFT-based approach yields adsorption geometries and energies, activation barriers and core-level binding energy shifts for C 1s and O 1s. Increasing the coverage in the theoretical model leads to slight shifts in core-level binding energies─toward higher values for C 1s and lower values for O 1s. It also alters the energy profiles of the decomposition reaction pathway, resulting in weaker adsorption energies and changes in both reaction and activation barriers. At low temperatures, we observe a multilayer for phenol and hydroquinone upon adsorption, with desorption occurring at 200 and 270 K, respectively. Following desorption of the multilayer, decomposition proceeds via initial O–H bond scission, followed by two parallel pathways involving either C–H or C–C bond scission, whereby in the case of phenol C–H bond scission occurs first. Here, we further provide characteristic core level binding energies by theoretical calculations that are subsequently used in experimental analyses, establishing a reference database for key spectra of phenolic functionalities applicable to a range of catalytic reactions.
09 BIOMASS FUELS↗
Quantitative Encapsulation and Homogeneity Assessment of Sol–Gel Based Nuclear Explosive Debris Simulants
Nuclear explosive debris simulants are an important material in training and validating aspects of post-detonation nuclear forensic processes. Realistic simulants should replicate several aspects of nuclear explosive debris such as the size, shape, color, density, and chemical and radiological properties. Silica particles produced via sol-gel synthesis have recently been found to successfully reproduce many of these parameters including the controllable incorporation of radionuclide content. However, to be useful as a benchmarking material for validation and verification of laboratory methodologies, radionuclide content from batch-to-batch must be reproducible. Here, in this work, we explore the variance in radionuclide distribution incorporated into sol-gel benchmarking materials with respect to sample subdivision. Results will help inform the sample sizes required to minimize variance between samples.
36 - MATERIALS SCIENCE↗
Quantitative Analysis and Prediction of Thermal Runaway Metrics of High-Nickel Oxide Cathodes by Machine Learning Models
The pursuit of higher energy density in lithium-ion batteries has made high-nickel (Ni) layered oxides leading cathode candidates for next-generation electric vehicles. However, their poor thermal stability, particularly at Ni contents ≥ 90%, increases the risk of cathode-initiated thermal runaway. Furthermore, we present a data-driven framework combining linear and nonlinear machine learning models to predict key thermal runaway descriptors from a high-throughput differential scanning calorimetry database. With cathode composition and state of charge (SOC) as input features, the ensemble model accurately predicts peak temperature, heat release, and peak heat flow. SHAP analysis identifies Ni content and SOC as the dominant factors controlling thermal runaway temperature, while SOC primarily governs heat release and peak heat flow. Al, Mg, and Mn improve thermal stability by strengthening metal–oxygen bonding and delaying structural transformation, whereas B mainly reduces heat release through surface passivation. Validation with a new cathode composition confirms accurate prediction of SOC-dependent thermal runaway behavior and critical SOC.
25 ENERGY STORAGE↗
Quantitative Measurement of Molecular Permeability to a Synthetic Bacterial Microcompartment Shell System
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
Quantitative Determination of Electronic Effects in Free Radicals through Open-Shell Hammett Substituent Constants
Hammett substituent constants (σ), which quantify the electronic effects of functional groups, are widely used for predicting the properties of organic compounds and investigating reaction mechanisms. While these values have been obtained for a wide range of closed-shell substituents, measurements of analogous values for open-shell substituents are rare due to challenges associated with their short lifetimes. Here, in this report, we developed a combined experimental and computational approach for quantifying the electronic properties of open-shell substituents based on changes in nitrile vibrational frequencies (ν(C≡N)). By coupling pulse radiolysis and time-resolved infrared spectroscopy (PR-TRIR), we measured ν(C≡N) IR bands of 30 para - and meta -substituted benzonitriles bearing C-, N-, and S-centered radicals. A linear scaling relationship was obtained between these experimental values and values obtained from DFT calculations. Using these computed values, two different Hammett constants, σ m , and σ p + , were determined for a series of C-, N-, O-, S-, Si-, and B-centered radicals. The differences between σm and σp+ values enable the separate evaluation of inductive and resonance effects in these open-shell substituents. The results suggest that there are three classes of radicals: one is electron withdrawing (σ m , σ p + > 0), one is electron donating (σm, σp+ < 0), and one is inductively withdrawing but resonance donating (σ m > 0, σ p + < 0). Our study represents a general approach to the analysis of the electronic properties of open-shell species and has potential applications in a wide range of molecular processes involving free radical intermediates.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A quantitative comparison of the fingerprint of twinned microstructures through surface and three-dimensional techniques
Assessing the fingerprint of a material’s microstructure is key for supporting materials design. With the emergence of a wide range of 3D characterization techniques, it is critical to understand the main differences in fingerprints reconstructed from 2D and 3D datasets. To this end, we introduce a graph-based microstructure reconstruction framework that enables structural comparisons of twin domain networks in high purity Ti using 3D and 2D electron backscatter diffraction. Insights into the structure of the twin networks are facilitated by combining statistical analysis of twin crystallography with visual and graphical analysis of the novel graph abstractions of the twins. We demonstrate that compared to 3D reconstructions, conventional 2D views of twinning miss key aspects of the microstructure including the high interconnectivity of domains into networks that span the full reconstruction volume. The reduced cross-grain and in-grain twin connectivity typically observed in 2D has notable implications on our understanding of how twinning mediates the plastic response of microstructures and how twin networks evolve. It is thus clear that 3D characterization is critical for accurately inferring both twin network morphologies as well as the key unit processes facilitating network formation.
36 MATERIALS SCIENCE↗
Quantitative kinetic rules for plastic strain-induced α - ω phase transformation in Zr under high pressure
Plastic strain-induced phase transformations (PTs) and chemical reactions under high pressure are broadly spread in modern technologies, friction and wear, geophysics, and astrogeology. However, because of very heterogeneous fields of plastic strain $E$ p and stress σ tensors and volume fraction c of phases in a sample compressed in a diamond anvil cell (DAC) and impossibility of measurements of σ and $E$ p , there are no strict kinetic equations for them. Here, we develop a kinetic model, finite element method (FEM) approach, and combined FEM-experimental approaches to determine all fields in strongly plastically predeformed Zr compressed in DAC, and specific kinetic equation for α-ω PT consistent with experimental data for the entire sample. Since all fields in the sample are very heterogeneous, data are obtained for numerous complex 7D paths in the space of 3 components of the plastic strain tensor and 4 components of the stress tensor. Kinetic equation depends on accumulated plastic strain (instead of time) and pressure and is independent of plastic strain and deviatoric stress tensors, i.e., it can be applied for various above processes. Our results initiate kinetic studies of strain-induced PTs and provide efforts toward more comprehensive understanding of material behavior in extreme conditions.
36 MATERIALS SCIENCE↗
Quantitative assessment of Ni + and He + ion irradiation damage in a tungsten heavy alloy under the simulated nuclear fusion environment
A 90W-7Ni-3Fe (wt.%) tungsten heavy alloy has been sequentially Ni + and He + ion irradiated at 700 °C to simulate the high temperature irradiation environment of a fusion reactor interior. W/Ni–Fe-W dual-phase alloys have been proposed to serve as plasma facing materials and require detailed investigation of their behavior under fusion relevant conditions to assess their overall applicability. To evaluate material performance under five years of simulated fusion reactor service, microstructural characterization of the nanoscale defect distribution has been performed on both constituent phases, revealing peak swelling in the W phase of approximately 0.03%. The γ-phase (Ni–Fe-W) is found to swell approximately 0.68% under the same irradiation conditions, indicating significant cavity formation and growth. Additionally, a novel multi-projection imaging approach has been applied to determine the extent of damage segregation along the dual-phase W-to-γ interface and exposes that these interfaces act as sink sites for the accumulation of cavities. Interphase boundaries are noted to possess an 11.8% areal coverage of defects along the boundary plane, primarily on the γ-phase side of the boundary. The accumulation of cavities at these interphase boundaries is anticipated to adversely affect overall material toughness, and this work reveals a pressing need for mechanical property testing of irradiated W–Ni-Fe dual-phase alloys.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗