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At least 217 records · Page 12

Permutation-adapted complete and independent basis for atomic cluster expansion descriptors

Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These methodologies thus require an additional numerical procedure, such as singular value decomposition (SVD), to eliminate redundant functions. In this work, it is shown that analytical linear relationships for subsets of cluster functions may be derived using recursion and permutation properties of generalized Wigner symbols. From these relationships, subsets (blocks) of cluster functions can be selected such that, within each block, functions are guaranteed to be linearly independent. It is conjectured that this block-wise independent set of permutation-adapted rotation and permutation invariant (PA-RPI) functions forms a complete, independent basis for ACE. Along with the first analytical proofs of block-wise linear dependence of ACE cluster functions and other theoretical arguments, numerical results are offered to demonstrate this. The utility of the method is demonstrated in the development of an ACE interatomic potential for tantalum. Using the new basis functions in combination with Bayesian compressive sensing sparse regression, some high degree descriptors are observed to persist and help achieve high-accuracy models.

Angular momentum↗

Hypoxia-cultured mouse mesenchymal stromal cells from bone marrow and compact bone display different phenotypic traits

Highlights: • Mouse compact bone is richer in MSC compared to central bone marrow. • Derivation of MSC from mouse compact bone is associated with lower risk of contamination with hematopoietic cells. • MSC from compact bone display higher osteogenic differentiation capacity than bone marrow MSC. It has been suggested that the bone marrow microenvironment harbors two distinct populations of mesenchymal stromal cells (MSC), one with a perivascular location and other present in the endosteum. A better understanding of the biology of these MSC subsets has been pursued in order to refine its clinical application. However, most comparative characterizations of mouse MSC have been performed in normoxia. This can result in misleading interpretations since mouse MSC subsets with low/defective p53 activity are known to be selected during culture in normoxia. Here, we report a comprehensive in vitro characterization of mouse MSC isolated from bone marrow (BM-MSC) and compact bone (CB-MSC) expanded and assayed under hypoxia for their morphology, clonogenic efficiency and differentiation capacity. We found that, under hypoxia, compact bone is richer in absolute numbers of MSC and isolation of MSC from compact bone is associated with a reduced risk of hematopoietic cell carryover. In addition, CB-MSC have higher in vitro osteogenic capacity than BM-MSC, while adipogenic differentiation potential is similar. These findings reinforce the hypothesis of the existence of MSC in bone marrow and compact bone representing functionally distinct cell populations and highlight the compact bone as an efficient source of murine MSC under physiological oxygen concentrations.

60 APPLIED LIFE SCIENCES↗

Antitumor CD8 T cell responses in glioma patients are effectively suppressed by T follicular regulatory cells

Regulatory T (Treg) cells are thought to contribute to tumor pathogenesis by suppressing tumor immunosurveillance and antitumor immunity. T follicular regulatory (Tfr) cells are a recently characterized Treg subset that expresses both the Treg transcription factor (TF) Foxp3 and the T follicular helper (Tfh) TF Bcl-6. The role of Tfr cells in glioma patients remains unclear. In this study, we found that the level of Tfr cells, identified as Foxp3{sup +}Bcl-6{sup +} CD4 T cells, was significantly elevated in tumor-infiltrating CD4 T cells from resected glioma tumors. Both Tfr cells and Treg cells significantly suppressed the proliferation and the cytotoxic capacity of CD8 T cells toward glioma tumor cells, and the suppression was positively associated with the proportion of Tfr cells and Treg cells, respectively. Tfr and Treg cells from glioma tumor samples demonstrated higher suppression potency than those from healthy blood samples and glioma blood samples. Interestingly, canonical CXCR5{sup -} Treg cells could suppress both CXCR5{sup +} and CXCR5{sup -} CD8 T cells, albeit with stronger potency toward CXCR5{sup -} CD8 T cells. However, Tfr cells presented much higher suppression potency toward CXCR5{sup +} CD8 T cells, whereas CXCR5{sup +} CD8 T cells are a potent CD8 T cell subset previously described to have antiviral and antitumor roles. Overall, these data indicate that Tfr cells are enriched in glioma tumors and have suppressive capacity toward CD8 T cell-mediated effector functions.

60 APPLIED LIFE SCIENCES↗

Photoinduced Dynamics with Constrained Vibrational Motion: FrozeNM Algorithm

Ab initio molecular dynamics (AIMD) simulation, analyzed in terms of vibrational normal modes, is a widely used technique that facilitates understanding of complex structural motions and coupling between electronic and nuclear degrees of freedom. Usually, only a subset of vibrations is directly involved in the process of interest. The impact of these vibrations can be evaluated by performing AIMD simulations by selectively freezing certain motions. In this paper, we present frozen normal mode (FrozeNM), a new algorithm to apply normal-mode constraints in AIMD simulations, as implemented in the nonadiabatic excited state molecular dynamics code. We further illustrate its capacity by analyzing the impact of normal-mode constraints on the photoinduced energy transfer between polyphenylene ethynylene dendrimer building blocks. Our results show that the electronic relaxation can be significantly slowed down by freezing a well-selected small subset of active normal modes characterized by their contributions in the direction of energy transfer. The application of these constraints reduces the nonadiabatic coupling between electronic excited states during the entire dynamical simulations. Furthermore, we validate reduced dimensionality models by freezing all the vibrations, except a few active modes. Altogether, we consider FrozeNM as a useful tool that can be broadly used to underpin the role of vibrational motion in a studied process and to formulate reduced models that describe essential physical phenomena.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Benchmark Data Set of Crystalline Organic Semiconductors

This work reports a Benchmark Data set of Crystalline Organic Semiconductors to test calculations of the structural and electronic properties of these materials in the solid state. The data set contains 67 crystals consisting of mostly rigid molecules with a single dominant conformer, covering the majority of known structural types. The experimental crystal structure is available for the entire data set, whereas zero-temperature unit cell volume can be reliably estimated for a subset of 28 crystals. Using this subset, we benchmark r 2 SCAN-D3 and PBE-D3 density functionals. Then, for the entire data set, we benchmark approximate density functional theory (DFT) methods, including GFN1-xTB and DFTB3(3ob-3-1), with various dispersion corrections against r 2 SCAN-D3. Our results show that r 2 SCAN-D3 geometries are accurate within a few percent, which is comparable to the statistical uncertainty of experimental data at a fixed temperature, but the unit cell volume is systematically underestimated by 2% on average. The several times faster PBE-D3 provides an unbiased estimate of the volume for all systems except for molecules with highly polar bonds, for which the volume is substantially overestimated in correlation with the underestimation of atomic charges. Considered approximate DFT methods are orders of magnitude faster and provide qualitatively correct but overcompressed crystal structures unless the dispersion corrections are fitted by unit cell volume.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Curvature Energetics Determined by Alchemical Simulation on Four Topologically Distinct Lipid Phases

The relative curvature energetics of two lipids are tested using thermodynamic integration (TI) on four topologically distinct lipid phases. Simulations use TI to switch between choline headgroup lipids (POPC; that prefers to be flat) and ethanolamine headgroup lipids (POPE; that prefer, for example, the inner monolayer of vesicles). Here, the thermodynamical moving of the lipids between planar, inverse hexagonal (H II ), cubic (Q II ; Pn3m space group), and vesicle topologies reveals differences in material parameters that were previously challenging to access. The methodology allows for predictions of two important lipid material properties: the difference in POPC/POPE monolayer intrinsic curvature (ΔJ 0 ) and the difference in POPC/POPE monolayer Gaussian curvature modulus (Δ$\bar{κ_m}$), both of which are connected to the energetics of topological variation. Analysis of the TI data indicates that, consistent with previous experiment and simulation, the J 0 of POPE is more negative than POPC (ΔJ 0 = –0.018 ± 0.001 Å –1 ). The theoretical framework extracts significant differences in $\bar{κ_m}$ of which POPE is less negative than POPC by 2.0 to 4.0 kcal/mol. The range of these values is determined by considering subsets of the simulations, and disagreement between these subsets suggests separate mechanical parameters at very high curvature. Finally, the fit of the TI data to the model indicates that the position of the pivotal plane of curvature is not constant across topologies at high curvature. Overall, the results offer insights into lipid material properties, the limits of a single HC model, and how to test them using simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impacts of Solvent Washing on the Electrochemical Remediation of Commercial End-of-Life Cathodes

Changes to surface structure and chemistry occurring throughout the functional lifetime of lithium-ion batteries (LIBs) may impact the effectiveness of end-of-life rejuvenation methods. Solvent washing prior to electrochemical relithiation is shown to both increase relithiation efficacy and beneficially alter the interfacial chemistry of heavily degraded industrial cathode material. Four common solvents (acetone, diethyl carbonate, isopropyl alcohol, propylene carbonate) are employed to investigate the role of varying physicochemical solvent properties on the mechanism of capacity recovery. Electrochemical (dQ/dV, EIS), structural (XRD), and chemical (SPME-GC-MS) analysis techniques are employed to comprehensively analyze solvent-cathode interactions. Highly nucleophilic solvents (acetone, DEC) are found to reduce cathode charge-transfer impedance and enable stable impedance growth throughout subsequent cycling. The use of nucleophilic solvents under mechanically aggressive washing conditions may also enable the reintroduction of bulk lattice oxygen, thereby restoring anionic redox capacity. Further, the four solvents are found to selectively remove a subset of surface species from the aged cathode material, including residual electrolyte, additives, and electrolyte-additive reaction products, which are qualitatively analyzed. Surface species removal by each solvent is correlated with the electrochemical performance of the correspondingly washed cathode, highlighting the importance of an optimized washing protocol to effective remediation in the context of direct LIB recycling. For the material under study, the use of a simple acetone washing protocol prior to electrochemical relithiation enables up to 174% capacity recovery relative to unwashed/relithiated black mass.

ADVANCED PROPULSION SYSTEMS↗

Utilizing Environmental Tracers to Reduce Groundwater Flow and Transport Model Parameter Uncertainties

Abstract Non‐uniqueness in groundwater model calibration is a primary source of uncertainty in groundwater flow and transport predictions. In this study, we investigate the ability of environmental tracer information to constrain groundwater model parameters. We utilize a pilot point calibration procedure conditioned to subsets of observed data including: liquid pressures, tritium ( 3 H), chlorofluorocarbon‐12 (CFC‐12), and sulfur hexafluoride (SF 6 ) concentrations; and groundwater apparent ages inferred from these environmental tracers, to quantify uncertainties in the heterogeneous permeability fields and infiltration rates of a steady‐state 2‐D synthetic aquifer and a transient 3‐D model of a field site located near Riverton, Wyoming (USA). To identify the relative data worth of each observation data type, the post‐calibration uncertainties of the optimal parameters for a given observation subset are compared to that from the full observation data set. Our results suggest that the calibration‐constrained permeability field uncertainties are largest when liquid pressures are used as the sole calibration data set. We find significant reduction in permeability uncertainty and increased predictive accuracy when the environmental tracer concentrations, rather than apparent groundwater ages, are used as calibration targets in the synthetic model. Calibration of the Riverton field site model using environmental tracer concentrations directly produces infiltration rate estimates with the lowest uncertainties, however; permeability field uncertainties remain similar between the environmental tracer concentration and apparent groundwater age calibration scenarios. This work provides insight on the data worth of environmental tracer information to calibrate groundwater models and highlights potential benefits of directly assimilating environmental tracer concentrations into model parameter estimation procedures.

54 ENVIRONMENTAL SCIENCES↗

Model Evaluation and Intercomparison of Marine Warm Low Cloud Fractions With Neural Network Ensembles

Abstract Low cloud fractions (LCFs) and meteorological factors (MFs) over an oceanic region containing multiple cloud regimes are examined for three data sets: one Energy Exascale Earth System Model (E3SM) simulation with the default 72‐layer vertical grid (E3SM72), another one with 8‐times vertical resolution via the Framework for Improvement by Vertical Enhancement (E3SM 8), and one with MFs from ERA5 reanalysis and LCFs from the CERES SSF product (ERA5‐SSF). Neural networks (NNs) are trained to capture the relationship between MFs and LCF and to select the best‐performing MF subsets for predicting LCF. NN ensembles are used to (a) confirm the performance of selected MF subsets, (b) to serve as proxy models for each data set to predict LCFs for MFs from all data sets, and (c) to classify MFs into those in shared and uniquely occupied MF subspaces. Overall, E3SM72 and E3SM 8 have large fractions of MFs in shared MF subspace, but less so near the Californian and Peruvian stratocumulus decks. E3SM 8 and ERA5 have small fractions of MFs in shared MF subspace but greater than E3SM72 and ERA5, especially in the Southeast Pacific. The differences in LCFs between three pairs of data sets are decomposed into those associated with the differences in the LCF‐MF relationship and those involving different MFs. Given the same MFs, LCFs produced by E3SM 8 are greater than those produced by E3SM72 but are still different from those in ERA5‐SSF. In general, the shift in MFs dominates the difference in the LCFs.

54 ENVIRONMENTAL SCIENCES↗

A spatio-temporally constrained gene regulatory network directed by PBX1/2 acquires limb patterning specificity via HAND2

A lingering question in developmental biology has centered on how transcription factors with widespread distribution in vertebrate embryos can perform tissue-specific functions. Here, using the murine hindlimb as a model, we investigate the elusive mechanisms whereby PBX TALE homeoproteins, viewed primarily as HOX cofactors, attain context-specific developmental roles despite ubiquitous presence in the embryo. We first demonstrate that mesenchymal-specific loss of PBX1/2 or the transcriptional regulator HAND2 generates similar limb phenotypes. By combining tissue-specific and temporally controlled mutagenesis with multi-omics approaches, we reconstruct a gene regulatory network (GRN) at organismal-level resolution that is collaboratively directed by PBX1/2 and HAND2 interactions in subsets of posterior hindlimb mesenchymal cells. Genome-wide profiling of PBX1 binding across multiple embryonic tissues further reveals that HAND2 interacts with subsets of PBX-bound regions to regulate limb-specific GRNs. Our research elucidates fundamental principles by which promiscuous transcription factors cooperate with cofactors that display domain-restricted localization to instruct tissue-specific developmental programs.

59 BASIC BIOLOGICAL SCIENCES↗

Entropy-driven order in an array of nanomagnets

Long-range ordering is typically associated with a decrease in entropy. Yet, it can also be driven by increasing entropy in certain special cases. Here we demonstrate that artificial spin-ice arrays of single-domain nanomagnets can be designed to produce such entropy-driven order. We focus on the tetris artificial spin-ice structure, a highly frustrated array geometry with a zero-point Pauling entropy, which is formed by selectively creating regular vacancies on the canonical square ice lattice. We probe thermally active tetris artificial spin ice both experimentally and through simulations, measuring the magnetic moments of the individual nanomagnets. Furthermore, we find two-dimensional magnetic ordering in one subset of these moments, which we demonstrate to be induced by disorder (that is, increased entropy) in another subset of the moments. In contrast with other entropy-driven systems, the discrete degrees of freedom in tetris artificial spin ice are binary and are both designable and directly observable at the microscale, and the entropy of the system is precisely calculable in simulations. This example, in which the system’s interactions and ground-state entropy are well defined, expands the experimental landscape for the study of entropy-driven ordering.

36 MATERIALS SCIENCE↗

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. Furthermore, we observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

97 MATHEMATICS AND COMPUTING↗

Comprehensive characterization of the structure of Zr-based metallic glasses

Structure of metallic glasses fascinates as the generic amorphous structural template for ubiquitous systems. Its specification necessitates determination of the complete hierarchical structure, starting from short-range-order (SRO) → medium-range-order (MRO) → bulk structure and free volume (FV) distribution. This link has largely remained elusive since previous investigations adopted one-technique-at-a-time approach, focusing on limited aspects of any one domain. Reconstruction of structure from experimental data inversion is non-unique for many of these techniques. As a result, complete and precise structural understanding of glass has not emerged yet. In this work, we demonstrate the first experimental pathway for reconstruction of the integrated structure, for and glasses. Our strategy engages diverse (×7) multi-scale techniques [XAFS, 3D-APT, ABED/NBED, FEM, XRD, PAS, FHREM] on the same glass. This strategy complemented mutual limitations of techniques and corroborated common parameters to generate complete, self-consistent and precise parameters. Further, MRO domain size and inter-void separation were correlated to identify the presence of FV at MRO boundaries. This enabled the first experimental reconstruction of hierarchical subset: SRO → MRO → FV → bulk structure. The first ever image of intermediate region between MRO domains emerged from this link. We clarify that determination of all subsets is not our objective; the essence and novelty of this work lies in directing the pathway towards finite solution, in the most logical and unambiguous way.

36 MATERIALS SCIENCE↗

scRNA seq of an F1 cross of Marek’s disease resistant and susceptible chickens identifies allele specific expression signatures enriched in transcription modulators

Abstract Marek’s disease (MD), a T cell lymphoma disease in chickens, is caused by the Marek’s disease virus (MDV) found ubiquitously in the poultry industry. Genetically resistant Line 6 3 (L6) and susceptible Line 7 2 (L7) chickens have been instrumental to research on avian immune system response to MDV infection. In this study we characterized molecular signatures unique to splenic immune cell types across different genetic backgrounds 6 days after infection. Using three populations, L6, L7, and an F1 cross between L6xL7, we evaluated the immune cell transcriptome of responding cell types using single cell RNA sequencing. Several MDV genes were found expressed mainly in cytotoxic T cells while ICP4 and MEQ MDV genes were expressed across infected cell types. Using the F1 we quantified allele specific expression (ASE) of biallelic SNPs and found biased expression of parental alleles specific to immune cell subtypes. We identified 22 SNPs with ASE in response to MDV infection mapped to gene rich regions surrounding 59 genes of critical importance for chromatin remodeling and transcriptional regulation. Histone deacetylase genes (HDAC1 and HDAC8) had increased expression of L6 alleles, while small nuclear RNA genes (SNORA68 and SNORA72) expressed higher levels of L7 alleles with infection in T cell subsets. SNPs with ASE also mapped genes important for an adequate immune response including GNLY (cytotoxic activity) and PDIA3 (component of MHC class I peptide loading complex), and genes known to promote viral replication (MCM5 and EIF3M). These results show that functional variants associated with susceptibility to MD may have a bigger impact in subsets of immune cell types, and by characterizing the transcriptomes of these subtypes we can unravel molecular signatures specific to MD genomic resistance.

Science & Technology - Other Topics↗

Design and synthesis of aryl-functionalized carbazole-based porous coordination cages

A subset of coordination cages have garnered considerable recent attention for their potential permanent porosity in the solid state. Herein, we report a series of functionalized carbazole-based cages of the structure type M 12 (R-cdc) 12 (M = Cr, Cu, Mo) where the functional groups include a range of aromatic substituents. Single-crystal X-ray structure determinations reveal a variety of intercage interactions in these materials, largely governed by pi–pi stacking. Density functional theory for a subset of these cages was used to confirm that the nature of the increased stability of aryl-functionalized cages is a result of inter-cage ligand interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Planck intermediate results

In this work, we describe an extension of the most recent version of the Planck Catalogue of Compact Sources (PCCS2), produced using a new multi-band Bayesian Extraction and Estimation Package (BeeP). BeeP assumes that the compact sources present in PCCS2 at 857 GHz have a dust-like spectral energy distribution (SED), which leads to emission at both lower and higher frequencies, and adjusts the parameters of the source and its SED to fit the emission observed in Planck’s three highest frequency channels at 353, 545, and 857 GHz, as well as the IRIS map at 3000 GHz. In order to reduce confusion regarding diffuse cirrus emission, BeeP’s data model includes a description of the background emission surrounding each source, and it adjusts the confidence in the source parameter extraction based on the statistical properties of the spatial distribution of the background emission. BeeP produces the following three new sets of parameters for each source: (a) fits to a modified blackbody (MBB) thermal emission model of the source; (b) SED-independent source flux densities at each frequency considered; and (c) fits to an MBB model of the background in which the source is embedded. BeeP also calculates, for each source, a reliability parameter, which takes into account confusion due to the surrounding cirrus. This parameter can be used to extract sub-samples of high-frequency sources with statistically well-understood properties. We define a high-reliability subset (BeeP/base), containing 26 083 sources (54.1% of the total PCCS2 catalogue), the majority of which have no information on reliability in the PCCS2. We describe the characteristics of this specific high-quality subset of PCCS2 and its validation against other data sets, specifically for: the sub-sample of PCCS2 located in low-cirrus areas; the Planck Catalogue of Galactic Cold Clumps; the Herschel GAMA15-field catalogue; and the temperature- and spectral-index-reconstructed dust maps obtained with Planck’s Generalized Needlet Internal Linear Combination method. The results of the BeeP extension of PCCS2, which are made publicly available via the Planck Legacy Archive, will enable the study of the thermal properties of well-defined samples of compact Galactic and extragalactic dusty sources.

79 ASTRONOMY AND ASTROPHYSICS↗

Tracing the outflow kinematics in Type 2 active galactic nuclei

Here, we used a sample of 577 spectra of active galactic nuclei Type 1.8-2 (z < 0.25) taken from the Sloan Digital Sky Survey to trace the influence of the outflow kinematics on the profiles of different emission lines (Hβ, [O III], Hα, [N II], [S II]). All considered lines were fitted with two Gaussian components: one that fits the core of the line, and another that fits the wings. We provide a procedure for decomposition of the Hα+[N II] wavelength band for spectra where these lines overlap. The influence of the gravitational and non-gravitational kinematics on the line components is investigated by comparing the dispersions of the line components with stellar velocity dispersion. We find that wing components of all the considered emission lines have pure non-gravitational kinematics. The core components are consistent with gravitational kinematics for the Hα, [N II], and [S II] lines, while in the [O III] there is evidence for contribution from non-gravitational kinematics. We adopted the wing components as a proxy for the outflow contribution and investigated the outflow kinematics by analysing the correlations between the widths and shifts of the wing components of different lines. For this purpose, we used the subsets in which wing components are detected in both compared lines, and can be fitted independently. We find strong correlations between wing component shifts, as well as between wing component widths of all considered lines, with the exception of the Hβ wing component width. These correlations indicate that outflow dynamics systemically affect all emission lines in the spectrum. However, it reflects with a different strength in their profiles, which is observed as different widths of the wing components. This is investigated by comparison of the mean widths of the wing components in subsets where wing components are present in all lines. The strongest outflow signature is observed in the [O III] lines, which have the broadest wing components; weaker outflow signatures are found in Hα and [N II], and the weakest is found for [S II]. These results imply that the considered lines arise in different parts of an outflowing region.

79 ASTRONOMY AND ASTROPHYSICS↗

ZTF SN Ia DR2 follow-up: Exploring the origin of the Type Ia supernova host galaxy step through Si II velocities

The relation between Type Ia supernovae (SNe Ia) and the stellar masses of their host galaxy is well documented. In particular, Hubble residuals display a distinct luminosity shift based on host mass. This is known as the mass step. This effect is widely used as an additional correction factor in the standardisation of SN Ia luminosities. We investigate the Hubble residuals and the mass step of normal SNe Ia in the context of Si IIλ6355 velocities based on 277 normal SNe Ia that are near their peak in the second data release (DR2) of the Zwicky Transient Facility (ZTF). We divided the sample into high-velocity (HV) and normal-velocity (NV) SNe Ia, separated at 12,000 km s −1 . This produced a sample of 70 HV and 207 NV objects. We then explored potential environment- and/or progenitor-related effects by investigating the Si IIλ6355 velocities with parameters such as the light-curve stretch x 1 , the colour c, and the host galaxy properties. Although we only find a marginal difference between the Hubble residuals of HV and NV SNe Ia, the NV mass step is 0.149 ± 0.024 mag (6.3σ). The HV mass step is smaller, 0.046 ± 0.041 mag (1.1σ), and is consistent with zero. The difference between the NV and HV mass steps is modest, at ∼2.2σ. Moreover, the clearest subtype difference appears for SNe in central regions (d DLR < 1), where NV SNe Ia show a large mass step, whereas HV SNe Ia are consistent with no step, yielding a difference of 3.1–3.6σ between NV and HV SNe Ia. We observe a host-colour step for both subtypes. NV SNe Ia show a step of 0.142 ± 0.024 mag (5.9σ), while HV SNe Ia show a step of 0.158 ± 0.042 mag (3.8σ), where the HV SNe Ia step appears to be larger, but the significance is lower because the sample size is smaller. Overall, the NV and HV colour steps are statistically consistent. HV SNe Ia also show modest (∼2.5–3σ) steps in certain subsets, such as those in outer regions (d DLR > 1), whereas NV SNe display stronger environmental trends. Our results indicate that NV SNe Ia appear to be more environmentally sensitive, particularly in central likely metal-rich and older regions, while HV SNe Ia show weaker and subset-dependent trends. This suggests that applying a universal mass-step correction might introduce biases, and that incorporating refined classifications and/or environment-dependent factors, such as the location within the host, might improve future cosmological analyses beyond the standard x 1 and c cuts.

supernovae: general↗