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At least 253 records · Page 14

Ab initio study of the structure and properties of amorphous silicon hydride from accelerated molecular dynamics simulations

This paper presents a large-scale ab initio simulation study of amorphous silicon hydride (a-Si 1-x H x ) with an emphasis on the structure and properties of the material across a range of hydrogen concentration by combining accelerated molecular dynamics (MD) simulations with first-principles density-functional calculations. The accelerated MD scheme relied on classical metadynamics, which enabled the development of 2600+ high-quality structural models of a-Si 1-x H x , with system sizes ranging from 150 to 6,000 atoms and hydrogen concentrations vary from 6 to 20 at. %. The resulting amorphous networks were found to be completely free from any coordination defects and that they all exhibited a pristine band-gap in their electronic spectrum. The microstructural properties of hydrogen distributions were examined with great emphasis on the presence of isolated and clustered environments of hydrogen atoms. The results were compared with a suite of experimental data obtained from x-ray diffraction, infrared spectroscopy, spectroscopic ellipsometry and nuclear magnetic resonance studies.

36 MATERIALS SCIENCE↗

Dynamics of Cation-Induced Conformational Changes in Nanometer-Sized Uranyl Peroxide Clusters

Conformational changes of the pyrophosphate (Pp)-functionalized uranyl peroxide nanocluster [(UO 2 ) 24 (O 2 ) 24 (P 2 O 7 ) 12 ] 48– ({U 24 Pp 12 }), dissolved as a Li/Na salt, can be induced by the titration of alkali cations into solution. The most symmetric conformer of the molecule has idealized octahedral ( O h ) molecular symmetry. One-dimensional 31 P NMR experiments provide direct evidence that both K + and Rb + ions trigger an O h -to- D 4 h conformational change within {U 24 Pp 12 }. Variable-temperature 31 P NMR experiments conducted on partially titrated {U 24 Pp 12 } systems show an effect on the rates; increased activation enthalpy and entropy for the D 4 h -to- O h transition is observed in the presence of Rb + compared to K + . Two-dimensional, exchange spectroscopy 31 P NMR revealed that magnetization transfer links chemically unique Pp bridges that are present in the D 4 h conformation and that this magnetization transfer occurs via a conformational rearrangement mechanism as the bridges interconvert between two symmetries. The interconversion is triggered by the departure and reentry of K (or Rb) cations out of and into the cavity of the cluster. This rearrangement allows Pp bridges to interconvert without the need to break bonds. Cs ions exhibit unique interactions with {U 24 Pp 12 } clusters and cause only minor changes in the solution 31 P NMR signatures, suggesting that O h symmetry is conserved. Single-crystal X-ray diffraction measurements reveal that the mixed Li/Na/Cs salt adopts D 2 h molecular symmetry, implying that while solvated, this cluster is in equilibrium with a more symmetric form. Thus, these results highlight the unusually flexible nature of the actinide-based {U 24 Pp 12 } and its sensitivity to countercations in solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heterometallic Ce IV / V V Oxo Clusters with Adjustable Catalytic Reactivities

Heterometallic Ce IV /M oxo clusters are underexplored yet and can benefit from synergistic properties from combining cerium and other metal cations to produce efficient redox catalysts. Herein, we designed and synthesized a series of new Ce 12 V 6 oxo clusters with different capping ligands: Ce 12 V 6 -SO 4 , Ce 12 V 6 -OTs (OTs: toluenesulfonic acid), and Ce 12 V 6 -NBSA (NBSA: nitrobenzenesulfonic acid). Single crystal X-ray diffraction (SCXRD) for all three structures reveals a Ce 12 V 6 cubane core formulated [Ce 12 (VO) 6 O 24 ] 18+ with cerium on the edges of the cube, vanadyl capping the faces, and sulfate on the corners. While infrared spectroscopy (IR), ultraviolet–visible spectroscopy (UV–vis), electrospray ionization mass spectrometry (ESI-MS), and proton nuclear magnetic resonance ( 1 H NMR) proved the successful coordination of the organic ligands to the Ce 12 V 6 core, liquid phase 51 V NMR and small-angle X-ray scattering (SAXS) confirmed the integrity of the clusters in the organic solutions. Furthermore, functionalization of the Ce 12 V 6 core with organic ligands both provides increased solubility in term of homogeneous application and introduces porosity to the assemblies of Ce 12 V 6 -OTs and Ce 12 V 6 -NBSA in term of heterogeneous application, thus allowing more catalytic sites to be accessible and improving reactivity as compared to the nonporous and less soluble Ce 12 V 6 -SO 4 . Meanwhile, the coordinated ligands also influenced the electronic environment of the catalytic sites, in turn affecting the reactivity of the cluster, which we probed by the selective oxidation of 2-chloroethyl ethyl sulfide (CEES). Furthermore, this work provides a strategy to make full use of the catalytic sites within a class of inorganic sulfate capped clusters via organic ligand introduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PyCCE: A python package for custer correlation expansion simulations of spin qubit dynamics.

PyCCE, an open-source Python library for simulating the dynamics of spin qubits in a spin bath, is presented using the cluster-correlation expansion (CCE) method. PyCCE includes modules to generate realistic spin baths, employing coupling parameters computed from first principles with electronic structure codes, and enables the user to run simulations with either the conventional or generalized CCE method. Three use cases of the Python library are illustrated: the calculation of the Hahn-echo coherence time of the nitrogen-vacancy in diamond; the calculation of the coherence time of the basal divacancy in silicon carbide at avoided crossings; and the calculation for magnetic field orientation-dependent dynamics of a shallow donor in silicon. The complete documentation, downloadable tutorials, and installation instructions are available at https://pycce.readthedocs.io/en/latest/.

coherence↗

Heavy chalcogenide-transition metal clusters as coordination polymer nodes

While metal–oxygen clusters are widely used as secondary building units in the construction of coordination polymers or metal–organic frameworks, multimetallic nodes with heavier chalcogenide atoms (S, Se, and Te) are comparatively untapped. The lower electronegativity of heavy chalcogenides means that transition metal clusters of these elements generally exhibit enhanced coupling, delocalization, and redox-flexibility. Leveraging these features in coordination polymers provides these materials with extraordinary properties in catalysis, conductivity, magnetism, and photoactivity. In this perspective, we summarize common transition metal heavy chalcogenide building blocks including polynuclear metal nodes with organothiolate/selenolate or anionic heavy chalcogenide atoms. Based on recent discoveries, we also outline potential challenges and opportunities for applications in this field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modification of magnetic ground state in Tb 2 Ni 0.90 Si 2.94 by thermal annealing

In this work, we have investigated the thermal annealing effect on the physical properties of an AlB 2 -type ternary intermetallic compound, Tb 2 Ni 0.90 Si 2.94 , that undergoes spin freezing behaviour coexisting with spatially limited antiferromagnetic phase below 9.9 K in as-cast form. Thermal annealing effect is found to result in considerable changes in the magnetic ground state properties of the system. Though only one magnetic transition around 9.9 K is observed for as-cast compound, the annealed sample exhibits two distinct magnetic transitions; one around T N ~ 13.5 K and another around T f ~ 4 K. The magnetization measurements and zero field neutron diffraction study reveal that the high temperature transition is antiferromagnetic type, though of limited correlation length, while the low temperature transition corresponds to spin freezing behaviour. The ac susceptibility and heat capacity studies also confirm the existence of frustrated cluster glass state at lower temperature than the antiferromagnetic ordering temperature. Additionally, ac susceptibility data exhibits signature of an additional peak in the even lower temperature region (at 2.2 K for zero frequency) that tends to shift in opposite direction with frequency in contrast to that observed for conventional glassy transitions. The change in intrinsic local structural disorder of Ni and Si ions associated with annealing has been argued to be responsible for the different magnetic behaviour in as-cast and annealed samples.

36 MATERIALS SCIENCE↗

Microstructure modeling of nuclear structural materials: Recent progress and future directions

Modeling and simulation of microstructures are essential to understand the complex responses and behaviors of nuclear materials in extreme environments. The needs to assess the extended life operation as well as the growing interest in accelerating nuclear materials development and qualification have stimulated the use of high-fidelity multiscale models aided by empirical and ab initio data. This paper reviews the role of various models across different length and time scales in investigating irradiation effects on microstructure evolution and degradation, in particular the embrittlement caused by radiation induced or enhanced formation of nanoscale chemical heterogeneities. The strength and limitations of these models, including classical rate theories, cluster dynamics, phase-field methods, and atomistic models informed by ab initio energies, are discussed with seminal examples. Challenges regarding the lack of thermo-kinetic data and theoretical treatments considering chemical complexities and magnetic excitations, as well as the stabilizing effect by excess point defects in nuclear structural materials are presented, along with potential solutions based on ab initio informed surrogate energy models and statistical sampling by Monte Carlo simulations. Further, the review then highlights the opportunities to leverage the advantages of different methods by establishing hybrid models by shared variables or coupled codes and applications. Finally, the review concludes with forward-looking remarks on how the use of physics-based models can aid the improvement of machine-learning models of property degradation and vice versa.

36 MATERIALS SCIENCE↗

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Effect of Geometry, Spin, and Orbital Optimization in Achieving Accurate, Correlated Results for Iron–Sulfur Cubanes

Iron–sulfur clusters comprise an important functional motif in the catalytic centers of biological systems, capable of enabling important chemical transformations at ambient conditions. This remarkable capability derives from a notoriously complex electronic structure that is characterized by a high density of states that is sensitive to geometric changes. The spectral sensitivity to subtle geometric changes has received little attention from correlated, large active space calculations, owing partly to the exceptional computational complexity for treating these large and correlated systems accurately. Here, to provide insight into this aspect, we report the first Complete Active Space Self Consistent Field (CASSCF) calculations for different geometries of the [Fe(II/III) 4 S 4 (SMe) 4 ] -2 clusters using two complementary, correlated solvers: spin-pure Adaptive Sampling Configuration Interaction (ASCI) and Density Matrix Renormalization Group (DMRG). We find that the previously established picture of a double-exchange driven magnetic structure, with minute energy gaps (<1 mHa) between consecutive spin states, has a weak dependence on the underlying geometry. However, the spin gap between the singlet and the spin state 2S + 1 = 19, corresponding to a maximal number of Fe-d electrons being unpaired and of parallel spin, is strongly geometry dependent, changing by a factor of 3 upon slight deformations that are still within biologically relevant parameters. The CASSCF orbital optimization procedure, using active spaces as large as 86 electrons in 52 orbitals, was found to reduce this gap compared to typical mean-field orbital approaches. Our results show the need for performing large active space calculations to unveil the challenging electronic structure of these complex catalytic centers and should serve as accurate starting points for fully correlated treatments upon inclusion of dynamical correlation outside the active space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Simons Observatory: science goals and forecasts for the enhanced Large Aperture Telescope

We describe updated scientific goals for the wide-field, millimeter-wave survey that will be produced by the Simons Observatory (SO). Significant upgrades to the 6-meter SO Large Aperture Telescope (LAT) are expected to be complete by 2028, and will include a doubled mapping speed with 30,000 new detectors and an automated data reduction pipeline. In addition, a new photovoltaic array will supply most of the observatory's power. The LAT survey will cover about 60% of the sky at a regular observing cadence, with five times the angular resolution and ten times the map depth of the Planck satellite. The science goals are to: (1) determine the physical conditions in the early universe and constrain the existence of new light particles; (2) measure the integrated distribution of mass, electron pressure, and electron momentum in the late-time universe, and, in combination with optical surveys, determine the neutrino mass and the effects of dark energy via tomographic measurements of the growth of structure at redshifts z ≲ 3; (3) measure the distribution of electron density and pressure around galaxy groups and clusters, and calibrate the effects of energy input from galaxy formation on the surrounding environment; (4) produce a sample of more than 30,000 galaxy clusters, and more than 100,000 extragalactic millimeter sources, including regularly sampled AGN light-curves, to study these sources and their emission physics; (5) measure the polarized emission from magnetically aligned dust grains in our Galaxy, to study the properties of dust and the role of magnetic fields in star formation; (6) constrain asteroid regoliths, search for Trans-Neptunian Objects, and either detect or eliminate large portions of the phase space in the search for Planet 9; and (7) provide a powerful new window into the transient universe on time scales of minutes to years, concurrent with observations from the Vera C. Rubin Observatory of overlapping sky.

79 ASTRONOMY AND ASTROPHYSICS↗

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Identification of preferred multimodal ligand‐binding regions on IgG1 F C using nuclear magnetic resonance and molecular dynamics simulations

Abstract In this study, the binding of multimodal chromatographic ligands to the IgG1 F C domain were studied using nuclear magnetic resonance and molecular dynamics simulations. Nuclear magnetic resonance experiments carried out with chromatographic ligands and a perdeuterated 15 N‐labeled F C domain indicated that while single‐mode ion exchange ligands interacted very weakly throughout the F C surface, multimodal ligands containing negatively charged and aromatic moieties interacted with specific clusters of residues with relatively high affinity, forming distinct binding regions on the F C . The multimodal ligand‐binding sites on the F C were concentrated in the hinge region and near the interface of the C H 2 and C H 3 domains. Furthermore, the multimodal binding sites were primarily composed of positively charged, polar, and aliphatic residues in these regions, with histidine residues exhibiting some of the strongest binding affinities with the multimodal ligand. Interestingly, comparison of protein surface property data with ligand interaction sites indicated that the patch analysis on F C corroborated molecular‐level binding information obtained from the nuclear magnetic resonance experiments. Finally, molecular dynamics simulation results were shown to be qualitatively consistent with the nuclear magnetic resonance results and to provide further insights into the binding mechanisms. An important contribution to multimodal ligand‐F C binding in these preferred regions was shown to be electrostatic interactions and π–π stacking of surface‐exposed histidines with the ligands. This combined biophysical and simulation approach has provided a deeper molecular‐level understanding of multimodal ligand–F C interactions and sets the stage for future analyses of even more complex biotherapeutics.

Gudhka, Ronak B.↗

Spin Decoherence in VOPc@graphene Nanoribbon Complexes

Carbon nanoribbons or nanographene qubit arrays can facilitate quantum-to-quantum transduction between light, charge, and spin, making them an excellent testbed for fundamental science in quantum coherent systems and for the construction of higher-level qubit circuits. Here, in this work, we study spin decoherence due to coupling with a surrounding nuclear spin bath of an electronic molecular spin of a vanadyl phthalocyanine (VOPc) molecule integrated onto an armchair-edged graphene nanoribbon (GNR). Density functional theory (DFT) is used to obtain ground-state atomic configurations. Decay of spin coherence in Hahn echo experiments is then simulated using the cluster correlation expansion method with a spin Hamiltonian involving hyperfine and electric field gradient tensors calculated from DFT. We find that the decoherence time T 2 is anisotropic with respect to magnetic field orientation and determined only by the hydrogen nuclear spins on both VOPc and GNR. Large electron spin echo envelope modulation (ESEEM) due to nitrogen and vanadium nuclear spins is present at specific field ranges and can be completely suppressed by tuning the magnetic field. The relation between these field ranges and the hyperfine interactions is analyzed. The effects of interactions with the nuclear quadrupole moments are also studied, validating the applicability and limitations of the spin Hamiltonian when they are disregarded.

Hamiltonians↗

Magneto-structural studies of an unusual [Mn III Mn II Gd III (OR) 4 ] 4– partial cubane from 2,2'-bis- p- t Bu-calix[4]arene

Reaction of 2,2'-bis- p - t Bu-calix[4]arene (H 8 L) with MnCl 2 ·4H 2 O, GdCl 3 ·6H 2 O and 2,6-pyridinedimethanol (H 2 pdm) affords [Mn III Mn II Gd III (H 3 L)(pdmH)(pdm)(MeOH) 2 (dmf)]·3MeCN·dmf ( 3 ·3MeCN·dmf) upon vapour diffusion of MeCN into the basic dmf/MeOH mother liquor. 3 crystallises in the tetragonal space group P 4 1 2 1 2 with the asymmetric unit comprising the entire cluster. The highly unusual core contains a triangular arrangement of Mn III Mn II Gd III ions housed within a [Mn III Mn II Gd III (OR) 4 ] 4– partial cubane. Magnetic susceptibility and magnetisation data reveal best fit parameters J Mn(II)–Mn(III) = +0.415 cm –1 , J Mn(III)–Gd(III) = +0.221 cm –1 , J Mn(II)–Gd(III) = –0.258 cm –1 and D Mn(III) = –4.139 cm –1 . Theoretically derived magnetic exchange interactions, anisotropy parameters, and magneto-structural correlations for 3 are in excellent agreement with the experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces

The objective of this project is to develop, and integrate, high-performance simulation tools capable of predicting plasma-facing component (PFC) operating lifetime and the impact of the evolving surface morphology of tungsten-based PFCs on plasma contamination, including the dynamic recycling of fuel species and tritium retention, in future magnetic fusion devices. Establishing a fundamental physical understanding and developing predictive capabilities of plasma-surface interactions (PSI) requires simultaneously addressing complex and diverse physics occurring over a wide range of length (Angstroms to meters) and time (femtoseconds to years) scales, as well as integrating extensive physical processes across the plasma–surface interface. This requires development of not only detailed physics models and computational strategies at each scale, but also algorithms and methods to couple them effectively in a way that can be robustly validated. Deploying these tools requires the continued development and coupling of leadership-scale computational codes to describe the boundary plasma and the evolving PFC surface, as well as a host of simulations that bridge disparate scales to address complex physical and computational issues at the plasma–surface interface in multi-component materials systems for magnetic fusion energy development beyond ITER.

36 MATERIALS SCIENCE↗

Pressure-induced charge orders and their postulated coupling to magnetism in hexagonal multiferroic LuFe 2 O 4

Hexagonal LuFe 2 O 4 is a promising charge order (CO) driven multiferroic material with high charge and spin-ordering temperatures. The coexisting charge and spin orders on Fe 3+ /Fe 2+ sites result in magnetoelectric behaviors, but the coupling mechanism between the charge and spin orders remains elusive. Here, by tuning external pressure, we reveal three charge-ordered phases with suggested correlation to magnetic orders in LuFe 2 O 4 : (i) a centrosymmetric incommensurate three-dimensional CO with ferrimagnetism, (ii) a non-centrosymmetric incommensurate quasi-two-dimensional CO with ferrimagnetism, and (iii) a centrosymmetric commensurate CO with antiferromagnetism. Experimental in situ single-crystal X-ray diffraction and X-ray magnetic circular dichroism measurements combined with density functional theory calculations suggest that the charge density redistribution caused by pressure-induced compression in the frustrated double-layer [Fe 2 O 4 ] cluster is responsible for the correlated spin-charge phase transitions. The pressure-enhanced effective Coulomb interactions among Fe-Fe bonds drive the frustrated (1/3, 1/3) CO to a less frustrated (1/4, 1/4) CO, which induces the ferrimagnetic to antiferromagnetic transition. Our results not only elucidate the coupling mechanism among charge, spin, and lattice degrees of freedom in LuFe 2 O 4 , but also provide a new way to tune the spin-charge orders in a highly controlled manner.

36 MATERIALS SCIENCE↗

Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit

Significance The high-temperature superconducting cuprates are governed by intertwined striped magnetic and charge orders, in addition to superconductivity. Remarkably similar behavior has also been seen in numerical calculations for the Hubbard model describing the copper–oxygen layers in these materials. Finite-cluster methods typically find that spin- and charge-stripe order dominates, while embedded quantum-cluster methods, which access the thermodynamic limit, often conclude that superconductivity does. Here, we report the observation of fluctuating spin and charge stripes in an embedded cluster calculation for the Hubbard model. This discovery demonstrates that striped states survive in the thermodynamic limit and allows us to study their influence on the model’s superconducting properties, where we find evidence for pair-density-wave correlations intertwined with the stripe correlations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Constraints on MeV dark matter and primordial black holes: Inverse Compton signals at the SKA

Here we investigate the possibilities for probing MeV dark matter (DM) particles and primordial black holes (PBHs) (for masses ~ 10 15 –10 17 g) at the upcoming radio telescope SKA, using photon signals from the Inverse Compton (IC) effect within a galactic halo. Pair-annihilation or decay of MeV DM particles (into e + e - pairs) or Hawking radiation from a population of PBHs generates mildly relativistic e ± which can lead to radio signals through the IC scattering on low energy cosmic microwave background (CMB) photons. We study the ability of SKA to detect such signals coming from nearby ultra-faint dwarf galaxies Segue I and Ursa Major II as well as the globular cluster ω-cen and the Coma cluster. We find that with ~ 100 hours of observation, the SKA improves the Planck constraints on the DM annihilation/decay rate and the PBH abundance for masses in the range ~ 1 to few tens of MeV and above 10 15 to 10 17 g, respectively. Importantly, the SKA limits are independent of the assumed magnetic fields within the galaxies. Previously allowed regions of diffusion parameters of MeV electrons inside a dwarf galaxy that give rise to observable signals at the SKA are also excluded. For objects like dwarf galaxies, predicted SKA constraints depend on both the DM and diffusion parameters. Independent observations in different frequency bands, e.g., radio and γ-ray frequencies, may break this degeneracy and thus enable one to constrain the combined parameter space of DM and diffusion. However, the constraints are independent of diffusion parameters for galaxy clusters such as Coma.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗