Spatially resolved GHz magnetization dynamics of a magnetite nano-particle chain inside a magnetotactic bacterium
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The evolution of cyber-physical infrastructure has made its security more challenging. The last few years have witnessed a convergence of hardware and software segments in various domains, including operational technology (OT) which is responsible for carrying out critical tasks such as monitoring and controlling power grids, nuclear plants, transportation, and emergency services. Both hardware and software encapsulate numerous open source and proprietary subcomponents, making it crucial for end-users to understand the composition of the products they are using. For example, wind turbines incorporate thousands of lines of code (software) used for the turbine's design, planning, operation, and analytics in addition to the numerous hardware subcomponents that construct it. Due to the highly complex nature of software and hardware, knowledge of the components and subcomponents is required to mitigate cyber vulnerabilities and defend against cyberattacks. There has also been a transformation from a traditional linear supply chain into a global, dynamic, diverse, and interconnected system. The digitization of the supply chain makes it easier to find and exploit vulnerabilities. Critical infrastructures (e.g., power grids, oil, natural gas, water, and wastewater) rely on OT to function, and if the OT is compromised, equipment damage and potential interruption of services could result. A significant security measure to protect OT systems from disruption is to develop a supply chain bill of materials (BoM) corresponding to the software and hardware used in OT, along with attestations amongst vendors and asset owners. A supply chain BoM is a proactive way to understand the inherent vulnerabilities in the system and mitigate them in advance of being exploited. BoMs bolster the trust placed in the digital infrastructure and enhance software supply chain security by sustaining the management of component obsolescence and compliance, along with the seclusion of unsafe segments of a specific product. Adopting BoM tools is becoming increasingly important across various government sectors, as evidenced by the recent U.S. executive order on cybersecurity (NIST 2021). This paper aims to classify BoMs based on structure, functionality, component type, and architecture. The work also discusses case studies to further highlight the benefits of BoMs. In addition, it identifies missing pieces in existing BoM implementations so that future research may identify bounds on where it could expect to make improvements and directly enable researchers to identify promising areas for exploration. Further, the authors provide valuable recommendations to tool developers, researchers, and standardizing organizations (policymakers), additionally benefitting critical infrastructure owners and government executives. This aids in paving a path for future work, thereby, providing suggestions to determine a tool for consumers that best suit their needs.
Solid polymer electrolytes are promising in fulfilling the requirements for a stable lithium metal anode toward higher energy and power densities. In this work, we investigate the segmental dynamics, ionic conductivity, and crystallinity of a polymer electrolyte consisting of poly(ethylene oxide) (PEO) and lithium triflate salt, in the semi-crystalline state. Using quasi-elastic neutron scattering, the segmental dynamics of PEO chains confined between the crystalline lamellae is quantified, using Cole–Cole analysis. We show that the structural relaxation time, τ 0 , of PEO equilibrated near room temperature is six-fold longer than the same sample that had just cooled down to room temperature. This corresponds to a three-fold smaller ionic conductivity in the equilibrated condition. This work reveals that the segmental dynamics of semi-crystalline polymer electrolytes is very sensitive to thermal history. We demonstrate that quasi-elastic neutron scattering can be used to characterize the ion transport and segmental dynamics in the semi-crystalline state.
In polymer nanoparticle composites (PNCs) with attractive interactions between nanoparticles (NPs) and polymers, a bound layer of the polymer forms on the NP surface, with significant effects on the macroscopic properties of the PNCs. The adsorption and wetting behaviors of polymer solutions in the presence of a solid surface are critical to the fabrication process of PNCs. In this study, we use both classical density functional theory (cDFT) and molecular dynamics (MD) simulations to study dilute and semi-dilute solutions of short polymer chains near a solid surface. Using cDFT, we calculate the equilibrium properties of polymer solutions near a flat surface while varying the solvent quality, surface–fluid interactions, and the polymer chain lengths to investigate their effects on the polymer adsorption and wetting transitions. Using MD simulations, we simulate polymer solutions near solid surfaces with three different curvatures (a flat surface and NPs with two radii) to study the static conformation of the polymer bound layer near the surface and the dynamic chain adsorption process. Additionally, we find that the bulk polymer concentration at which the wetting transition in the poor solvent system occurs is not affected by the difference in surface–fluid interactions; however, a threshold value of surface–fluid interaction is needed to observe the wetting transition. We also find that with good solvent, increasing the chain length or the difference in the surface–polymer interaction relative to the surface–solvent interaction increases the surface coverage of polymer segments and independent chains for all surface curvatures. Finally, we demonstrate that the polymer segmental adsorption times are heavily influenced only by the surface–fluid interactions, although polymers desorb more quickly from highly curved surfaces.
Artificial Spin Ice (ASI), consisting of a two dimensional array of nanoscale magnetic elements, provides a fascinating opportunity to observe the physics of out-of-equilibrium systems. Initial studies concentrated on the static, frozen state, whilst more recent studies have accessed the out-of-equilibrium dynamic, fluctuating state. This opens up exciting possibilities such as the observation of systems exploring their energy landscape through monopole quasiparticle creation, potentially leading to ASI magnetricity, and to directly observe unconventional phase transitions. In this work we have measured and analysed the magnetic relaxation of thermally active ASI systems by means of SQUID magnetometry. We have investigated the effect of the interaction strength on the magnetization dynamics at different temperatures in the range where the nanomagnets are thermally active. We have observed that they follow an Arrhenius-type Néel-Brown behaviour. An unexpected negative correlation of the average blocking temperature with the interaction strength is also observed, which is supported by Monte Carlo simulations. The magnetization relaxation measurements show faster relaxation for more strongly coupled nanoelements with similar dimensions. The analysis of the stretching exponents obtained from the measurements suggest 1-D chain-like magnetization dynamics. This indicates that the nature of the interactions between nanoelements lowers the dimensionality of the ASI from 2-D to 1-D. Finally, we present a way to quantify the effective interaction energy of a square ASI system, and compare it to the interaction energy computed with micromagnetic simulations.
Currently, one of the key challenges preventing the wide commercialization of polymer-based solid-state batteries is achieving high-rate capabilities. This work unravels chain structure and segmental dynamics in a polymer-based composite cathode consisting of LiFePO 4 (LFP), carbon, and poly(ethylene oxide) (PEO) with lithium bis(trifluoromethanesulfonyl)imide. Small-angle neutron scattering (SANS) data reveal that PEO chains are adsorbed on the surface of LFP particles during slurry processing to make the composite electrode. The strong interaction between LFP and PEO chains leads to greatly reduced segmental dynamics of PEO, as discovered by quasi-elastic neutron scattering (QENS). The reduced segmental dynamics results in 70% decreased Li + mobility of the polymer electrolyte in the composite cathode. The combined SANS and QENS study indicates that one of the key bottlenecks that limits the rate performance of PEO-based polymer batteries originates from molecular interactions within the cathode.
Shape memory polymers are promising materials in many emerging applications due to their large extensibility and excellent shape recovery. However, practical application of these polymers is limited by their poor energy densities (up to ~1 MJ/m 3 ). Here, we report an approach to achieve a high energy density, one-way shape memory polymer based on the formation of strain-induced supramolecular nanostructures. As polymer chains align during strain, strong directional dynamic bonds form, creating stable supramolecular nanostructures and trapping stretched chains in a highly elongated state. Upon heating, the dynamic bonds break, and stretched chains contract to their initial disordered state. This mechanism stores large amounts of entropic energy (as high as 19.6 MJ/m 3 or 17.9 J/g), almost six times higher than the best previously reported shape memory polymers while maintaining near 100% shape recovery and fixity. The reported phenomenon of strain-induced supramolecular structures offers a new approach toward achieving high energy density shape memory polymers.
Compatibility between polymers with different glass transition temperatures controls the thermomechanical properties of blends. This work explores the segmental dynamics of poly(methyl acrylate) (PMA) chains when they are blended with polymers of different rigidities and miscibility. Inspired by the intriguing dynamic asymmetry of chains within the interfacial layer of nanoparticles, this study aims to understand dynamic heterogeneity in dynamically asymmetric blends of PMA/poly(methyl methacrylate) (PMMA), PMA/polystyrene (PS), and PMA/poly(ethylene oxide) (PEO) using the differential scanning calorimetry (DSC) and quasi-elastic neutron scattering (QENS) measurements below and above the glass transition temperature of PMMA or PS. Further, results revealed that the segmental jump distance of PMA increased on blending due to volume enhancement. The reduced effective diffusivity of PMA in PMMA is attributed to PMMA's enhanced flexibility (lower characteristic ratio, C ∞ ) and superior interaction (lower ) when compared with the PS environment. The results demonstrate that the chain rigidity and miscibility affect the free volume, interchain cooperativity, and segmental dynamics in dynamically asymmetric blends.
Flavodoxin (Fld) is a small FMN containing protein that is involved in single electron transfer. The long‐chain flavodoxin in Rhodopseudomonas palustris bacteria replaces ferredoxin as a low‐potential electron carrier when iron is scarce. Thus it is proposed to interact with the bifurcating electron transfer flavoprotein (ETF) that yields low‐potential electrons. A surface loop on Fld interacts with another of Fld's partner proteins, so we hypothesize that it also mediates Fld's interaction with ETF. To monitor interactions with ETF directly and investigate dynamics in this loop, we are using 19 F NMR in solution. 19 F is hyperresponsive to changes in its chemical environment with a chemical shift range of >300 ppm. To provide a static reference point and assess structural heterogeneity, we are also exploiting X‐ray crystallography. In this study we selectively fluorinated the five tyrosine residues in Fld. We obtained resonance assignments from 19 F spectra of Fld variants in which individual tyrosine residues have been replaced. We obtain well resolved signals for each residue, but the resonances' linewidths indicate dynamics that affects some resonances more than others. Y90 residue displays two resonances demonstrating two different conformations that interconvert slowly on an NMR time scale. Meanwhile the crystal structure solved at 2.1Å resolution reveals two molecules per asymmetric unit providing two perspectives on the details of the structure. The crystal symmetry is monoclinic in contrast to most of the other Flds, which are orthorhombic. Interestingly, the long loop bearing Y121 and Y123 is not well resolved in chain B of the crystal structure, and the NMR line of Y123 is exceptionally broad, both indicating that the loop is dynamic and capable of altering its conformation to accomodate binding to a partner protein. Future directions include monitoring the changes in the 19 F NMR of the Fld when titrated with the partner protein, temperature dependence of the NMR spectrum and relaxation studies to evaluate time scales of motions.
Self-organization of dust grains into stable filamentary dust structures (or “chains”) largely depends on dynamic interactions between individual charged dust grains and complex electric potential arising from the distribution of charges within a local plasma environment. Recent studies have shown that the positive column of the gas discharge plasma in the Plasmakristall-4 (PK-4) experiment at the International Space Station supports the presence of fast-moving ionization waves, which lead to variations of plasma parameters by up to an order of magnitude from the average background values. The highly variable environment resulting from ionization waves may have interesting implications for the dynamics and self-organization of dust particles, particularly concerning the formation and stability of dust chains. Here, we investigate the electric potential surrounding dust chains in the PK-4 experiment by employing a molecular dynamics model of the dust and ions with boundary conditions supplied by a particle-in-cell with Monte Carlo collision simulation of the ionization waves. The model is used to examine the effects of the plasma conditions within different regions of the ionization wave and compare the resulting dust structure to that obtained by employing the time-averaged plasma conditions. Here, the comparison between simulated dust chains and experimental data from the PK-4 experiment shows that the time-averaged plasma conditions do not accurately reproduce observed results for dust behavior, indicating that more careful treatment of plasma conditions in the presence of ionization waves is required. It is further shown that commonly used analytic forms of the electric potential do not accurately describe the electric potential near charged dust grains under these plasma conditions.
A small number of associating groups incorporated onto a polymer backbone have dramatic effects on the mobility and viscoelastic response of the macromolecules in melts. These associating groups assemble, driving the formation of clusters, whose lifetime affects the properties of the polymers. In this study, we probe the effects of the interaction strength on the structure and dynamics of two topologies, linear and star polymer melts, and further investigate blends of associative and non-associating polymers using molecular dynamics simulations. Polymer chains of approximately one entanglement length are described by a bead–spring model, and the associating groups are incorporated in the form of interacting beads with an interaction strength between them that is varied from 1 to 20 k B T. We find that, for all melts and blends, interaction of a few k B T between the associating groups drives cluster formation, where the size of the clusters increases with increasing interaction strength. These clusters act as physical crosslinkers, which slow the chain mobility. Blends of chains with and without associating groups macroscopically phase separate for interaction strength between the associating groups of a few k B T and above. For weakly interacting associating groups, the static structure function S(q) is well fit by functional form predicted by the random phase approximation where a clear deviation occurs as phase segregation takes place, providing a quantitative assessment of phase segregation.
Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., –CH 3 , –CH 2 R, –CHRR', and –CRR'R") are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.
The kinetics of intramolecular-contact formation between remote functional groups in peptides with restricted conformational flexibility were examined using designed peptides with variable-length proline bridges. As probes for this motion, free radicals were produced using the • OH-induced oxidation at the C-terminal methionine residue of γ-Glu-(Pro) n -Met peptides ( n = 0–3). The progress of the radicals’ motion along the proline bridges was monitored as the radicals underwent reactions along the peptides’ backbones. Of particular interest was the reaction between the sulfur atom located in the side chain of the oxidized Met residue and the unprotonated amino group of the glutamic acid moiety. Interactions between them were probed by the radiation-chemical yields (expressed as G values) of the formation of C-centered, α-aminoalkyl radicals (αN) on the Glu residue. These radicals were monitored directly or via their reaction with p -nitroacetophenone (PNAP) to generate the optically detected PNAP •– radical anions. The yields of these αN radicals were found to be linearly dependent on the number of Pro residues. A constant decrease by 0.09 μM J –1 per spacing Pro residue of the radiation-chemical yields of G (αN) was observed. Previous reports support the conclusion that the αN radicals in these cases would have to result from (S$\therefore$N) + -bonded cyclic radical cations that arose as a result from direct contact between the ends of the peptides. Furthermore, by analogy with the rate constants for the formation of intramolecularly (S$\therefore$S) + -bonded radical cations in Met-(Pro) n -Met peptides ( J. Phys. Chem. B 2016 , 120 , 9732), the rate constants for the formation of intramolecularly (S$\therefore$N) + -bonded radical cations are activated to the same extent for all of the γ-Glu-(Pro) n -Met peptides. Thus, the continuous decrease of G (αN) with the number of Pro residues (from 0 to 3) suggests that the formation of a contact between the S-atom in the C-terminal Met residue and the N-atom of a deprotonated N-terminal amino group of Glu is controlled in peptides with 0 to 3 Pro residues by the relative diffusion of the S •+ and unoxidized N-atom. The overall rate constants of cyclization to form the (S$\therefore$N)-bonded radical cations were estimated to be 3.8 × 10 6 , 1.8 × 10 6 , and 8.1 × 10 5 s –1 for peptides with n = 0, 1, and 2 Pro residues, respectively. If activation is the same for all of the peptides, then these rate constants are a direct indication for the end-to-end dynamics along the chain.
Particle fracture has a significant influence on the engineering behavior of granular materials. However, the combined influence of the initial fabric and wetting on particle fracture and force chain evolution in granular materials, particularly in sands, remains insufficiently explored in the current literature. Here, in this paper, one-dimensional (1D) confined compression experiments were conducted on dry and wet specimens, and particle-level fracture was captured using three-dimensional (3D) in-situ Synchrotron Micro-Computed Tomography (SMT). A quantitative assessment of particle fracture revealed that wet specimens, which have disturbed fabric, exhibited a higher fracture percentage in comparison to dry specimens. Complementary 3D finite element (FE) simulations were performed using dry and wet (only solid fabric was considered and the influence of pore water is not considered) sand assemblies to assess interparticle contact forces and particle-scale stress distributions within the specimens. Force chain analysis was subsequently conducted, encompassing quantification of interparticle forces, characterization of force network structures, and monitoring the dynamic evolution of force chains under different strain levels. The results show that the specimens with disturbed fabric led to a more dynamic and less persistent force network, more fabric instability, and thus more reorganization of force chain structures. In addition, the frequent rearrangement of the force network in the presence of water (with reduced inter-particle contact friction) likely exacerbates localized stress concentrations, promoting failure in previously unengaged or weakly connected particles. The results reported in this paper offer a new insight into how the initial fabric and wetting cause different fracture behavior. The findings can also pave the way for more in-depth future investigations into the mechanics governing particle fracture in granular assemblies.
Abstract Relaxor ferroelectric polymers exhibiting a giant electrocaloric effect (ECE) can potentially be used to create next‐generation solid‐state coolers. Under an electric field, poly(vinylidene fluoride‐trifluoroethylene‐chlorofluoroethylene) terpolymer goes through a large dipolar entropy change producing a high adiabatic temperature change (Δ T ECE ). This work resolves the molecular origins of the large entropy change behind the electric field‐induced dipole switching. A Fourier transform infrared spectroscopy equipped with a high voltage source is used to operandoly observe the characteristic molecular vibrational modes. A short‐range trans (T) conformation of the CF 2 ‐CH 2 dyads interrupted by a gauche (G) conformation, e.g., TTTG in the terpolymer chain, undergoes a dynamic transformation that leads to a corresponding Δ T ECE whenever an electric field is applied. The molecular dynamics simulation also proves that the energy barrier that the transformation from TTTGs into a long T sequence overcomes is smaller than that for all other conformations. A mixed solvent system is used to obtain T3G‐enriched terpolymer films exhibiting a 4.02 K Δ T ECE at 60 MV m −1 and these films are employed to manufacture a 2‐layer‐cascaded cooling device that achieves a 6.7 K temperature lift, the highest reported value for a 2‐layer cascaded device made of fluoropolymers.
Single-molecule stretching experiments are widely utilized within the fields of physics and chemistry to characterize the mechanics of individual bonds or molecules, as well as chemical reactions. Analytic relations describing these experiments are valuable, and these relations can be obtained through the statistical thermodynamics of idealized model systems representing the experiments. Since the specific thermodynamic ensembles manifested by the experiments affect the outcome, primarily for small molecules, the stretching device must be included in the idealized model system. Though the model for the stretched molecule might be exactly solvable, including the device in the model often prevents analytic solutions. In the limit of large or small device stiffness, the isometric or isotensional ensembles can provide effective approximations, but the device effects are missing. Here a dual set of asymptotically correct statistical thermodynamic theories are applied to develop accurate approximations for the full model system that includes both the molecule and the device. In conclusion, the asymptotic theories are first demonstrated to be accurate using the freely jointed chain model and then using molecular dynamics calculations of a single polyethylene chain.
A phenomenological theory is formulated for chemically quenched binary interpenetrating polymer networks (IPNs), considering both simultaneously crosslinked networks and sequentially crosslinked networks, as well as pseudointerpenetrating networks (where only one component is crosslinked and the other is a linear polymer). The construction of free energy functionals for homogeneous weakly crosslinked IPNs and pseudo-IPNs and their spinodal curves and critical points of unmixing is described. These free energy functionals are augmented with gradient energy terms in order to consider effects due to spatially varying small inhomogeneities in the network chain concentration. The dynamic response and the initial spinodal decomposition of IPNs are discussed.
For several years individual DNA molecules have been observed and photographed during agarose gel electrophoresis. The DNA molecule is clearly the largest molecule known. Nevertheless, the largest molecule is still too small to be seen using a microscope. A technique developed by Morikawa and Yanagida has made it possible to visualize individual DNA molecules. When these long molecules are labeled with appropriate fluorescence dyes and observed under a fluorescence microscope, although it is not possible to directly visualize the local ultrastructure of the molecules, yet because they are long light emitting chains, their microscopic dynamical behavior can be observed. This visualization works in the same principle that enables one to observe a star through a telescope because it emits light against a dark background. The dynamics of individual DNA molecules migrating through agarose matrix during electrophoresis have been described by Smith et al. (1989), Schwartz and Koval (1989), and Bustamante et al. (1990). DNA molecules during agarose gel electrophoresis advance lengthwise thorough the gel in an extended configuration. They display an extension-contraction motion and tend to bunch up in their leading ends as the 'heads' find new pores through the gel. From time to time they get hooked on obstacles in the gel to form U-shaped configurations before they resume their linear configuration.