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At least 163 records · Page 9

Measurement of the longitudinal flow-plane decorrelation using multiplane cumulants in $\sqrt{s_{NN}}$ = 200 GeV Au+Au, Ru+Ru, and Zr+Zr collisions

Measurements of the variation of anisotropic flow-plane angles (𝛹 𝑛 ) with rapidity, commonly known as the flow-plane decorrelation, provide important insights into the initial conditions of the matter produced in heavy-ion collisions. Here, in this paper, using data collected by the STAR experiment, we report the first measurement of the four-plane correlator observable 𝑇 𝑛 ⁡{𝑏⁢𝑎;𝑑⁢𝑐}=⟨⟨sin⁡[𝑛⁢(𝛹$^𝑏_𝑛$ − 𝛹$^𝑎_𝑛$)]⁢sin⁡[𝑛⁢(𝛹$^𝑑_𝑛$ − 𝛹$^𝑐_𝑛$)]⟩⟩, where superscripts 𝑎, 𝑏, 𝑐, and 𝑑 denote sequential pseudorapidity (𝜂) regions with 𝑎 corresponding to the most backward region, 𝑏 and 𝑐 close to mid-rapidity with 𝜂 𝑏 < 0 and 𝜂 𝑐 > 0, and 𝑑 being the most forward. The measurement is performed for the elliptic and triangular flow (i.e.~𝑛 = 2 and 3) in Au+Au and isobar (Ru+Ru, Zr+Zr) collisions at $\sqrt{s_{NN}}$=200~GeV. The goal of calculating the correlation of the flow-plane angle variations from backward to mid-central, and from mid-central to forward regions, is to probe the systematic variation of flow angle over a wide 𝜂 range. In mid-central collisions (10−30% centrality), we find 𝑇 2 ⁡{𝑏⁢𝑎;𝑑⁢𝑐} =−0.004 ±0.001⁢(s⁢t⁢a⁢t) ±0.002⁢(s⁢y⁢s⁢t) independent of the collision system. Such a small value of 𝑇 2 favors a random-walk'' variation of the flow-plane angles, where the rapidity correlation length is smaller than the entire region under study. These measurements provide new information on the decorrelation patterns in the system and offer a quantitative estimate of possible systematic variations in anisotropic flow angles such astwist’’ between forward and backward regions. This opens new opportunities for understanding the three-dimensional structure and the time evolution of the quark-gluon plasma created in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA’s first ground-based Galactic Cosmic Ray Simulator: Enabling a new era in space radiobiology research

With exciting new NASA plans for a sustainable return to the moon, astronauts will once again leave Earth’s protective magnetosphere only to endure higher levels of radiation from galactic cosmic radiation (GCR) and the possibility of a large solar particle event (SPE). Gateway, lunar landers, and surface habitats will be designed to protect crew against SPEs with vehicle optimization, storm shelter concepts, and/or active dosimetry; however, the ever penetrating GCR will continue to pose the most significant health risks especially as lunar missions increase in duration and as NASA sets its aspirations on Mars. The primary risks of concern include carcinogenesis, central nervous system (CNS) effects resulting in potential in-mission cognitive or behavioral impairment and/or late neurological disorders, degenerative tissue effects including circulatory and heart disease, as well as potential immune system decrements impacting multiple aspects of crew health. Characterization and mitigation of these risks requires a significant reduction in the large biological uncertainties of chronic (low-dose rate) heavy-ion exposures and the validation of countermeasures in a relevant space environment. Historically, most research on understanding space radiation-induced health risks has been performed using acute exposures of monoenergetic single-ion beams. However, the space radiation environment consists of a wide variety of ion species over a broad energy range. Using the fast beam switching and controls systems technology recently developed at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory, a new era in radiobiological research is possible. NASA has developed the “GCR Simulator” to generate a spectrum of ion beams that approximates the primary and secondary GCR field experienced at human organ locations within a deep-space vehicle. The majority of the dose is delivered from protons (approximately 65%–75%) and helium ions (approximately 10%–20%) with heavier ions (Z ≥ 3) contributing the remainder. The GCR simulator exposes state-of-the art cellular and animal model systems to 33 sequential beams including 4 proton energies plus degrader, 4 helium energies plus degrader, and the 5 heavy ions of C, O, Si, Ti, and Fe. A polyethylene degrader system is used with the 100 MeV/n H and He beams to provide a nearly continuous distribution of low-energy particles. A 500 mGy exposure, delivering doses from each of the 33 beams, requires approximately 75 minutes. To more closely simulate the low-dose rates found in space, sequential field exposures can be divided into daily fractions over 2 to 6 weeks, with individual beam fractions as low as 0.1 to 0.2 mGy. In the large beam configuration (60 × 60 cm 2 ), 54 special housing cages can accommodate 2 to 3 mice each for an approximately 75 min duration or 15 individually housed rats. On June 15, 2018, the NSRL made a significant achievement by completing the first operational run using the new GCR simulator. This paper discusses NASA’s innovative technology solution for a ground-based GCR simulator at the NSRL to accelerate our understanding and mitigation of health risks faced by astronauts. Ultimately, the GCR simulator will require validation across multiple radiogenic risks, endpoints, doses, and dose rates.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancing Building Energy Efficiency through Advanced Sizing and Dispatch Methods for Energy Storage

Energy storage and electrification of buildings hold great potential for future decarbonization. However, there are several technical and economic barriers that prevent large-scale adoption and integration of energy storage in buildings. These barriers include integration with building control systems, high capital costs, and the necessity to identify and quantify value streams for different stakeholders. To overcome these obstacles, it is crucial to develop advanced sizing and dispatch methods to assist planning and operational decision-making for integrating energy storage in buildings. This work develops simple and flexible optimal sizing and dispatch framework for thermal energy storage (TES) and battery energy storage (BES) systems in large-scale office building. The optimal sizes of TES, BES, as well as other building assets are determined in a joint manner instead of sequentially to avoid sub-optimal solutions. The interaction between the sizing at the planning stage and hourly or sub-hourly dispatch at the operating stage is explicitly modeled. The solution is determined considering both capital costs in optimal sizing and operational benefits in optimal dispatch. Comprehensive assessments are performed using simulation studies to quantify potential energy, economic, and emission benefits by different utility tariffs and climate locations, to improve our understanding of the techno-economic performance of different TES and BES systems, and to identify barriers for adopting energy storage for buildings. Finally, the proposed framework will provide guidance to a broad range of stakeholders to properly design energy storage in buildings and maximizes potential benefits, thereby advancing affordable building energy storage deployment and helping us accelerating the transition towards a cleaner and more equitable energy economy.

Yu, Mingyung↗

Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem

Background: Viruses impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time and their response to strong seasonal changes in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental soil DNA and RNA viruses, focusing especially on bacteriophages, across dynamics’ seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes. Results: We identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of fungal RNA viruses, and a large and unsuspected diversity of positive single-stranded RNA phages ( Leviviricetes ), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active DNA and RNA phages that changed across seasons, consistent with a “seed-bank” viral community structure in which new phage activity, for example, replication and host lysis, is sequentially triggered by changes in environmental conditions. At the population level, we further identified virus-host dynamics matching two existing ecological models: “Kill-The-Winner” which proposes that lytic phages are actively infecting abundant bacteria, and “Piggyback-The-Persistent” which argues that when the host is growing slowly, it is more beneficial to remain in a dormant state. The former was associated with summer months of high and rapid microbial activity, and the latter with winter months of limited and slow host growth. Conclusion: Taken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. As our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry.

54 ENVIRONMENTAL SCIENCES↗

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗

Titanium isotope systematics of refractory inclusions: Echoes of molecular cloud heterogeneity

Calcium-aluminum-rich inclusions (CAIs) are highly refractory objects found in different chondrite groups and represent some of the oldest known solids of the Solar System. As such, CAIs provide key information regarding the conditions prevailing in the solar protoplanetary disk as well as subsequent mixing and transport processes. Many studies have investigated CAIs for their isotopic compositions and reported nucleosynthetic isotope anomalies in numerous elements, which are typically explained by the variable incorporation of isotopically highly anomalous presolar phases. However, with the exception of 54 Cr-enriched nanospinels, the exact presolar phases responsible for the isotopic heterogeneities are yet to be identified. To address this issue, we here present in-situ Ti isotopic analyses obtained on a diverse set of CAIs from various CV3 chondrites. In this work, the in-situ measurements were performed by targeting individual mineral phases of 15 CAIs with laser-ablation mass spectrometry and indicate significant inter- and intra-CAI isotopic heterogeneity in the neutron-rich isotope 50 Ti. This is particularly pronounced for primitive fine-grained CAIs, whereas coarse-grained CAIs, which have been subject to melting, exhibit smaller degrees of Ti isotopic heterogeneity. To further investigate this Ti isotopic heterogeneity, we additionally obtained Ti isotopic compositions of sequential acid leachates from two fine-grained and two coarse-grained CAIs derived from CV3 chondrites. In contrast to potential expectations from the first part of the study, we do not observe any significant intra-CAI Ti isotopic heterogeneity between the different leaching steps. The lack of intra-CAI Ti isotopic heterogeneity in the acid leachate samples of this study likely reflects that the leaching procedure is unable to efficiently separate the carriers of isotopically anomalous Ti in CAIs. By comparing the bulk CAI Ti isotope compositions with Ti isotope data for hibonite-rich objects from the literature, we find that the range of Ti isotope compositions recorded by CAIs from various chondrite groups can be accounted for by the averaging of hibonite grains. In turn, the variable Ti isotope compositions of hibonite grains can be explained by the averaging of isotopically diverse presolar grains present in the Sun’s parental molecular cloud. This effect of averaging is statistically supported by the central limit theorem, and the concept has the potential to be useful for other isotopic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ghost imaging second harmonic generation microscopy

Second harmonic generation (SHG) microscopy is useful for visualizing interfaces and sub-structures within a wide range of materials due to the propensity for SHG to occur in non-centrosymmetric environments. However, since SHG is a nonlinear process generally necessitating small focal sizes for higher peak powers, a raster scanning approach is usually needed to build an SHG image over a significant sample size. While raster scanning is effective, there is a cost in terms of the time needed to acquire the image and, also, some materials cannot withstand the higher optical intensities within the small focal volume. As such, we describe a SHG microscopy approach based on ghost imaging (GI), which enables imaging data to be collected in parallel rather than sequentially as in raster scanning techniques. We experimentally demonstrate the approach and combine GI-SHG with compressive sensing to make further substantial gains in reducing the amount of sampling required for image reconstruction. Furthermore, GI-SHG is shown to have significant advantages for imaging in highly scattering environments, partly because GI is a background-free approach requiring spatial correlations between photons that travel two paths, with one path entirely devoid of sample interaction. This basic property of GI means that only the photons that travel unimpeded through the sample preserve the spatial correlations needed to reconstruct the image, while more scattered photons do not contribute to the overall GI signal. Finally, we compare the image quality and sampling properties of three different reconstruction algorithms used for compressive sensing.

47 OTHER INSTRUMENTATION↗

Above-threshold multiphoton photoemission from noble metal surfaces

Exciting solids with intense femtosecond laser pulses prompts electrons of the interrogated material to respond in a highly nonlinear manner, as is evident in the emission of high-order harmonic radiation and photoelectrons with kinetic energies well above that of the driving photons. Such high-field interactions can be resolved, for example, in above-threshold multiphoton photoemission (ATP) spectroscopy. In this work, we interrogate the nonlinear photoelectric responses of the pristine copper, silver, and gold noble metal surfaces in (111) and (100) crystal orientations in the perturbative regime. Using multiphoton photoemission spectroscopy (mPP) excited by finely tuned optical fields, we characterize enhancement of the mPP and ATP yields from (111) surfaces in selected k||-momentum ranges when the occupied Shockley surface (SS) states are (near-)resonantly coupled by multiphoton transitions to image potential (IP) intermediate states in the excitation process. The ATP signal from the IP states of (111) surfaces is largely defined by their formation through polarization of SS electrons; this observation is contrasted with ATP experiments from the Ag(100) surface, for which the SS becomes an unoccupied resonance and the IP states can only be excited from bands with significantly more bulk character. In addition, based on the optical power and nonlinear order-dependent mPP spectra, we provide evidence for ATP being a one-step, rather than a sequential process, as previously postulated.

74 ATOMIC AND MOLECULAR PHYSICS↗

Simultaneous Discovery of Positive and Negative Interactions Among Rhizosphere Bacteria Using Microwell Recovery Arrays

Understanding microbe-microbe interactions is critical to predict microbiome function and to construct communities for desired outcomes. Investigation of these interactions poses a significant challenge due to the lack of suitable experimental tools available. Here we present the microwell recovery array (MRA), a new technology platform that screens interactions across a microbiome to uncover higher-order strain combinations that inhibit or promote the function of a focal species. One experimental trial generates 10 4 microbial communities that contain the focal species and a distinct random sample of uncharacterized cells from plant rhizosphere. Cells are sequentially recovered from individual wells that display highest or lowest levels of focal species growth using a high-resolution photopolymer extraction system. Interacting species are then identified and putative interactions are validated. Using this approach, we screen the poplar rhizosphere for strains affecting the growth of Pantoea sp. YR343, a plant growth promoting bacteria isolated from Populus deltoides rhizosphere. In one screen, we montiored 3,600 microwells within the array to uncover multiple antagonistic Stenotrophomonas strains and a set of Enterobacter strains that promoted YR343 growth. The later demonstrates the unique ability of the platform to discover multi-membered consortia that generate emergent outcomes, thereby expanding the range of phenotypes that can be characterized from microbiomes. This knowledge will aid in the development of consortia for Populus production, while the platform offers a new approach for screening and discovery of microbial interactions, applicable to any microbiome.

59 BASIC BIOLOGICAL SCIENCES↗

Custom tuning of Rieske oxygenase reactivity

Rieske oxygenases use a Rieske-type [2Fe-2S] cluster and a mononuclear iron center to initiate a range of chemical transformations. However, few details exist regarding how this catalytic scaffold can be predictively tuned to catalyze divergent reactions. Therefore, in this work, using a combination of structural analyses, as well as substrate and rational protein-based engineering campaigns, we elucidate the architectural trends that govern catalytic outcome in the Rieske monooxygenase TsaM. We identify structural features that permit a substrate to be functionalized by TsaM and pinpoint active-site residues that can be targeted to manipulate reactivity. Exploiting these findings allowed for custom tuning of TsaM reactivity: substrates are identified that support divergent TsaM-catalyzed reactions and variants are created that exclusively catalyze dioxygenation or sequential monooxygenation chemistry. Importantly, we further leverage these trends to tune the reactivity of additional monooxygenase and dioxygenase enzymes, and thereby provide strategies to custom tune Rieske oxygenase reaction outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

Z-Sequence: photometric redshift predictions for galaxy clusters with sequential random k-nearest neighbours

ABSTRACT We introduce Z-Sequence, a novel empirical model that utilizes photometric measurements of observed galaxies within a specified search radius to estimate the photometric redshift of galaxy clusters. Z-Sequence itself is composed of a machine learning ensemble based on the k-nearest neighbours algorithm. We implement an automated feature selection strategy that iteratively determines appropriate combinations of filters and colours to minimize photometric redshift prediction error. We intend for Z-Sequence to be a standalone technique but it can be combined with cluster finders that do not intrinsically predict redshift, such as our own DEEP-CEE. In this proof-of-concept study, we train, fine-tune, and test Z-Sequence on publicly available cluster catalogues derived from the Sloan Digital Sky Survey. We determine the photometric redshift prediction error of Z-Sequence via the median value of |Δ$z$|/(1 + $z$) (across a photometric redshift range of 0.05 ≤ $z$ ≤ 0.6) to be ∼0.01 when applying a small search radius. The photometric redshift prediction error for test samples increases by 30–50 per cent when the search radius is enlarged, likely due to line-of-sight interloping galaxies. Eventually, we aim to apply Z-Sequence to upcoming imaging surveys such as the Legacy Survey of Space and Time to provide photometric redshift estimates for large samples of as yet undiscovered and distant clusters.

Chan, Matthew C.↗

Temperature‐Dependent Crystallization in Two‐Step Perovskite Deposition Revealed by In Situ GIWAXS and Machine Learning‐Guided Analysis

The performance and stability of perovskite solar cells are strongly governed by the crystallization behavior of their active layer. In two-step sequential deposition, early-stage film formation plays a decisive role in determining final phase purity and device quality. Guided by a data-driven analysis of nearly 39 000 devices in the FAIR perovskite database, we identified solvent-mediated quenching and thermal processing as key variables affecting power conversion efficiency (PCE), particularly in two-step fabrication. Here, to investigate these effects in real time, we designed and implemented a custom-built, temperature-controlled spin-coating system, enabling precise thermal modulation during precursor deposition. Using this platform, we performed in situ GIWAXS measurements to study the crystallization dynamics of FA 0.5 MA 0.5 PbI 3 films over a temperature range of 30°C–90°C. Our results reveal a non-monotonic relationship between spin-coating temperature and α-phase formation, governed by the interplay between precursor interdiffusion, PbI 2 crystallinity, and δ-phase suppression. The custom thermal control enabled us to isolate and quantify these competing effects during the earliest stages of film formation, providing mechanistic insight into how spin-coating temperature governs both phase purity and kinetic pathways in two-step perovskite systems. Temperature-dependent SEM and photovoltaic device measurements further demonstrate that early-stage crystallization pathways directly translate into differences in morphology, charge-transport continuity, and device performance. These findings inform targeted strategies for optimizing deposition protocols to balance rapid nucleation, phase stability, and device performance.

Saadawy, Ahmed [King Fahd University of Petroleum ↗

Strong, ductile, and hierarchical hetero-lamellar-structured alloys through microstructural inheritance and refinement

The strength−ductility trade-off exists ubiquitously, especially in brittle intermetallic-containing multiple principal element alloys (MPEAs), where the intermetallic phases often induce premature failure leading to severe ductility reduction. Hierarchical heterogeneities represent a promising microstructural solution to achieve simultaneous strength−ductility enhancement. However, it remains fundamentally challenging to tailor hierarchical heterostructures using conventional methods, which often rely on costly and time-consuming processing. Here, we report a multiscale microstructural inheritance and refinement strategy to process “structural hierarchy precursors” in as-cast heterogeneous Al 0.7 CoCrFeNi MPEAs, which lead directly to a hierarchical hetero-lamellar structure (HLS) after simple rolling and annealing. Interestingly, it takes only 10 min of annealing time, two orders of magnitude less than that required to render the state-of-the-art properties during conventional processing of Al 0.7 CoCrFeNi, for us to achieve record-high strength−ductility combinations via the hierarchical HLS design that sequentially stimulates multiple unusual deformation and reinforcement mechanisms. In particular, the HLS-enabled high hetero-deformation-induced (HDI) internal stress triggers profuse <111>-type dislocations on over five independent slip systems in the supposedly brittle intermetallic phase and activates extensive stacking faults (SFs) and nanotwinning in the adjoining soft phase with a rather high SF energy. These unexpected, dynamically reinforcing hetero-deformation mechanisms across multiple length scales facilitate high sustained HDI strain hardening, along with a salient microcrack-mediated extrinsic ductilization effect, suggesting that the proposed microstructural inheritance and refinement strategy provides an efficient, fast, and low-cost approach to overcome the strength−ductility trade-off in a broad range of structural materials.

Science & Technology - Other Topics↗

The Myth of Fungible FTE: A Quantitative Assessment of Matrixed Resource Allocation

Matrix organizations allow scientific facilities to share specialized personnel across projects, operations, maintenance, and strategic initiatives. Nominal staffing allocations, however, may not capture the schedule consequences of fragmented individual commitments, limited access to specialist groups, and intermittent availability of key decision makers. We developed a stochas- tic, daily-time-step simulation of a hypothetical medium-sized accelerator-facility project com- prising sequential phases and parallel tasks. Each task requires role-specific work measured in FTE-days. Ordinary personnel may be unavailable because they contribute concurrently to other institutional activities, while designated key roles have independently specified daily un- availability probabilities. An organization-wide priority factor scales the number of people from each functional group who can effectively contribute to the project. It is interpreted as a composite proxy for project access and workforce fragmentation across competing commit- ments. We examined project completion time as a function of this factor and Project Lead unavailability using 100 Monte Carlo runs per condition. Increasing priority factor from 0.1 to 1.0 reduced median completion time from 1708.5 days (interquartile range 1681.5–1735.25) to 390 days (interquartile range 379–399). At priority factor = 0.1, increasing Project Lead unavailability from 0.5 to 0.9 increased median completion time from 1713.5 days (interquartile range 1691–1733.25) to 4,417 days (interquartile range 4271.75–4550.5). The model quantifies the commonly expected sensitivity of project schedules to fragmented resource commitments and limited coordination availability. Within this model, the results also indicate a possible threshold regime in which small increases in workforce availability yield only modest sched- ule improvements until sufficient capacity becomes accessible, after which project performance improves sharply. With further validation and calibration, this quantitative framework could support resource-allocation decisions during initial project planning and subsequent schedule rebaselining.

Bai, Mei [SLAC National Accelerator Laboratory (SL↗

Swelling characteristics of DNA polymerization gels

The development of biomolecular stimuli-responsive hydrogels is important for biomimetic structures, soft robots, tissue engineering, and drug delivery. DNA polymerization gels are a new class of soft materials composed of polymer gel backbones with DNA duplex crosslinks that can be swollen by sequential strand displacement using hairpin-shaped DNA strands. The extensive swelling can be tuned using physical parameters such as salt concentration and biomolecule design. Previously, DNA polymerization gels have been used to create shape-changing gel automata with a large design space and high programmability. Here we systematically investigate how the swelling response of DNA polymerization gels can be tuned by adjusting the design and concentration of DNA crosslinks in the hydrogels or DNA hairpin triggers, and the ionic strength of the solution in which swelling takes place. Finally, we also explore the effect hydrogel size and shape have on the swelling response. Tuning these variables can alter the swelling rate and extent across a broad range and provide a quantitative connection between biochemical reactions and macroscopic material behaviour.

59 BASIC BIOLOGICAL SCIENCES↗

Relativistic hybrid stars with sequential first-order phase transitions and heavy-baryon envelopes

We compute the mass, radius and tidal deformability of stars containing phase transitions from hadronic to quark phase(s). These quantities are computed for three types of hadronic envelopes: purely nuclear, hyperonic, and Δ-resonance--hyperon admixed matter. We consider either a single first-order phase transition to a quark phase with a maximally stiff equation of state (EOS) or two sequential first-order phase transitions mimicking a transition from hadronic to a quark matter phase followed by a second phase transition to another quark phase. We explore the parameter space which produces low-mass twin and triplet configurations where equal-mass stars have substantially different radii and tidal deformabilities. We demonstrate that while for purely hadronic stiff EOS the obtained maximum mass is inconsistent with the upper limit on this quantity placed by GW170817, the inclusion of the hyperonic and Δ-resonance degrees of freedom, as well as the deconfinement phase transition at sufficiently low density, produces a configuration of stars consistent with this limit. The obtained hybrid star configurations are in the mass range relevant for the interpretation of the GW170817 event. We compare our results for the tidal deformability with the limits inferred from GW170817 showing that the onset of non-nucleonic phases, such as Δ-resonance--hyperon admixed phase and/or the quark phase(s), are favored by this data if the nuclear EOS is stiff. Also, we show that low-mass twins and especially triplets proliferate the number of combinations of possible types of stars that can undergo a merger event, the maximal number being six in the case of triplets. The prospects for uncovering the first-order phase transition(s) to and in quark matter via measurements of tidal deformabilities in merger events are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Electronic Conductivity of Nanoporous Indium Oxide Derived from Sequential Infiltration Synthesis

Sequential infiltration synthesis (SIS) is a vapor phase synthetic method that enables the selective nucleation and growth of metal oxides within polymer volumes. The expanding palette of SIS materials and process designs enables tunability of the resulting material properties. We derive porous indium oxide thin films from the SIS of indium oxide using trimethyl indium and H 2 O 2 in polymethyl methacrylate films and observe the strong effect of SIS and post-deposition processing, which affords 7 orders of magnitude of tunability in electrical resistivity. While as-deposited hybrid nanocomposites show no measurable conductivity, high-temperature treatment in O 2 removes the polymer matrix and creates a porous nanocrystalline In 2 O 3 film with resistivities ranging from 10 3 to 10 5 Ω*cm, with lower resistivity correlated to larger grain sizes. Subsequent annealing in H 2 decreases the resistivity of films to less than 10 –2 Ω*cm. A clear correlation between increasing In 2 O 3 volume fraction, grain size, and carrier mobility is observed, which arises from increased percolation pathways, path length, and contact area in nanocrystalline In 2 O 3 films. Furthermore, this wide tunability demonstrates the importance of understanding growth mechanisms and processing conditions for functional materials development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design, modeling and experimental validation of a micro cantilever beam with an electro-controllable twisting ability

The structure design of micro cantilever beams (MCBs), which has a significant effect on MCBs' controllable actuation range, is usually restricted by the establishment of the inner electric circuit. This paper proposes the design of a micro electro-controllable twisting cantilever beam (METCB). The architecture and the fabrication diagram of the proposed METCB are presented before its features are theoretically and experimentally validated. In detail, the analytical validation includes a sequence of two models: electro-thermal and thermo-mechanical. Through these two models, the thermal distribution along the METCB and the deformation brought by the thermal distribution are investigated, respectively. On the basis of the design and equations, the METCB samples have been manufactured using a planar deposition technique with an e-beam evaporator. Two in-site experiments are then conducted to sequentially figure out the upper voltage limit of the inner electric circuit and the maximum temperature limit of the METCB. Finally, another experiment is carried out to explore the relation between the applied voltage and the relative twisting angle of the METCB sample. Here, the theoretical prediction and the observed experiment result both prove the feasibility of the proposed METCB and its electro-controllable twisting ability.

36 MATERIALS SCIENCE↗