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At least 343 records · Page 19

Flexible organic integrated electronics for self-powered multiplexed ocular monitoring

Smart contact lens has drawn extensive research interests due to the noninvasive real-time detection of the human body to provide biomedical information for health management. However, it has been difficult to accurately measure the physiological signals in tears, and the use of external power source has also hindered the future applications. Here, we demonstrated an organic electrochemical transistor based multiplexed sensors self-powered by the organic solar cells (OSCs). The integrated device was fabricated via simple process including solution blade-coating and thermal evaporation. OSCs were optimized to provide optimal operation voltage for the sensors that exhibit semilog-linear response to the glucose and calcium ions in tear fluids without any peripheral circuits. The sensing signals can be transmitted to the laptop wirelessly through a near filed communication unit. This integrated self-powered multiplexed sensing device will provide real-time monitoring of the biomarkers in tears, prospected to be installed on the smart contact lens for the early detection and diagnosis of diabetes.

36 MATERIALS SCIENCE↗

Engineered Living Materials For Sustainability

Recent advances in synthetic biology and materials science have given rise to a new form of materials, namely engineered living materials (ELMs), which are composed of living matter or cell communities embedded in self-regenerating matrices of their own or artificial scaffolds. Like natural materials such as bone, wood, and skin, ELMs, which possess the functional capabilities of living organisms, can grow, self-organize, and self-repair when needed. They also spontaneously perform programmed biological functions upon sensing external cues. Currently, ELMs show promise for green energy production, bioremediation, disease treatment, and fabricating advanced smart materials. This review first introduces the dynamic features of natural living systems and their potential for developing novel materials. We then summarize the recent research progress on living materials and emerging design strategies from both synthetic biology and materials science perspectives. Lastly, we discuss the positive impacts of living materials on promoting sustainability and key future research directions.

36 MATERIALS SCIENCE↗

Self-sorting in supramolecular assemblies

Supramolecular self-assembly enables living organisms to form highly functional hierarchical structures with individual components self-organized across multiple length scales. This has inspired work on multicomponent supramolecular materials to understand factors behind co-assembly versus self-sorting of molecules. We report here on a supramolecular system comprised of negatively charged peptide amphiphile (PA) molecules, in which only a tiny fraction of the molecules (0.7 mol%) were covalently conjugated to one of two different fluorophores, half to fluorescein isothiocyanate (FTIC) and the other half to tetramethylrhodamine (TAMRA). Confocal microscopy of the system revealed self-sorting of the two different fluorescent PA molecules, where TAMRA PA is concentrated in micron-scale domains while FITC PA remains dispersed throughout the sample. From Förster resonance energy transfer and fluorescence recovery experiments, we conclude that conjugation of the negatively charged FITC to PA significantly disrupts its co-assembly with the 99.3 mol% of unlabeled molecules, which are responsible for formation of micron-scale domains. Conversely, conjugation of the zwitterionic TAMRA causes no such disruption. Interestingly, this dissimilar behavior between FITC and TAMRA PA causes them to self-sort at large length scales in the supramolecular system, mediated not by specific interactions among the individual fluorophores but instead by their different propensities to co-assemble with the majority component. We also found that greater ionic strength in the aqueous environment of the system promotes mixing by lowering the electrostatic barriers involved in self-sorting. Furthermore, our results demonstrate great thermodynamic subtlety in the driving forces that mediate self-sorting versus co-assembly in supramolecular peptide assemblies.

36 MATERIALS SCIENCE↗

Multi-scale organization in communicating active matter

The emergence of collective motion among interacting, self-propelled agents is a central paradigm in non-equilibrium physics. Examples of such active matter range from swimming bacteria and cytoskeletal motility assays to synthetic self-propelled colloids and swarming microrobots. Remarkably, the aggregation capabilities of many of these systems rely on a theme as fundamental as it is ubiquitous in nature: communication. Despite its eminent importance, the role of communication in the collective organization of active systems is not yet fully understood. Here we report on the multi-scale self-organization of interacting self-propelled agents that locally process information transmitted by chemical signals. We show that this communication capacity dramatically expands their ability to form complex structures, allowing them to self-organize through a series of collective dynamical states at multiple hierarchical levels. Our findings provide insights into the role of self-sustained signal processing for self-organization in biological systems and open routes to applications using chemically driven colloids or microrobots.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of Nanoparticle Size and Surface Chemistry on Peptoid Self-Assembly

Self-assembled organic nanomaterials can be generated by bottom-up assembly pathways where the structure is controlled by the organic sequence and altered using pH, temperature, and solvation. In contrast, self-assembled structures based on inorganic nanoparticles typically rely on physical packing and drying effects to achieve uniform superlattices. By combining these two chemistries to access inorganic–organic nanostructures, we aim to understand the key factors that govern the assembly pathway and structural outcomes in hybrid systems. In this work, we outline two assembly regimes between quantum dots (QDs) and reversibly binding peptoids. These regimes can be accessed by changing the solubility and size of the hybrid (peptoid-QD) monomer unit. The hybrid monomers are prepared via ligand exchange and assembled, and the resulting assemblies are studied using ex-situ transmission electron microscopy as a function of assembly time. In aqueous conditions, QDs were found to stabilize certain morphologies of peptoid intermediates and generate a final product consisting of multilayers of small peptoid sheets linked by QDs. The QDs were also seen to facilitate or inhibit assembly in organic solvents based on the relative hydrophobicity of the surface ligands, which ultimately dictated the solubility of the hybrid monomer unit. Increasing the size of the QDs led to large hybrid sheets with regions of highly ordered square-packed QDs. A second, smaller QD species can also be integrated to create binary hybrid lattices. Furthermore, these results create a set of design principles for controlling the structure and structural evolution of hybrid peptoid-QD assemblies and contribute to the predictive synthesis of complex hybrid matter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-consistent dispersal puts tight constraints on the spatiotemporal organization of species-rich metacommunities

Dispersal can be critical to the maintenance of ecosystems as it allows local communities to be recolonized after extinction. However, it remains unclear whether the extinction-mitigating effect of dispersal persists when the number of competing species is large. Based on a spatially explicit mathematical description of metacommunities, we show that when many species coexist, each species operates near its extinction threshold, barely surviving due to dispersal. This has general consequences for spatiotemporal abundance patterns. For short-range dispersal, species organize into fractal spatiotemporal extinction patterns characteristic of a directed percolation phase transition. As species approach their extinction threshold, biodiversity is very sensitive to perturbation, suggesting that dispersal within a metacommunity puts tight constraints on the robustness and evolution of species-rich metacommunities. Biodiversity is often attributed to a dynamic equilibrium between the immigration and extinction of species. This equilibrium forms a common basis for studying ecosystem assembly from a static reservoir of migrants—the mainland. Yet, natural ecosystems often consist of many coupled communities (i.e., metacommunities), and migration occurs between these communities. The pool of migrants then depends on what is sustained in the ecosystem, which, in turn, depends on the dynamic migrant pool. This chicken-and-egg problem of survival and dispersal is poorly understood in communities of many competing species, except for the neutral case—the “unified neutral theory of biodiversity.” Employing spatiotemporal simulations and mean-field analyses, we show that self-consistent dispersal puts rather tight constraints on the dynamic migration–extinction equilibrium. When the number of species is large, species are pushed to the edge of their global extinction, even when competition is weak. As a consequence, the overall diversity is highly sensitive to perturbations in demographic parameters, including growth and dispersal rates. When dispersal is short range, the resulting spatiotemporal abundance patterns follow broad scale-free distributions that correspond to a directed percolation phase transition. The qualitative agreement of our results for short-range and long-range dispersal suggests that this self-organization process is a general property of species-rich metacommunities. Our study shows that self-sustaining metacommunities are highly sensitive to environmental change and provides insights into how biodiversity can be rescued and maintained.

54 ENVIRONMENTAL SCIENCES↗

The Fermi–Löwdin self-interaction correction for ionization energies of organic molecules

(Semi)-local density functional approximations (DFAs) suffer from self-interaction error (SIE). When the first ionization energy (IE) is computed as the negative of the highest occupied orbital (HO) eigenvalue, DFAs notoriously underestimate them compared to quasi-particle calculations. Here, the inaccuracy for the HO is attributed to SIE inherent in DFAs. We assessed the IE based on Perdew-Zunger self-interaction correction on 14 small to moderate-sized organic molecules relevant in organic electronics and polymer donor materials. Though self-interaction corrected DFAs were found to significantly improve the IE relative to the uncorrected DFAs, they overestimate. However, when the self-interaction correction is interiorly scaled using a function of the iso-orbital indicator zs , only the regions where SIE is significant get a correction. We discuss these approaches and show how these methods significantly improve the description of the HO eigenvalue for the organic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solvent-Free Self-Assembly for Scalable Preparation of Highly Crystalline Mesoporous Metal Oxides

Mesoporous metal oxides (MMOs) have been demonstrated great potential in various applications. Up to now, the direct synthesis of MMOs is still limited to the solvent induced inorganic-organic self-assembly process. In this work, we develop a facile, general, and high throughput solvent-free self-assembly strategy to synthesize a series of MMOs including single-component MMOs and multi-component MMOs (e.g., doped MMOs, composite MMOs, and polymetallic oxide) with high crystallinity and remarkable porous properties by grinding and heating raw materials. Compared with the traditional solution self-assembly process, the avoidance of solvents in this method not only greatly increases the yield of target products and synthesis efficiency, but also reduces the environmental pollution and the consumption of cost and energy. We believe the presented approach will pave a new avenue for scalable production of advanced mesoporous materials for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Random Close Packing as a Dynamical Phase Transition

Sphere packing is an ancient problem. The densest packing is known to be a face-centered cubic (FCC) crystal, with space-filling fraction Φ FCC = π / √ 18 ≈ 0.74 . The densest “random packing,” random close packing (RCP), is yet ill defined, although many experiments and simulations agree on a value Φ RCP ≈ 0.64 . We introduce a simple absorbing-state model, biased random organization (BRO), which exhibits a Manna class dynamical phase transition between absorbing and active states that has as its densest critical point Φ cmax ≈ 0.64 ≈ Φ RCP and, like other Manna class models, is hyperuniform at criticality. The configurations we obtain from BRO appear to be structurally identical to RCP configurations from other protocols. This leads us to conjecture that the highest-density absorbing state for an isotropic biased random organization model produces an ensemble of configurations that characterizes the state conventionally known as RCP.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Geothermal Entrepreneurship Organization (GEO) Accelerating Technology Transfer, Testing and Adoption of Cutting-edge Extreme Environment Drilling

The Geothermal Entrepreneurship Organization launched in 2019 with the goal of building a geothermal innovation ecosystem at the University of Texas at Austin (UT Austin), and in the State of Texas at large. The theses underlying the work of GEO were 1) that with targeted advocacy, recruitment, organization, and coalition building, research institutions with legacy excellence in petroleum and geosystems engineering could become engines of geothermal innovation, research and development; 2) that startups were the appropriate vehicle to speed these innovations from the lab into the field, and building a geothermal startup ecosystem in Texas would not only advance next generation geothermal concepts into the field, but also help spur oil and gas engagement in the space, and 3) that with targeted engagement, education, and recruitment across stakeholders in the oil and gas industry and the State of Texas generally, the oil and gas industry, and other legacy oil and gas entities in the State could become sources of large scale deployment of geothermal energy. The overall goal was to create a ‘snowball’ effect, where targeted impactful actions would catalyze self-sustaining, organic growth of a new geothermal ecosystem in the State of Texas. That goal was achieved through GEO’s work. To test its theses, GEO began work by interviewing and recruiting UT Austin faculty and alumni into geothermal. At the beginning of the GEO project, there was no geothermal activity ongoing within the UT Austin Petroleum and Geosystems Engineering Department, the Bureau of Economic Geology, or the Jackson School of Geoscience, and many faculty approached had not before considered how their skillsets might apply in the space. By the end of the project period, three major research consortia focused on geothermal were launched as a result of GEO’s work, one at the Bureau of Economic Geology, one within the Petroleum and Geosystems Engineering Department, and another organized by GEO across six research institutions across the State of Texas, called the Texas Geothermal Institute. Geothermal curricula was launched at UT Austin, and UT Austin began attracting new geothermal enthusiasts into its faculty, including Dr. Silviu Livescu, former Chief Scientist of Baker Hughes. Startups recruited and mentored by GEO launched, raised funding, and deployed (or are currently deploying) their concepts in the field. By the end of the project period, the GEO concept expanded to faculty beyond UT Austin to other institutions, like Texas A&M, the University of Houston, and Rice University, and geothermal engagement began at those institutions as well. Multiple faculty members and alumni across these institutions launched geothermal startup companies, launched geothermal research consortia, and/or began teaching geothermal courses. In 2020, GEO launched what was to become the largest geothermal conference in the world by its second year, ‘PIVOT – From Hydrocarbons to Heat’, and the resulting momentum catalyzed the Society of Petroleum Engineers to launch a geothermal technical section, drove more startups to launch out of the ecosystem, and drove actors in the State of Texas, NGOs, and stakeholders globally to become engaged. Riding this momentum, the Texas Geothermal Energy Alliance was launched, the first ever industry association dedicated to advancing geothermal energy in the State of Texas. The Texas geothermal ecosystem after only two years of building and support is now robust, quickly growing, and self-sustaining. By 2021, the Texas geothermal ecosystem had attracted the attention of philanthropists, funding entities, media, and influencers outside of Texas, and GEO’s executive director was invited to give a TED talk about oil and gas engagement in building the future of geothermal energy, which elevated the success of the ecosystem to a global audience.

15 GEOTHERMAL ENERGY↗

Tracer particle transport dynamics in the diffusive sandpile cellular automaton

The confinement properties of the diffusive running sandpile are characterized by tracking the motion of a population of marked grains of sand. It is found that, as the relative strength of the avalanching to the diffusive transport channel is varied, a point is reached at which the particle global confinement time and the probability density functions of the jump-sizes and waiting-times of the tracked grains experience a sudden change, thus revealing a dynamical transition, that is consistent with previous studies (Newman DE et al., Phys Rev Lett 2002;88(20):204304). Across this transition, the sandpile moves from a regime characterized by self-similarity and memory, where avalanches of all possible sizes dominate transport across the system, to another regime where transport is taken over by near system-size, quasi-periodic avalanches. Values for the fractional transport exponents that quantify effective transport across the sandpile prior to the transition are also obtained.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Land surface dynamics and meteorological forcings modulate land surface temperature characteristics

This study examines the effect of land cover, vegetation health, climatic forcings, elevation heat loads, and terrain characteristics (LVCET) on land surface temperature (LST) distribution over West Africa (WA). We employ fourteen machine-learning models, which preserve nonlinear relationships, to downscale LST and other predictands while preserving the geographical variability of WA. Our results showed that the random forest model performs best in downscaling predictands. This is important for the sub-region since it has limited access to mainframes to power multiplex machine-learning algorithms. In contrast to the northern regions, the southern regions consistently exhibit healthy vegetation. Also, areas with unhealthy vegetation coincide with hot LST clusters. The positive Normalized Difference Vegetation Index (NDVI) trends in the Sahel underscore rainfall recovery and subsequent Sahelian greening. The southwesterly winds cause the upwelling of cold waters, lowering LST in southern WA and highlighting the cooling influence of water bodies on LST. Identifying regions with elevated LST is paramount for prioritizing greening initiatives, and our study underscores the importance of considering LVCET factors in urban planning. Topographic slope-facing angles, heat loads, and diurnal anisotropic heat all contribute to variations in LST, emphasizing the need for a holistic approach when designing resilient and sustainable landscapes.

54 ENVIRONMENTAL SCIENCES↗

Self-Assembly of Silica Nanoparticles at Water–Hydrocarbon Interfaces: Insights from In Operando Small-Angle X-ray Scattering Measurements and Molecular Dynamics Simulations

To achieve tunable controls on the interactions of siliceous materials in subsurface environments bearing water and hydrocarbons, it is essential to determine the influence of hydrocarbon–water interfaces on the self-assembly of the silica particles. The hydrophilic silica particle have a tendency to aggregate on the water front of the interface. Self-assembly of silica nanoparticles proceeds via the migration of these nanoparticles to the water–hydrocarbon interface followed by aggregation at the interface. Fractal-like morphologies of assembled silica nanoparticles at water–hydrocarbon interfaces are observed. Rapid assembly of the hydrophilic silica nanoparticles at water–hydrocarbon interfaces corresponds to an overall reduction in the surface tension of water–toluene and water–heptane systems. These studies demonstrate the silica aggregation that is the precursor of silica polymerization, or nucleation and growth is influenced by the presence of hydrocarbons in subsurface geologic environments. These insights were derived from in operando ultrasmall and small-angle X-ray scattering (USAXS/SAXS) measurements, cryo-scanning electron microscopy (Cryo-SEM) imaging, and classical molecular dynamics simulations. As a result, these studies are intended to inform current and future efforts aimed at tuning silica reactivity in subsurface geologic environments to enhance permeability, the design and use of silica-based proppants to enhance fractures, and the development of effective strategies to control silica-based scaling behavior in subsurface reservoirs.

42 ENGINEERING↗

PSCF+: An Extended and Improved Open-Source Software Package for Polymer Self-Consistent Field Calculations

This work introduces PSCF+, a freely available open‑source software tool for modeling how block copolymers self‑assemble into ordered nanoscale structures. The software allows researchers to study a wide range of polymer models and interaction types, making it possible to directly compare theoretical predictions with molecular and simulation‑based studies in a consistent way. PSCF+ incorporates several recently developed numerical methods that significantly reduce computer memory requirements and speed up calculations, enabling efficient use of modern GPU hardware. Here, it also provides automated tools to calculate free‑energy landscapes and phase boundaries, which are essential for understanding and predicting material behavior. Together, these advances make PSCF+ a powerful and flexible platform for studying polymer self‑assembly and support the design of new polymeric materials for scientific and technological applications.

Chemical calculations↗

Charge Transport in Solvated Donor–Acceptor Functionalized Peptoids: Molecular Dynamics and Rate Theory

Scalable solar-energy conversion requires photoactive materials that combine the efficiency of natural photosynthetic systems with the stability and processability needed for practical applications. Achieving reliable charge transport in soft, self-assembled organic materials remains challenging, as structural fluctuations and environmental effects strongly influence charge-transfer (CT) rates. Here, we present a broadly applicable computational framework for evaluating CT rates in the condensed phase, combining Fermi’s golden rule rate theory with inputs from all-atom molecular dynamics (MD) simulations and first-principles electronic-structure calculations. The approach does not rely on system-specific parametrization and is applicable to a wide range of soft and disordered materials. We demonstrate the applicability and usefulness of the framework on redox-active peptoids functionalized with iron–porphyrin (Fe–P) complexes, a bioinspired platform with programmable donor–acceptor units and tunable three-dimensional organization. The calculated CT rates exhibit strong sensitivity to molecular conformation, with variations spanning several orders of magnitude. This dependence is shown to arise from the pronounced variation in diabatic electronic coupling with the relative orientations and separations of the Fe–P complexes across the conformational ensemble. The framework provides a consistent route for connecting atomistic structure to CT kinetics in the condensed phase and enables analysis of structure–rate relations in organic semiconducting systems.

Charge transfer↗