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At least 559 records · Page 31

Ultrathin graphene oxide-based hollow fiber membranes with brush-like CO 2 -philic agent for highly efficient CO 2 capture

Among the current CO 2 capture technologies, membrane gas separation has many inherent advantages over other conventional techniques. However, fabricating gas separation membranes with both high CO 2 permeance and high CO 2 /N 2 selectivity, especially under wet conditions, is a challenge. In this study, sub-20-nm thick, layered graphene oxide (GO)-based hollow fiber membranes with grafted, brush-like CO 2 -philic agent alternating between GO layers are prepared by a facile coating process for highly efficient CO 2 /N 2 separation under wet conditions. Piperazine, as an effective CO 2 -philic agent, is introduced as a carrier-brush into the GO nanochannels with chemical bonding. The membrane exhibits excellent separation performance under simulated flue gas conditions with CO 2 permeance of 1,020 GPU and CO 2 /N 2 selectivity as high as 680, demonstrating its potential for CO 2 capture from flue gas. We expect this GO-based membrane structure combined with the facile coating process to facilitate the development of ultrathin GO-based membranes for CO 2 capture.

36 MATERIALS SCIENCE↗

Selective inactivation of hypomethylating agents by SAMHD1 provides a rationale for therapeutic stratification in AML

Hypomethylating agents decitabine and azacytidine are regarded as interchangeable in the treatment of acute myeloid leukemia (AML). However, their mechanisms of action remain incompletely understood, and predictive biomarkers for HMA efficacy are lacking. Here, we show that the bioactive metabolite decitabine triphosphate, but not azacytidine triphosphate, functions as activator and substrate of the triphosphohydrolase SAMHD1 and is subject to SAMHD1-mediated inactivation. Retrospective immunohistochemical analysis of bone marrow specimens from AML patients at diagnosis revealed that SAMHD1 expression in leukemic cells inversely correlates with clinical response to decitabine, but not to azacytidine. SAMHD1 ablation increases the antileukemic activity of decitabine in AML cell lines, primary leukemic blasts, and xenograft models. AML cells acquire resistance to decitabine partly by SAMHD1 up-regulation. Together, our data suggest that SAMHD1 is a biomarker for the stratified use of hypomethylating agents in AML patients and a potential target for the treatment of decitabine-resistant leukemia.

60 APPLIED LIFE SCIENCES↗

Engineering and evaluation of FXa bypassing agents that restore hemostasis following Apixaban associated bleeding

Direct oral anticoagulants (DOACs) targeting activated factor Xa (FXa) are used to prevent or treat thromboembolic disorders. DOACs reversibly bind to FXa and inhibit its enzymatic activity. However, DOAC treatment carries the risk of anticoagulant-associated bleeding. Currently, only one specific agent, andexanet alfa, is approved to reverse the anticoagulant effects of FXa-targeting DOACs (FXaDOACs) and control life-threatening bleeding. However, because of its mechanism of action, andexanet alfa requires a cumbersome dosing schedule, and its use is associated with the risk of thrombosis. Here, we present the computational design, engineering, and evaluation of FXa-variants that exhibit anticoagulation reversal activity in the presence of FXaDOACs. Our designs demonstrate low DOAC binding affinity, retain FXa-enzymatic activity and reduce the DOAC-associated bleeding by restoring hemostasis in mice treated with apixaban. Importantly, the FXaDOACs reversal agents we designed, unlike andexanet alfa, do not inhibit TFPI, and consequently, may have a safer thrombogenic profile.

59 BASIC BIOLOGICAL SCIENCES↗

Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials

Abstract Mechanical behavior of 2D materials such as MoS 2 can be tuned by the ancient art of kirigami. Experiments and atomistic simulations show that 2D materials can be stretched more than 50% by strategic insertion of cuts. However, designing kirigami structures with desired mechanical properties is highly sensitive to the pattern and location of kirigami cuts. We use reinforcement learning (RL) to generate a wide range of highly stretchable MoS 2 kirigami structures. The RL agent is trained by a small fraction (1.45%) of molecular dynamics simulation data, randomly sampled from a search space of over 4 million candidates for MoS 2 kirigami structures with 6 cuts. After training, the RL agent not only proposes 6-cut kirigami structures that have stretchability above 45%, but also gains mechanistic insight to propose highly stretchable (above 40%) kirigami structures consisting of 8 and 10 cuts from a search space of billion candidates as zero-shot predictions.

36 MATERIALS SCIENCE↗

Operating advanced scientific instruments with AI agents that learn on the job

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations. However, these facilities must continuously evolve to support new experimental workflows, adapt to diverse user projects, and meet growing demands for more intricate instruments and experiments. This continuous development introduces significant operational complexity, necessitating a focus on usability, reproducibility, and intuitive human-instrument interaction. In this work, we explore the integration of agentic AI, powered by Large Language Models (LLMs), as a transformative tool to achieve this goal. We present our approach to developing a human-in-the-loop pipeline for operating advanced instruments including an X-ray nanoprobe beamline and an autonomous robotic station dedicated to the design and characterization of materials. Specifically, we evaluate the potential of various LLMs as trainable scientific assistants for orchestrating complex, multi-task workflows, which also include multimodal data, optimizing their performance through optional human input and iterative learning. We demonstrate the ability of AI agents to bridge the gap between advanced automation and user-friendly operation, paving the way for more adaptable and intelligent scientific facilities.

Large Language Models↗

An agentic artificially intelligent X-ray scientist

Executing experimental tasks in both normal research laboratories and large-scale scientific facilities often requires extensive human supervision and remains a key challenge on the path to fully autonomous, artificial intelligence (AI)-driven science. Here we demonstrate a large language model-driven agent that autonomously performs X-ray sample alignment on a synchrotron beamline by planning actions, executing instrumental commands, interpreting observations and iterating towards experimental goals. Based on existing large language models with structured tool-use via the model context protocol, our AI X-ray scientist was guided and tested using an in-house-built virtual experimental setup that mirrors a six-circle diffractometer at an operational synchrotron beamline. The agentic workflow developed in the virtual environment was directly deployed on a real beamline, where it correctly identified reference reflections and determined the orientation matrix, an essential first step in any type of single-crystal scattering experiment. Our AI X-ray scientist responded effectively to unexpected experimental conditions, demonstrating adaptive problem-solving and readiness for addressing practical experimental situations. Our study provides a step towards autonomous operation across diverse experimental environments at large-scale scattering facilities.

Chen, Zhantao (ORCID:0000000319543868)↗

Managing autonomous materials labs with multi-agent AI and its implications for the science of science

Self-driving lab systems (aka, autonomous experimentation) accelerate research - letting scientists learn faster, spend less resources, and fail smarter in well defined, narrow studies. The next-generation materials lab combines self-driving systems to tackle broader challenges - orchestrating complex research campaigns while optimizing lab resources. We propose that agent-based and agentic artificial intelligence will be an integral part of next-generation lab management and discuss potential implementation scenarios. Additionally, digital and physical sandboxes will allow scientists to evaluate diverse and dynamic research and lab management strategies. Beyond the immediate benefit to lab optimization, such sandboxes will enable realistic computational studies of the philosophy of science (i.e., science of science) to achieve higher level scientific efficiencies.

Computer science↗

Phenotypic transition maps of 3D breast acini obtained by imaging-guided agent-based modeling

We introduce an agent-based model of epithelial cell morphogenesis to explore the complex interplay between apoptosis, proliferation, and polarization. By varying the activity levels of these mechanisms we derived phenotypic transition maps of normal and aberrant morphogenesis. These maps identify homeostatic ranges and morphologic stability conditions. The agent-based model was parameterized and validated using novel high-content image analysis of mammary acini morphogenesis in vitro with focus on time-dependent cell densities, proliferation and death rates, as well as acini morphologies. Model simulations reveal apoptosis being necessary and sufficient for initiating lumen formation, but cell polarization being the pivotal mechanism for maintaining physiological epithelium morphology and acini sphericity. Furthermore, simulations highlight that acinus growth arrest in normal acini can be achieved by controlling the fraction of proliferating cells. Interestingly, our simulations reveal a synergism between polarization and apoptosis in enhancing growth arrest. After validating the model with experimental data from a normal human breast line (MCF10A), the system was challenged to predict the growth of MCF10A where AKT-1 was overexpressed, leading to reduced apoptosis. As previously reported, this led to non growth-arrested acini, with very large sizes and partially filled lumen. However, surprisingly, image analysis revealed a much lower nuclear density than observed for normal acini. The growth kinetics indicates that these acini grew faster than the cells comprising it. The in silico model could not replicate this behavior, contradicting the classic paradigm that ductal carcinoma in situ is only the result of high proliferation and low apoptosis. Our simulations suggest that overexpression of AKT-1 must also perturb cell-cell and cell-ECM communication, reminding us that extracellular context can dictate cellular behavior.

59 BASIC BIOLOGICAL SCIENCES↗

Nanoparticle-Based Immunochromatographic Test Strip with Fluorescent Detector for Quantification of Phosphorylated Acetycholinesterase: An Exposure Biomarker of Organophosphorous Agents

A nanoparticle-based fluorescence immunochromatographic test strip (FITS) coupled with a hand-held detector for highly selective and sensitive detection of phosphorylated acetylcholinesterase (AChE), an exposure biomarker of organophosphate (OP) pesticides and nerve agents, is reported. In this approach, OP-AChE adducts were selectively captured by quantum dot-tagged anti-AChE antibodies (Qdot-anti-AChE) and zirconia nanoparticles (ZrO2 NPs). The sandwich-like immunoreactions were performed among the Qdot-anti-AChE, OP-AChE and ZrO2 NPs to form Qdot-anti-AChE/OP-AChE/ZrO2 complex, which was detected by recording the fluorescence intensity of Qdot captured on the test line. Paraoxon was used as the model OP pesticides. Under optimal conditions, this portable FITS immunosensor demonstrates a highly linear absorption response over the range of 0.01 nM to 10 nM OP-AChE, with a detection limit of 4 pM, coupled with a good reproducibility. Moreover, the FITS immunosensor has been validated with OP-AChE spiked human plasma samples. This is the first report on the development of ZrO2 NPs-based FITS for detection of OP-AChE adduct. The FITS immunosensor provides a sensitive and low-cost sensing platform for on-site screening/evaluating OP pesticides and nerve agents poisoning.

Acetylcholinesterase↗

Effects of biradical deuteration on the performance of DNP: Towards better performing polarizing agents

We study the effects of the deuteration of biradical polarizing agents on the efficiency of dynamic nuclear polarization (DNP) via the cross-effect. To this end, we synthesized a series of bTbK and TOTAPol biradicals with systematically increased deuterium substitution. The deuteration increases the radicals' relaxation time, thus contributing to a higher saturation factor and larger DNP enhancement, and reduces the pool of protons within the so-called spin diffusion barrier. Notably, we report that full or partial deuteration leads to improved DNP enhancement factors in standard samples, but also slows down the build-up of hyperpolarization. Improvements in DNP enhancements factors of up to 70% and time savings of up to 38% are obtained upon full deuteration. As a result, it is foreseen that this approach may be applied to other DNP polarizing agents thus enabling further sensitivity improvements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

One-pot synthesis of MWW zeolite nanosheets using a rationally designed organic structure-directing agent

A new material MIT-1 comprised of delaminated MWW zeolite nanosheets is synthesized in one-pot using a rationally designed organic structure-directing agent (OSDA). The OSDA is comprised of a hydrophilic head segment that resembles the OSDA used to synthesize the zeolite precursor MCM22(P), a hydrophobic tail segment that resembles the swelling agent used to swell MCM22(P), and a di-quaternary ammonium linker that connects both segments. MIT-1 features high crystallinity and surface areas exceeding 500 m 2 g -1 , and can be synthesized over a wide synthesis window that includes Si/Al ratios ranging from 13 to 67. Characterization data reveal high mesoporosity and acid strength with no detectable amorphous silica phases. In conclusion, compared to MCM-22 and MCM-56, MIT-1 shows a three-fold increase in catalytic activity for the Friedel-Crafts alkylation of benzene with benzyl alcohol.

36 MATERIALS SCIENCE↗

Highly efficient synthesis of zeolite chabazite using cooperative hydration-mismatched inorganic structure-directing agents

Chabazite (CHA type) zeolite is notoriously difficult to synthesize in the absence of organic structure-directing agents owing to long synthesis times and/or impurity formation. The ability to tailor organic-free syntheses of zeolites is additionally challenging due to the lack of molecular level understanding of zeolite nucleation and growth pathways, particularly the role of inorganic cations. In this study, we reveal that zeolite CHA can be synthesized using six different combinations of inorganic cations, including the first reported seed- and organic-free synthesis without the presence of potassium. We show that lithium, when present in small quantities, is an effective accelerant of CHA crystallization; and that ion pairings can markedly reduce synthesis times and temperatures, while expanding the design space of zeolite CHA formation in comparison to conventional methods utilizing potassium as the sole structure-directing agent. Herein, we posit the effects of cation pairings on zeolite CHA crystallization are related to their hydrated ionic radii. We also emphasize the broader implications for considering the solvated structure and cooperative role of inorganic cations in zeolite synthesis within the context of the reported findings for chabazite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation

We present a multi-agentic workflow for critical materials recovery that deploys a series of AI agents and automated instruments to recover critical materials from produced water and magnet leachates. This approach achieves selective precipitation from real-world feedstocks using simple chemicals, accelerating the development of efficient, adaptable, and scalable separations to a timeline of days, rather than months and years.

Ritchhart, Andrew J.↗

Enhanced heat transfer through filler-polymer interface by surface-coupling agent in heat-dissipation material: A non-equilibrium molecular dynamics study

Developing a composite material of polymers and micrometer-sized fillers with higher heat conductance is crucial to realize modular packaging of electronic components at higher densities. Enhancement mechanisms of the heat conductance of the polymer-filler interfaces by adding the surface-coupling agent in such a polymer composite material are investigated through the non-equilibrium molecular dynamics (MD) simulation. A simulation system is composed of α-alumina as the filler, bisphenol-A epoxy molecules as the polymers, and model molecules for the surface-coupling agent. The inter-atomic potential between the α-alumina and surface-coupling molecule, which is essential in the present MD simulation, is constructed to reproduce the calculated energies with the electronic density-functional theory. Through the non-equilibrium MD simulation runs, we find that the thermal resistance at the interface decreases significantly by increasing either number or lengths of the surface-coupling molecules and that the effective thermal conductivity of the system approaches to the theoretical value corresponding to zero thermal-resistance at the interface. Detailed analyses about the atomic configurations and local temperatures around the interface are performed to identify heat-transfer routes through the interface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Realization of consensus of multi-agent systems with stochastically mixed interactions

In this paper, we propose a new consensus model in which the interactions among agents stochastically switch between attraction and repulsion. Such a positive-and-negative mechanism is described by the white-noise-based coupling. Analytic criteria for the consensus and non-consensus in terms of the eigenvalues of the noise intensity matrix are derived, which provide a better understanding of the constructive roles of random interactions. Specifically, we discover a positive role of noise coupling that noise can accelerate the emergence of consensus. We find that the converging speed of the multi-agent network depends on the square of the second smallest eigenvalue of its graph Laplacian. The influence of network topologies on the consensus time is also investigated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Silicon nanoparticles as contrast agents in the methods of optical biomedical diagnostics

The efficiency of light scattering by nanoparticles formed using the method of picosecond laser ablation of silicon in water and by nanoparticles of mechanically grinded mesoporous silicon is compared. The ensembles of particles of both types possess the scattering coefficients sufficient to use them as contrast agents in optical coherence tomography (OCT), particularly in the range of wavelengths 700 – 1000 nm, where the absorption of both silicon and most biological and mimicking tissues is small. According to the Mie theory the main contribution to the scattering in this case is made by the particles having a relatively large size (150 – 300 nm). In the experiments on visualising the agar phantom surface by means of OCT, the contrast of the medium boundary, provided by nanoparticles amounted to 14 dB and 30 dB for the ablated particles and the porous silicon powder, respectively. The numerical simulation of OCT images of skin in the presence of nanoparticles, confirmed the efficiency of using them as a contrast agent. (nanoparticles)

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Accelerating countermeasure candidate discovery for A-series chemical warfare agent exposure

The recent alleged use of A-series chemical warfare agents (CWAs) highlights the urgent need to better understand their inhibition of cholinesterase enzymes and the reported shortcomings of traditional oxime countermeasures. Here, using high-throughput (HT) mass spectrometry (MS) technologies, we characterized the largely unknown inhibition kinetics of A-series CWAs on human acetylcholinesterase (hAChE) and its reactivation by oximes, achieving label-free quantitation at rates of up to 7,000 reactions per hour. Our findings indicate i) A-series agents exhibit inhibitory potencies similar to traditional CWAs like sarin and VX, and ii) bipyridinium-based oximes can reactivate A-series-adducted hAChE in vitro, challenging prior reports on oxime efficacy. These results underscore the need for continued exploration of countermeasure candidates against A-series CWAs and demonstrate the potential of HT-MS for rapidly and safely characterizing emerging toxic chemicals.

acetylcholinesterase↗

Torrefaction of almond shell as a renewable reinforcing agent for plastics: techno-economic analyses and comparison to bioethanol process

Abstract In 2016, the US state of California alone produced nearly 3.5 billion kilograms of almonds, accounting for approximately 84% of the world’s almond production. This generated about 2.58 million metric tons (MTs) of almond residues. Almond shells are currently either burned to generate power or disposed of in landfill. Valorizing almond shells and hulls provides an opportunity to replace petroleum-derived products and divert organic material from landfill. Here we demonstrate a detailed techno-economic analysis (TEA) of an almond shell torrefaction process capable of utilizing the 520 000 MTs of almond shells produced annually in California. Our process also includes preprocessing the torrefied biomass to exploit it as a reinforcing agent for plastics. We further compared the revenue generated from the torrefied biomass and bioethanol derived from the same quantity of almond shells. We considered three different torrefaction facility scales to evaluate trade-offs between economies of scale at the facility and trucking costs to deliver almond shells. A facility that takes in 200 000 MT yr –1 of almond shells results in lower per-unit-output basis capital and operating cost relative to other smaller-scale torrefaction facilities, including 10 000 MT yr –1 and 50 000 MT yr –1 , considered for analysis in this study. The large-sale facility results in a minimum selling price (MSP) of the torrefied biomass of $311.4 MT –1 . An analogous TEA on converting almond residues into bioethanol is also investigated. The MSP of almond shell derived ethanol ($1.71 kg −1 ) is higher than that of corn ($0.48 kg −1 ) or cellulosic biomass ($0.88 kg −1 ) derived ethanol. Compared with the bioethanol route, the torrefied almond shells result in three times more revenue if utilized as a reinforcing agent for plastics.

Liu, Dupeng (ORCID:0000000269514064)↗