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At least 973 records · Page 54

The Future of a Myriad of Accelerated Biodiscoveries Lies in AI‐Powered Mass Spectrometry and Multiomics Integration

The intersection of modern artificial intelligence (AI) and mass spectrometry (MS) is set to transform the MS‐based “omics” research fields, particularly proteomics, metabolomics, lipidomics, and glycomics, enabling advancements across a wide range of domains, from health to environment and industrial biotechnology. Beginning with an overview of key challenges inherent in MS software pipelines, this personal perspective explores how AI‐driven solutions can address them to enhance data processing, integration and interpretation. It proposes a paradigm shift in molecular identification and quantitation algorithms, leveraging AI to enable holistic interpretation of MS‐based multiomics data. While centered on MS‐based omics, this holistic AI‐driven paradigm is also critical for connecting dynamic biochemical changes to genomics and transcriptomics contexts, reinforcing the integrative value of MS in multiomics research. Ultimately, this AI‐driven approach could enhance efficiency, accuracy, and molecular breadth of coverage, deepening our systems‐level understanding of biological processes and accelerating a myriad of biodiscoveries.

47 OTHER INSTRUMENTATION↗

An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems

Deep Reinforcement Learning (DRL)-based control shows enhanced performance in the management of integrated energy systems when compared with Rule-Based Controllers (RBCs), but it still lacks scalability and generalisation due to the necessity of using tailored models for the training process. Transfer Learning (TL) is a potential solution to address this limitation. However, existing TL applications in building control have been mostly tested among buildings with similar features, not addressing the need to scale up advanced control in real-world scenarios with diverse energy systems. This paper assesses the performance of an online heterogeneous TL strategy, comparing it with RBC and offline and online DRL controllers in a simulation setup using EnergyPlus and Python. The study tests the transfer in both transductive and inductive settings of a DRL policy designed to manage a chiller coupled with a Thermal Energy Storage (TES). The control policy is pre-trained on a source building and transferred to various target buildings characterised by an integrated energy system including photovoltaic and battery energy storage systems, different building envelope features, occupancy schedule and boundary conditions (e.g., weather and price signal). The TL approach incorporates model slicing, imitation learning and fine-tuning to handle diverse state spaces and reward functions between source and target buildings. Results show that the proposed methodology leads to a reduction of 10% in electricity cost and between 10% and 40% in the mean value of the daily average temperature violation rate compared to RBC and online DRL controllers. Moreover, online TL maximises self-sufficiency and self-consumption by 9% and 11% with respect to RBC. Conversely, online TL achieves worse performance compared to offline DRL in either transductive or inductive settings. However, offline Deep Reinforcement Learning (DRL) agents should be trained at least for 15 episodes to reach the same level of performance as the online TL. Therefore, the proposed online TL methodology is effective, completely model-free and it can be directly implemented in real buildings with satisfying performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Resilience in an Age of Increasing Electrification

The purpose of this paper is to outline considerations of global electrification trends that include the resultant system-wide and nation-wide impacts. How we incorporate resilience into the electrification plans that transition a nation from conventional energy sources to secure clean energy sources can impact the success of those transitions. Electrification of energy systems has the potential to impact power system planning, emissions, and security; however, little research has been done on comprehensive solutions for incorporating resilience into the electrification process. Research has been conducted on aspects of the energy system and electrification, but not holistically across disciplines and related to the interdependencies of different components of the grid system. This gap in research provides an opportunity for more analysis and a collection of best practices to incorporate resilience into electrification plans. Although clean energy is the goal of an increasing number of nations worldwide, there are many considerations in designing clean energy transitions and increased electrification. Resilience must be factored into clean energy transitions from planning, market design, and policies to modernized grid structures and new, location-specific dispersed energy and energy storage technologies.

clean energy↗

Experimental investigation of a reverse osmosis desalination system directly powered by wave energy

Powering desalination processes with renewable energy is a promising solution to address the global issue of water shortage with minimum carbon footprint and environmental impact. Here, we experimentally investigate a sustainable reverse osmosis (RO) desalination system directly powered by wave energy. In this system, seawater is pressurized and pumped to a RO desalination module via a piston pump directly driven by an oscillating surge wave energy converter (OSWEC). An accumulator is adopted on the feed inlet to mitigate the pressure fluctuations under time-varying ocean conditions. Meanwhile, a needle valve on the brine outlet is used to adjust the system pressure and water recovery. A 1:10 scaled model was designed, fabricated, and tested in a wave tank based on the Froude scaling law. Further, the optimal specific water productivity (SWP) obtained in the tank tests with 3.5 g/L feed salinity was 2.23m 3 /kWh, indicating a full-scale specific water productivity of 0.22m 3 /kWh for 35g/L seawater salinity. The influence of needle valve tuning on the specific water productivity was experimentally investigated and analyzed. Under a specific operational condition, tuning this valve improved specific water productivity by about 17% and reduced the system pressure by 24%, thereby avoiding extreme pressure and improving the system’s capability. This pilot study demonstrates that ocean wave energy is a promising source to sustainably power reverse osmosis desalination and provide freshwater water for coastal regions.

16 TIDAL AND WAVE POWER↗

Water desalination through the dewpoint evaporative system

This paper presents the first numerical analysis of a novel Dew Point Desalination unit (DPD), which utilizes the phenomenon of the evaporative cooling process to minimize energy consumption. The proposed solution is based on a modular structure, which allows it to obtain any required water production capacity. The analyses for various operational parameters and various climatic conditions are based on the numerical simulations conducted using a validated mathematical model. The system performance was described with different factors, including specific energy consumption (SEC) and daily water production rate respected to 1 m^3*s^-1 of passing air stream (DWP). It is shown that the DPD system can operate in almost every climate zone, and the desalinated water production consumes less than 1.5 kWh*m^-3 of electric energy It is noted the best performance of the DPD system is achieved in the semi-arid, desert and subtropical climate zones. In these climate zones, the 2-stage DPD system allows the production of desalinated water with an electric energy consumption SEC lower than 0.5 kWh*m^-3. The additional benefit of the DPD system is its modularity. The presented DPD system stands as a module, that can be multiplied as needed to achieve the desired size of the desalination plant.

Desalination↗

A high order Cartesian grid, finite volume method for elliptic interface problems

We present a higher-order finite volume method for solving elliptic PDEs with jump conditions on interfaces embedded in a 2D Cartesian grid. Second, fourth, and sixth order accuracy is demonstrated on a variety of tests including problems with high-contrast and spatially varying coefficients, large discontinuities in the source term, and complex interface geometries. We include a generalized truncation error analysis based on cell-centered Taylor series expansions, which then define stencils in terms of local discrete solution data and geometric information. In the process, we develop a simple method based on Green's theorem for computing exact geometric moments directly from an implicit function definition of the embedded interface. This approach produces stencils with a simple bilinear representation, where spatially-varying coefficients and jump conditions can be easily included and finite volume conservation can be enforced.

97 MATHEMATICS AND COMPUTING↗

Radiation-induced molecular hydrogen gas generation in the presence of aluminum alloy 1100

The United States government currently manages nearly 13 metric tons of aluminum-clad spent nuclear fuel (SNF) without a long-term storage solution, so a fundamental understanding of corrosion processes occurring on aluminum alloy surfaces is of utmost importance to plan for extended (>50 years) interim dry storage of aluminum-clad SNF. While thermal and chemical corrosion processes are well characterized for aluminum, radiation effects are not. To help understand the impacts of radiation on aluminum-clad SNF, here the radiation-induced molecular hydrogen gas (H 2 ) generation from pristine and pre-corroded aluminum alloy 1100 (Al-1100) coupons have been studied. Corrosion of coupons was achieved by submerging coupons in water at 95 °C for 29 days, yielding a ~5 μm boehmite/bayerite oxide film. Pre-corroded coupons were exposed to cobalt-60 gamma radiation to absorbed doses of up to 1.0 MGy under a variety of conditions: cover-gas composition (argon, nitrogen, or air), relative humidity (0, 50, and 100%), and temperature (ambient, 100, and 200 °C). Post-irradiation measurements demonstrated that the yield of H 2 was directly attributable to the presence of the Al-1100 coupons and their physisorbed water with dependence on absorbed gamma dose, relative humidity, and cover-gas composition. No H 2 was quantified in the presence of air, while both nitrogen and argon environments afforded higher H 2 yields with increasing relative humidities. This was attributed to the greater availability of adsorbed water for radiolytic processes. Irradiation of pre-corroded Al-1100 coupons at different temperatures under 0% relative humidity argon conditions yielded statistically equivalent H 2 yields for ambient temperatures and 100 °C. However, irradiation at 200 °C promoted a 3 to 4-fold increase in the yield of H 2 , possibly due to the transformation of bayerite to boehmite and/or improved efficiency of H • and H 2 release from oxide surfaces.

36 MATERIALS SCIENCE↗

Separation, speciation, and mechanism of astatine and bismuth extraction from nitric acid into 1-octanol and methyl anthranilate

We report a detailed study of At and Bi extraction from nitric acid media into conventional solvents, namely 1-octanol and methyl anthranilate, has been performed. The analysis includes a mathematical modeling which allows the fitting of experimental data and determination of extraction constants of the two above mentioned elements. Also, this approach helped to estimate a stability constant of a weak AtO(NO3) complex along with thermodynamic constants describing the redox process of At species in the acidic solution and formation of an adduct of Bi in the presence of methyl anthranilate. The results of the fitting have been used to calculate corresponding separation factors of Bi and At as well. Moreover, a computational study has been performed to evaluate At interaction with the above mentioned solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reactive Transport Modeling of Shale–Fluid Interactions after Imbibition of Fracturing Fluids

Injection of hydraulic fracturing fluid (HFF) into shale formations for unconventional oil/gas production results in chemical reactions in the shale matrix. Our recent experimental study determined the depths to which different types of reactions between the shale matrix and the HFF extended. In the present study, we built continuum-scale reactive transport models to understand the coupling of chemical reactions and the transport of aqueous species in these shale–HFF systems. Calibration of the model with our previous experimental results reveals that it takes hours to months for the shale matrix to completely neutralize the imbibed acids, depending primarily upon the carbonate content of the shale. Both the HFF pH and pore pH affect the location of barite precipitation, resulting in unique barite precipitation profiles extending millimeters into calcite-rich Eagle Ford shale but only tens of micrometers into low-carbonate Marcellus shale. In addition, dissolved oxygen and extracted bitumen are key to reproducing the experimental observation of Fe(III) (oxyhydr)oxide formation in the shale matrix as a result of pyrite dissolution in the shales. A comparison between the modeling results of porosity in the present study to experimentally measured permeabilities in our previous study suggests that chemical reactions occurring at a greater depth than the observable reaction zone might have impacted permeability. Our model serves as a benchmark for efficiently modeling water–rock interactions in similar systems where bulk rock samples react with a solution in batch reactors. Important reactive transport processes were ascertained via modeling, which allows for quantitative prediction of shale–HFF interactions in shale matrices given the shale and HFF compositions.

58 GEOSCIENCES↗

Excited State Orbital Optimization via Minimizing the Square of the Gradient: General Approach and Application to Singly and Doubly Excited States via Density Functional Theory

We present a general approach to converge excited state solutions to any quantum chemistry orbital optimization process, without the risk of variational collapse. The resulting square gradient minimization (SGM) approach only requires analytic energy/Lagrangian orbital gradients and merely costs 3 times as much as ground state orbital optimization (per iteration), when implemented via a finite difference approach. SGM is applied to both single determinant ΔSCF and spin-purified restricted open-shell Kohn-Sham (ROKS) approaches to study the accuracy of orbital optimized DFT excited states. It is found that SGM can converge challenging states where the maximum overlap method (MOM) or analogues either collapse to the ground state or fail to converge. We also report that ΔSCF/ROKS predict highly accurate excitation energies for doubly excited states (which are inaccessible via TDDFT). Singly excited states obtained via ROKS are also found to be quite accurate, especially for Rydberg states that frustrate (semi)local TDDFT. Our results suggest that orbital optimized excited state DFT methods can be used to push past the limitations of TDDFT to doubly excited, charge-transfer, or Rydberg states, making them a useful tool for the practical quantum chemist's toolbox for studying excited states in large systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unraveling the Formation Mechanism of a Hybrid Zr-Based Chemical Conversion Coating with Organic and Copper Compounds for Corrosion Inhibition

Environmental-friendly chromate-free, zirconium (Zr)-based conversion coating is a promising green technology for corrosion protection. Additives in the surface treatment provides critical functionalities and performance improvements; however, mechanistic understanding as of how the additives influence the coatings remains unclear. In this study, a new organic-inorganic hybrid Zrbased conversion coating which combines copper (Cu) compounds and polyamidoamine (PAMAM), taking advantages of a complementary nature of organic and inorganic additives. Here, a multimodal approach combining electron and X-ray characterization is applied to study the interaction of Cu 2+ and PAMAM and the resulting impacts on the coating formation. Adding PAMAM changed the surface morphology, thickness, distribution of Cu in the cluster and void formation of the coatings. High PAMAM (100-200 pm) leads to little conversion coating formation, and low PAMAM (0-25 ppm) shows voids formation under the coatings. Moreover, PAMAM incorporates in the coating in a form of PAMAM-Cu complex with a higher concentration towards the surface, provides an organic layer at the surface of the coating. X-ray absorption near-edge structure (XANES) spectroscopy shows a difference between the conventional and hybrid coating treatments in an alkaline solution to simulate the E-coat process, suggesting the contribution of PAMAM in the enhanced chemical stability in an alkaline environment. Therefore, an intermediate range of addition of PAMAM (50 ppm) is optimal to 1) avoid excessive voids formation, 2) promote some Cu cluster formation and thus enhancing the Zr-based coating formation and 3) incorporate organic components into the coating to improve the adhesion of the subsequent coatings. Overall, this work furthers our knowledge on the formation mechanism of an effective and environmentally friendly hybrid conversion coating for corrosion inhibition, demonstrating a critical processing-structureproperty relationship. This study will benefit future development of green and effective surface treatment technology.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Understanding Cation Selectivity in Carbon Nanopores with Hybrid First-Principles/Continuum Simulations: Implications for Water Desalination and Separation Technologies

Understanding ion adsorption in porous carbons is crucial for a range of technologies, including water desalination and energy storage. In this work, we combined density functional theory with a continuum solvation model to investigate thermodynamics and kinetics of the adsorption process of alkali metal ions from aqueous solutions into carbon nanopores with different sizes and geometries. We found that cations with a larger ionic radius are more favorable to enter the nanopores because of a lower energy penalty of dehydration. In addition, the pore size and geometry were found to have a significant impact on the ion–pore interaction under confinement and cation selectivity. Our study highlights a complex interplay among nanopore geometry, ion size, and hydration on the cation adsorption selectivity, suggesting that tuning the porosity could represent a general strategy for improving ion separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hybrid Nanocrystals of Small Molecules and Chemically Disordered Polymers

Organic crystals formed by small molecules can be highly functional but are often brittle or insoluble structures with limited possibilities for use or processing from a liquid phase. A possible solution is the nanoscale integration of polymers into organic crystals without sacrificing long-range order and therefore function. This enables the organic crystals to benefit from the advantageous mechanical and chemical properties of the polymeric component. We report here on a strategy in which small molecules co-crystallize with side chains of chemically disordered polymers to create hybrid nanostructures containing a highly ordered lattice. Synchrotron X-ray scattering, absorption spectroscopy, and coarse-grained molecular dynamics simulations reveal that the polymer backbones form an “exo-crystalline” layer of disordered chains that wrap around the nanostructures becoming a handle for interesting properties. The morphology of this “hybrid bonding polymer” nanostructure is dictated by the competition between the polymers’ entropy and the enthalpy of the lattice allowing for control over the aspect ratio of the nanocrystal by changing the degree of polymer integration. Further, we observed that nanostructures with an exo-crystalline layer of polymer exhibit enhanced fracture strength, self-healing capacity, and dispersion in water, which benefits their use as light-harvesting assemblies in photocatalysis. Guided by computation, future work could also explore these hybrid nanostructures as building blocks for functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct Air Capture and Sequestration of CO 2 by Accelerated Indirect Aqueous Mineral Carbonation under Ambient Conditions

Mineralization of gaseous carbon dioxide into solid carbonates using alkaline industrial residues such as coal fly ash has a dual advantage of reducing the carbon dioxide footprint of coal power plants and improving ash utilization. However, the slow mineral carbonation rate under atmospheric conditions is a major challenge, especially when using natural minerals or industrial residues for direct air capture (DAC) of CO 2 . In this study, using coal fly ash samples and concentrated alkali carbonate aqueous solutions as a recyclable solvent, we show the feasibility of coupling mineral carbonation with DAC under atmospheric conditions. Findings show that carbonation efficiency is best under alkaline conditions, achieving as high as ~80% conversion to calcium carbonates within 1 h in a 1.9 M sodium carbonate solution. Based on the experimental results, a process coupling DAC and mineral carbonation that operates entirely under ambient conditions is proposed. Here, the techno-economic and life cycle assessments for the proposed process project a levelized cost of $\$116$–133/t-CO 2 -sequestered (US $\$2019$) and process carbon emissions (GWP) in the range of 0.03–0.25 t-CO 2 e/t-CO 2 -sequestered. Considering the low cost, simplicity, and gigaton-scale sequestration potential, we believe that DAC based on alkaline industrial residue carbonation can be considered a “low-hanging fruit” in the pursuit of negative emissions to combat climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observation of formation and local structures of metal-organic layers via complementary electron microscopy techniques

Abstract Metal-organic layers (MOLs) are highly attractive for application in catalysis, separation, sensing and biomedicine, owing to their tunable framework structure. However, it is challenging to obtain comprehensive information about the formation and local structures of MOLs using standard electron microscopy methods due to serious damage under electron beam irradiation. Here, we investigate the growth processes and local structures of MOLs utilizing a combination of liquid-phase transmission electron microscopy, cryogenic electron microscopy and electron ptychography. Our results show a multistep formation process, where precursor clusters first form in solution, then they are complexed with ligands to form non-crystalline solids, followed by the arrangement of the cluster-ligand complex into crystalline sheets, with additional possible growth by the addition of clusters to surface edges. Moreover, high-resolution imaging allows us to identify missing clusters, dislocations, loop and flat surface terminations and ligand connectors in the MOLs. Our observations provide insights into controllable MOL crystal morphology, defect engineering, and surface modification, thus assisting novel MOL design and synthesis.

36 MATERIALS SCIENCE↗

Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders

Abstract Coherent diffraction imaging (CDI) is an advanced non-destructive 3D X-ray imaging technique for measuring a sample’s electron density. The main challenge of CDI is loss of phase information in diffraction intensity measurements, resulting in lengthy iterative reconstruction processes that can return non-unique solutions, which pose challenges for experiments attempting to track dynamic sample evolution through multiple states. As the increased brightness of fourth-generation light sources enables faster sample measurements and drives operando experiments with Bragg CDI, there is a growing need for faster reconstruction techniques that can keep pace. We have developed an adaptive generative autoencoder approach for uniquely tracking a sample’s electron density as it dynamically evolves. Our approach adaptively tunes the low-dimensional latent embedding of a generative autoencoder, enabling a computationally efficient manner to account for time-varying shifting distributions in real-time. Analytic proof of convergence is provided as well as numerical demonstration of sample tracking with noisy measurements.

97 MATHEMATICS AND COMPUTING↗

Proton affinities of pertechnetate (TcO 4 - ) and perrhenate (ReO 4 - )

The anions pertechnetate, TcO 4 - , and perrhenate, ReO 4 - , exhibit very similar chemical and physical properties. Revealing and understanding disparities between them enhances fundamental understanding of both. Electrospray ionization generated the gas-phase proton bound dimer (TcO 4 - )(H + )(ReO 4 - ). Collision induced dissociation of the dimer yielded predominantly HTcO 4 - and ReO 4 - , which according to Cooks’ kinetic method indicates that the proton affinity (PA) of TcO 4 - is greater than that of Re O 4 - . Density functional theory computations agree with the experimental observation, providing PA[TcO 4 - ] = 300.1 kcal mol -1 and PA[ReO 4 - ] = 297.2 kcal mol -1 . Attempts to rationalize these relative PAs based on elementary molecular parameters such as atomic charges indicate that the entirety of bond formation and concomitant bond disruption needs to be considered to understand the energies associated with such protonation processes. Although in both the gas and solution phases, TcO 4 - is a stronger base than ReO 4 - , it is noted that the significance of even such qualitative accordance is tempered by the very different natures of the underlying phenomena.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗