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At least 1,117 records · Page 62

Challenges and Opportunities in the Enzymatic Recycling of Nylons

Enzymatic depolymerization has the potential to contribute to nylon waste recycling. However, the implementation of a viable industrial process still lags far behind progress in enzymatic polyester recycling. Here we review the current biocatalytic nylon recycling landscape, highlighting biochemical, structural, and materials science barriers that currently limit depolymerization extents. We detail efforts to identify, engineer, and characterize new nylon depolymerases, where currently even the best biocatalysts rarely exceed ~1 wt% conversion of solid polymer to products. Based on our analyses, we suggest that limited substrate accessibility due to substrate crystallinity and hydrogen bonding, rather than intrinsic enzyme inefficiency or instability, is the primary bottleneck to enhanced depolymerization. Guided by successes in polyester enzymatic recycling, we outline a research roadmap combining nylonase engineering with polymer pretreatment, chemo-enzymatic cascades, and process analyses to accelerate development of viable enzymatic nylon recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Catalytic pyrolysis as a platform technology for supporting the circular carbon economy

Catalytic pyrolysis, a process that combines pyrolysis and vapour-phase catalytic upgrading, is a versatile technology platform capable of direct liquefaction of biomass and waste plastic into intermediates that can enable the decarbonized production of chemicals and/or transportation fuels. Recently, catalytic pyrolysis has attracted substantial research and commercialization attention, with over 15,000 journal articles and patents published in the past decade alone. Here, in this Perspective, we chart a path towards commercial-scale catalytic pyrolysis of waste plastic and biomass by identifying key short-term and long-term technological barriers. Within the proposed development roadmap addressing these barriers, catalytic pyrolysis can move from the demonstration scale to integrated biorefinery networks producing fuels and plastics precursors at a scale of between 0.1 and 1 billion tonnes of carbon per year.

09 BIOMASS FUELS↗

Global tuning of hadronic interaction models with accelerator-based and astroparticle data

In high-energy and astroparticle physics, event generators play an essential role, even in the simplest data analyses. As analysis techniques become more sophisticated, e.g. based on deep neural networks, their correct description of the observed event characteristics becomes even more important. Physical processes occurring in hadronic collisions are simulated within a Monte Carlo framework. A major challenge is the modeling of hadron dynamics at low momentum transfer, which includes the initial and final phases of every hadronic collision. QCD-inspired phenomenological models used for these phases cannot guarantee completeness or correctness over the full phase space. These models usually include parameters which must be tuned to suitable experimental data. Until now, event generators have been developed and tuned mainly on the basis of data from high-energy physics experiments at accelerators. The wealth of data available from the latest generation of astroparticle experiments has not yet been fully exploited, and in many cases is not satisfactorily described. Both kinds of data sets are complementary as astroparticle experiments provide sensitivity especially to hadrons produced nearly parallel to the collision axis and cover center-of-mass energies up to several hundred TeV, well beyond those reached at colliders so far. In this report, we provide an overview of state-of-the-art event generators and their tuning, including the most relevant inputs from high-energy accelerator and astroparticle experiments. We present a road map that shows, for the first time, how the unified tuning of event generators with accelerator-based and astroparticle data can be performed.

Albrecht, J. [Ruhr U., Bochum, RAPP Ctr.; Ruhr U.,↗

Federated benchmarking of medical artificial intelligence with MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status and real-world deployment, our roadmap and, importantly, the use of MedPerf with multiple international institutions within cloud-based technology and on-premises scenarios. Finally, we welcome new contributions by researchers and organizations to further strengthen MedPerf as an open benchmarking platform.

60 APPLIED LIFE SCIENCES↗

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs

Applications of deep learning (DL) to design nanomaterials are hampered by a lack of suitable data representations and training data. Here, in this study, we report efforts to overcome these limitations and leverage DL to optimize the nonlinear optical properties of core–shell upconverting nanoparticles (UCNPs). UCNPs, which have applications in fields such as biosensing, super-resolution microscopy and three-dimensional printing, can emit visible and ultraviolet light from near-infrared excitations. We report a large-scale dataset of UCNP emission spectra based on accurate but expensive kinetic Monte Carlo simulations (N > 6,000) and use these data to train a heterogeneous graph neural network using a physically motivated representation of UCNP nanostructure. Applying gradient-based optimization on the trained graph neural network, we identify structures with 6.5× higher predicted emission under 800-nm illumination than any UCNP in our training set. Our work reveals design principles for UCNP heterostructures and presents a roadmap for DL-based inverse design of nanomaterials.

Sivonxay, Eric [Lawrence Berkeley National Laborat↗

Nano-array integrated monolithic devices: toward rational materials design and multi-functional performance by scalable nanostructures assembly

We report the scalable three-dimensional (3-D) integration of functional nanostructures into applicable platforms represents a promising technology to meet the ever-increasing demands of fabricating high performance devices featuring cost-effectiveness, structural sophistication and multi-functional enabling. Such an integration process generally involves a diverse array of nanostructural entities (nano-entities) consisting of dissimilar nanoscale building blocks such as nanoparticles, nanowires, and nanofilms made of metals, ceramics, or polymers. Various synthetic strategies and integration methods have enabled the successful assembly of both structurally and functionally tailored nano-arrays into a unique class of monolithic devices. The performance of nano-array based monolithic devices is dictated by a few important factors such as materials substrate selection, nanostructure composition and nano-architecture geometry. Therefore, the rational material selection and nano-entity manipulation during the nano-array integration process, aiming to exploit the advantageous characteristics of nanostructures and their ensembles, are critical steps towards bridging the design of nanostructure integrated monolithic devices with various practical applications. In this article, we highlight the latest research progress of the two-dimensional (2-D) and 3-D metal and metal oxide based nanostructural integrations into prototype devices applicable with ultrahigh efficiency, good robustness and improved functionality. Lastly, selective examples of nano-array integration, scalable nanomanufacturing and representative monolithic devices such as catalytic converters, sensors and batteries will be utilized as the connecting dots to display a roadmap from hierarchical nanostructural assembly to practical nanotechnology implications ranging from energy, environmental, to chemical and biotechnology areas.

36 MATERIALS SCIENCE↗

Economically sustainable scaling of photovoltaics to meet climate targets

To meet climate targets, power generation capacity from photovoltaics (PV) in 2030 will have to be much greater than is predicted from either steady state growth using today's manufacturing capacity or industry roadmaps. Analysis of whether current technology can scale, in an economically sustainable way, to sufficient levels to meet these targets has not yet been undertaken, nor have tools to perform this analysis been presented. Here, we use bottom-up cost modeling to predict cumulative capacity as a function of technological and economic variables. We find that today's technology falls short in two ways: profits are too small relative to upfront factory costs to grow manufacturing capacity rapidly enough to meet climate targets, and costs are too high to generate enough demand to meet climate targets. We show that decreasing the capital intensity (capex) of PV manufacturing to increase manufacturing capacity and effectively reducing cost (e.g., through higher efficiency) to increase demand are the most effective and least risky ways to address these barriers to scale. We also assess the effects of variations in demand due to hard-to-predict factors, like public policy, on the necessary reductions in cost.Lastly, we review examples of redundant technology pathways for crystalline silicon PV to achieve the necessary innovations in capex, performance, and price.

14 SOLAR ENERGY↗

A Review of Crystalline Silicon Bifacial Photovoltaic Performance Characterisation and Simulation

Bifacial photovoltaic (PV) technology has received considerable attention in recent years due to the potential to achieve higher annual energy yield compared to its monofacial counterpart. Higher annual energy yield is a crucial factor (even more than to further reduce the module costs) because, with the use of higher power PV modules, the high BOS (Balance of System) costs can be reduced, resulting in the lowest LCOE (levelised cost of energy). The International Technology Roadmap for Photovoltaic (ITRPV) predicts an upward trend for the shares of crystalline silicon (c-Si) bifacial PV cells and modules in the global PV market in the next decade, i.e., more than 35% in 2028. Two key enabling factors have been identified to promote the widespread use of c-Si bifacial PV devices, namely the bifacial PV performance measurement method/standard for indoor characterisation and comprehensive simulation models for outdoor performance characterisation. Both will increase the bankability of bifacial PV technology. In this paper, a comprehensive review of the state-of-the-art of the c-Si bifacial PV performance characterisation and simulation is presented. First, an overview of the indoor characterisation of c-Si bifacial PV cells and modules is presented, followed by an overview of the outdoor characterisation of c-Si bifacial PV modules and the draft technical specification, IEC TS 60904-1-2. The second part of this paper reviews the current status of bifacial PV performance modelling, which includes the three primary sub-models: optical, electrical, and thermal models. This paper also provides an overview of the required future research to address the challenges associated with the characterisation and simulation of c-Si bifacial PV devices.

14 SOLAR ENERGY↗

Colloidal quantum wells for optoelectronic devices

Colloidal quantum wells, also called nanoplatelets, are nanoscopic materials displaying quantum confinement in two dimensions. Unlike colloidal quantum dots, colloidal quantum well ensembles have no inhomogeneous broadening due to an atomically-precise definition of the short axis, a fact which results in much narrower ensemble absorption and emission. Thus, colloidal quantum wells can translate many advantages of colloidal nanocrsytals or other solution-processable materials, such as scalable synthesis and substrate-agnostic deposition (particularly compared to epitaxial quantum wells), without sacrificing material uniformity. Furthermore, due to very narrow photoluminescnece peaks, these materials have found a home in applications involving light emission, such as downconversion enhancement films, light-emitting diodes, and lasers, in which they represent some of the best performers among solution-cast materials. As argued in this review, the full spectrum of epitaxial quantum well devices offers a roadmap to other potential applications, such as detection, electronics, electro-optics, non-linear optics, or intersubband devices, in which only nascent efforts have been made.

36 MATERIALS SCIENCE↗

Colloidal quantum dot based infrared detectors: extending to the mid-infrared and moving from the lab to the field

Quantum dots (QDs) that absorb in the mid-wave infrared (MWIR) regime (3–5 μm) have recently generated significant interest as possible detector materials for MWIR cameras, with promises to reduce materials and device fabrication costs and potentially increase device operating temperatures. However, these materials have been primarily explored in single pixel devices – not multi-pixel cameras – and their current performance lags behind that of commercially available MWIR cameras based on single crystalline materials. To realize the potential of QD MWIR photodetectors with imaging capabilities, improvements are needed in the quality of the MWIR-absorbing QD materials, ligands dictating inter-QD charge transport, ordering of QD films, device architectures, and scalability of these methods to larger areas. With three families of QDs being researched – lead-, silver-, and mercury-based chalcogenides – as well as a multitude of possible capping ligands and film deposition techniques, the experimental phase space for MWIR QDs is vast. Here, we provide a roadmap, considering the pros and cons of various film deposition and ligand exchange techniques, as well as reintroduce lessons learned over years of research on QD film formation. We also extracted and created a database of reported quantum dot photodetectors’ performance and fabrication methods and have developed an interactive data visualization dashboard for this database, which provides researchers in the field a quick snapshot of the existing state of the art. Finally, we outline figures of merit and information that should be presented in papers moving forward which would help to clarify the reported results, as well as offer ideas for future steps. We provide a database visualization of the QD photodetector literature at https://public.tableau.com/app/profile/tom.nakotte/viz/IRQDphotodetectors_16384709473480/Dashboard1#1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid scalable fabrication of roll-to-roll slot-die coated flexible perovskite solar cells using intense pulse light annealing

Perovskite solar cells have achieved high efficiencies at the lab scale using batch processes that often may not be scalable. Processes that can be integrated into a continuous manufacturing platform, such as roll-to-roll, where several processes can be carried out sequentially are necessary to develop a new cost-competitive solar technology. In this work, intense pulsed light thermal post-processing is coupled with scalable slot-die coating and air knife evaporation in a high-speed roll-to-roll process of up to 2 m min –1 . The optimization of IPL energy parameters, web speeds, solution flow rates, and concentration of precursor inks yielded a champion power conversion efficiency of 11.24% for a 1 cm 2 roll-to-roll coated device. The overall processing time for a single layer in this process is reduced from minutes to seconds and the overall footprint of the manufacturing process is decreased. Furthermore, this demonstrates the promising capabilities for intensed pulsed light to reduce manufacturing costs and paves a roadmap for scalable and efficient PSCs on a roll-to-roll platform.

14 SOLAR ENERGY↗

Geologic hydrogen: a review of resource potential, subsurface dynamics, exploration, production, transportation, and research opportunities

Hydrogen is a versatile resource with critical roles in decarbonization, industrial manufacturing, and energy integration. However, most hydrogen today is produced from fossil fuels, resulting in high emissions and energy consumption. Although low-carbon hydrogen production methods, such as steam methane reforming with carbon capture and renewable-powered electrolysis, are advancing, their high costs hinder large-scale deployment. Identifying alternative pathways for producing low-cost, low-emission hydrogen is therefore essential. Geologic hydrogen, referring to natural and stimulated hydrogen generated in the Earth's subsurface, has attracted growing attention as a potential source of sustainable, economically viable, and environmentally favorable hydrogen. This paper provides a comprehensive review of geologic hydrogen, covering its resource potential, origins, migration and trapping mechanisms, exploration techniques, production strategies, and pipeline transportation. It also identifies key knowledge gaps and proposes a roadmap for future research. The review indicates that geologic hydrogen has vast resource potential and can leverage existing subsurface technologies and geophysical exploration methods. However, major challenges persist, including uncertain hydrogen generation rates, limited understanding and control of serpentinization processes, costly transportation infrastructure, the lack of validated techno-economic analysis, and potential social and environmental issues. As the field is still in its early stages, progress will require interdisciplinary collaboration spanning geoscience, engineering, economics, environmental science, and policy and regulation.

42 ENGINEERING↗

Navigating the Path to Autonomy: Real-World Lessons from an Air-Free Self-Driving Laboratory

While autonomous experimentation has promise to accelerate discovery in physcial sciences, the real-world integration of predictive models and experimentation is non-trivial. Here we describe the genesis of a self-driving laboratory (SDL) for air-sensitive chemistry at Argonne National Laboratory and demonstrate the experimental design considerations needed for high-throughput experiments before predictive models can lead to scientific discovery. Our SDL was designed to explore battery electrolyte stability. Our final SDL utilized plate readers in a glovebox with a nitrogen atmosphere to perform kinetic assays and screen hundreds of battery-relevant solvents. However, the roadmap to autonomy and airfree-friendly experimentation required the complex evaluation of several spectroscopic and chromatographic methods. The greatest experimental challenges were (a) developing long-term sampling methods that remained air-free; (b) accelerating kinetics to advance reactivity projections; and (c) ensuring labware compatibility with nonaqueous solvents used in battery chemistry. Our experiences highlight the practical gap between closed-loop aspirations and the realities of chemical discovery, offering lessons on the challenges of transferring every day laboratory workflows to autonomy. These results suggest a more realistic blueprint for autonomy in chemistry—one that balances thoughtful and realistic experimental formulation.

Robertson, Lily A.↗

Chapter 2: International Requirements for Large Integration of Renewable Energy Sources

Most European countries have concerns about the integration of large amounts of renewable energy sources (RES) into electric power systems, and this is currently a topic of growing interest. In January 2008, the European Commission published the 2020 package, which proposes committing the European Union to a 20% reduction in greenhouse gas emissions, to achieve a target of deriving 20% of the European Union's final energy consumption from renewable sources, and to achieve 20% improvement in energy efficiency both by the year 2020 [1]. Member states have different individual goals to meet these overall objectives, and they each need to provide a detailed roadmap describing how they will meet these legally binding targets [2]. At this time, RES are an indispensable part of the global energy mix, which has been partially motivated by the continuous increases in hydropower as well as the rapid expansion of wind and solar photovoltaic (PV). The International Energy Agency's 2012 edition of the World Energy Outlook stated that the rapid increases in RES integration are underpinned by falling technology costs as well as rising fossilfuel prices and carbon pricing, but RES integration is also encouraged by continued subsidies: from $88 billion globally in 2011 (compared to $523 billion in fossil-fuel subsidies in 2012 [3], with a share of $131 billion for electricity generation) to an estimated $240 billion in 2035 [4]. According to [3], in 2015 RES accounted for 22% of electricity generation, which was approximately the same level as gas and about one-half the level of coal.

24 POWER TRANSMISSION AND DISTRIBUTION↗

KiDS-1000 cosmology: Combined second- and third-order shear statistics

Aims.In this work, we perform the first cosmological parameter analysis of the fourth release of Kilo Degree Survey (KiDS-1000) data with second- and third-order shear statistics. This paper builds on a series of studies aimed at describing the roadmap to third-order shear statistics. Methods.We derived and tested a combined model of the second-order shear statistic, namely, the COSEBIs and the third-order aperture mass statistics 〈ℳ ap 3 〉 in a tomographic set-up. We validated our pipeline withN-body mock simulations of the KiDS-1000 data release. To model the second- and third-order statistics, we used the latest version of HMCODE2020 for the power spectrum and BIHALOFITfor the bispectrum. Furthermore, we used an analytic description to model intrinsic alignments and hydro-dynamical simulations to model the effect of baryonic feedback processes. Lastly, we decreased the dimension of the data vector significantly by considering only equal smoothing radii for the 〈ℳ ap 3 〉 part of the data vector. This makes it possible to carry out a data analysis of the KiDS-1000 data release using a combined analysis of COSEBIs and third-order shear statistics. Results.We first validated the accuracy of our modelling by analysing a noise-free mock data vector, assuming the KiDS-1000 error budget, finding a shift in the maximum of the posterior distribution of the matter density parameter, ΔΩ m < 0.02 σ Ω m , and of the structure growth parameter, ΔS 8 < 0.05 σ S 8 . Lastly, we performed the first KiDS-1000 cosmological analysis using a combined analysis of second- and third-order shear statistics, where we constrained Ω m = 0.248 −0.055 +0.062 andS 8 = σ 8 √(Ω m /0.3 )= 0.772 ± 0.022. The geometric average on the errors of Ω m andS 8 of the combined statistics decreases, compared to the second-order statistic, by a factor of 2.2.

Astronomy & Astrophysics↗

CLEANSPACE 'Small Debris Removal By Laser Illumination And Complementary Technologies'

Studies show that the number of debris in Low Earth Orbit is exponentially growing despite future debris release mitigation measures considered. Especially, the already existing population of small and medium debris (between 1 cm and several dozens of cm) is today a concrete threat to operational satellites. A ground based laser solution which can remove at low expense and in a non-destructive way hazardous debris of decimetric size around selected space assets appears as one highly promising answer. This solution will be studied in the frame of CLEANSPACE project which is a part of the FP7 space theme. The overall CLEANSPACE objective is threefold: to propose an efficient and affordable global system architecture, to tackle safety regulation aspects, political implications and future collaborations, to develop affordable technological bricks and to establish roadmap for the development and the future implantation of a fully functional laser protection system. This paper will present the CLEANSPACE project.

42 ENGINEERING↗

Metrology and Characterization Challenges for Emerging Research Materials and Devices

The International Technology Roadmap for Semiconductors (ITRS) Emerging Research Materials (ERM) and Emerging Research Devices (ERD) Technology Workgroups have identified materials and devices that could enable continued increases in the density and performance of future integrated circuit (IC) technologies and the challenges that must be overcome; however, this will require significant advances in metrology and characterization to enable progress. New memory devices and beyond CMOS logic devices operate with new state variables (e.g., spin, redox state, etc.) and metrology and characterization techniques are needed to verify their switching mechanisms and scalability, and enable improvement of operation of these devices. Similarly, new materials and processes are needed to enable these new devices. Additionally, characterization is needed to verify that the materials and their interfaces have been fabricated with required quality and performance.

36 MATERIALS SCIENCE↗

Prospects for advanced electron cyclotron resonance and electron beam ion source charge breeding methods for EURISOL

As the most ambitious concept of isotope separation on line (ISOL) facility, EURISOL aims at producing unprecedented intensities of post-accelerated radioactive isotopes. Charge breeding, which transforms the charge state of radioactive beams from 1+ to an n+ charge state prior to post-acceleration, is a key technology which has to overcome the following challenges: high charge states for high energies, efficiency, rapidity and purity. On the roadmap to EURISOL, a dedicated R and D is being undertaken to push forward the frontiers of the present state-of-the-art techniques which use either electron cyclotron resonance or electron beam ion sources. We describe here the guidelines of this R and D.

43 PARTICLE ACCELERATORS↗