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At least 127 records · Page 7

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DOE OSTI2024

Evaluation of Aliphatic Alcohols for CO 2 Capture Using the Characteristic Carbonate Frequency

Control over CO 2 capture and utilization are important scientific and technological challenges. Although a variety of amine absorbents are used for capture, releasing the captured CO 2 is often difficult and limits their recyclability. Therefore, it is crucial to control the strength of the CO 2 bond with the absorbent. Furthermore, it is desirable to use a method that can conveniently report the strength of this bond. This motivates exploring adducts of CO 2 with alcohols in the presence of a base, using vibrational spectroscopy to report on the bond strength. Although reactions of alcohols with CO 2 to form alkyl carbonates are known, a systematic study of these adducts has not been conducted. Here we show formation of alkyl carbonates by a series of alcohols spanning the pK a range 9.5 to 16.8. We show experimental and computational results for the frequency of the characteristic asymmetric stretch of the carbonate and demonstrate that it correlates inversely with the pK a of the alcohol. Based on computations of the bond lengths and previous work, we propose that this frequency also correlates inversely with the adduct strength. As a result, this work extends the scope of CO 2 capture reagents and inspires further research in tuning alcohols as reversible absorbents.

Alcohols↗

DOE OSTI2023

Novel waste-derived non-noble metal catalysts to accelerate acidic and alkaline hydrogen evolution reaction

Carbon substrate support is a promising approach to facilitate catalytic activity of non-noble metal catalysts in hydrogen evolution reactions (HER). Here, in this paper, we report a waste-derived electrocatalyst P-CoNiO 2 @NC synthesized under mild condition. It exhibits outstanding HER performance in both acid (η 10 = 64.6 mV) and alkaline (η 10 = 96.4 mV) condition with good stability. Especially, it begins to outperform commercial Pt/C when the current density is over 74 mA/cm 2 in acid electrolyte and 29 mA/cm 2 in alkaline electrolyte. Moreover, the waste-derived carbon substrate could effectively promote HER activity of other dual 3d TMOs such as Fe and Co, Fe and Ni. The improved HER activity originates from electron transfer, electronic structure adjustment and optimization of intermediates adsorption according to X -ray photoelectron spectroscopy and density functional theory calculations. This work provides a new insight for converting wastes into value-added products and a sustainable and friendly strategy to facilitate hydrogen energy production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Assessing and advancing the potential of quantum computing: A NASA case study

Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy-intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. In this paper, we describe NASA’s work in assessing and advancing the potential of quantum computing. We discuss advances in algorithms, both near- and longer-term, and the results of our explorations on current hardware as well as with simulations, including illustrating the benefits of algorithm-hardware co-design in the NISQ era. This work also includes physics-inspired classical algorithms that can be used at application scale today. We discuss innovative tools supporting the assessment and advancement of quantum computing and describe improved methods for simulating quantum systems of various types on high-performance computing systems that incorporate realistic error models. We provide an overview of recent methods for benchmarking, evaluating, and characterizing quantum hardware for error mitigation, as well as insights into fundamental quantum physics that can be harnessed for computational purposes.

Rieffel, Eleanor G.↗

DOE OSTI2024

Grid connection barriers to renewable energy deployment in the United States

Bulk-power grid connection is an emerging bottleneck to the entry of wind, solar, and storage but has been understudied due to a lack of data. We create and analyze two novel interconnection datasets with more than 38,000 project-level observations that provide new information documenting interconnection challenges in the United States. Active grid connection requests are more than double the total installed capacity of the US power plant fleet (2,600 vs. 1,280 GW). The time required to secure a connection has increased by 70% over the last decade, and withdrawal rates remain high at 80%, suggesting a constrained transmission system that jeopardizes energy transition targets. Wide distributions of interconnection costs indicate the inherent uncertainty of the interconnection process. Interconnection requests that identify large transmission upgrades tend to withdraw from the process. These findings suggest the need for interconnection reforms, tighter links between long-term transmission planning and project-level interconnection processes, and more interconnection outcome transparency.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

AI-assisted optimization of the ECCE tracking system at the Electron Ion Collider

The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the “glue” that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5 T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Herein our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.