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Chen, Yan

Publications and source records attributed to Chen, Yan.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Towards Digital and Performance-Based Supervisory HVAC Control Delivery

Upgrading supervisory HVAC control in commercial buildings is one of the most attractive decarbonization tools at our disposal. Modern controls are software programs and can in theory be deployed at scale and with a low up-front carbon "pulse". In practice, however, control delivery is a disjointed and inefficient process, dominated by manual handoffs of imprecise English language documents. A particularly high barrier exists between control implementation and building energy modeling (BEM) which results in control sequences typically not being tested for correctness or performance before implementation. Together with industry partners, DOE and the national labs are developing an ecosystem of tools and standards that can support fully digital performance-based control delivery workflows. This paper describes this ecosystem, which consists of three mutually supportive efforts. Semantic models of buildings and their systems enable automatic configuration and installation of control software. Platform-neutral control descriptions separate control algorithms from control platforms and enable the creation of libraries of reference control implementations. Dynamic whole-building energy-control simulation that can execute physically realistic control sequences makes it possible to test and evaluate the performance of control sequences and then directly compile them for installation and execution in control systems. In addition to digitizing and streamlining project-level control delivery, these standards and related software support benchmarking of control algorithms, both rule-based and optimization-based, and help to both advance the state of the art and to implement ratings and programs that encourage the adoption of high-performance control.

building controls↗
DOE OSTI2022

An automated liquid jet for fluorescence dosimetry and microsecond radiolytic labeling of proteins

X-ray radiolytic labeling uses broadband X-rays for in situ hydroxyl radical labeling to map protein interactions and conformation. High flux density beams are essential to overcome radical scavengers. However, conventional sample delivery environments, such as capillary flow, limit the use of a fully unattenuated focused broadband beam. An alternative is to use a liquid jet, and we have previously demonstrated that use of this form of sample delivery can increase labeling by tenfold at an unfocused X-ray source. Here we report the first use of a liquid jet for automated inline quantitative fluorescence dosage characterization and sample exposure at a high flux density microfocused synchrotron beamline. Our approach enables exposure times in single-digit microseconds while retaining a high level of side-chain labeling. This development significantly boosts the method’s overall effectiveness and efficiency, generates high-quality data, and opens up the arena for high throughput and ultrafast time-resolved in situ hydroxyl radical labeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Compositional and structural control in LLZO solid electrolytes

Garnet-based solid-state electrolytes (SSEs) represent a promising class of materials for next-generation batteries with improved safety and performance. However, lack of control over the composition and crystal structure of the well-known Li 7 La 3 Zr 2 O 12 (LLZO) garnet material has led to poor reproducibility with a wide range of ionic conductivities reported in the literature. In this study, the role of precursor homogeneity in controlling the compositional and structural evolution of Al-doped LLZO is explored. A novel solution-based synthesis approach is employed to demonstrate enhanced atomic-scale mixing of the starting materials in comparison to conventional solid-state preparation methods. Through this technique, it is shown that the stability and formation temperature of the highly conductive cubic phase is directly impacted by the spatial distribution of the doping element and reactant species in the precursor mixture. Precursor homogeneity was also an important factor in mitigating the formation of unwanted secondary impurities. These findings can be used to guide the synthesis of SSEs with reproducible material characteristics and enhanced electrolytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Strong yet ductile nanolamellar high-entropy alloys by additive manufacturing

Additive manufacturing produces net-shaped components layer by layer for engineering applications. The additive manufacture of metal alloys by laser powder bed fusion (L-PBF) involves large temperature gradients and rapid cooling, which enables microstructural refinement at the nanoscale to achieve high strength. However, high-strength nanostructured alloys produced by laser additive manufacturing often have limited ductility. In this work, we use L-PBF to print dual-phase nanolamellar high-entropy alloys (HEAs) of AlCoCrFeNi 2.1 that exhibit a combination of a high yield strength of about 1.3 gigapascals and a large uniform elongation of about 14 percent, which surpasses those of other state-of-the-art additively manufactured metal alloys. The high yield strength stems from the strong strengthening effects of the dual-phase structures that consist of alternating face-centred cubic and body-centred cubic nanolamellae; the body-centred cubic nanolamellae exhibit higher strengths and higher hardening rates than the face-centred cubic nanolamellae. The large tensile ductility arises owing to the high work-hardening capability of the as-printed hierarchical microstructures in the form of dual-phase nanolamellae embedded in microscale eutectic colonies, which have nearly random orientations to promote isotropic mechanical properties. The mechanistic insights into the deformation behaviour of additively manufactured HEAs have broad implications for the development of hierarchical, dual- and multi-phase, nanostructured alloys with exceptional mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Chemical and structural evolutions of Li–Mn-rich layered electrodes at different current densities

Although the two active redox centers in Li-rich cathodes, including the anionic and cationic contributions, can enable Li-ion batteries to achieve outstanding specific energy, their behaviors at different current densities have not been clarified. In this report we provide a comparative study of transition metals (TMs) and oxygen redox activities by directly accessing their oxidation states in Li-rich materials operated at very different current rates. Our data reveal that the oxidation of oxygen in the near-surface region is at the same level for electrodes cycled with a wide range of current rates, indicating a reaction gradient of lattice oxygen redox reactions. The oxidation process of lattice oxygen is found to be dynamically compatible with that of the TMs. Combining the results of first principles calculations and complementary experimental findings, we propose a detailed mechanism of structural distortion from octahedral Li to tetrahedral Li and the role of oxygen vacancy in Li + diffusion. It is found that fast delithiation occurring at high current densities can easily cause local structural transformation, leading to a limited Li + diffusion rate and consequently suppressing rate capability.

25 ENERGY STORAGE↗
DOE OSTI2022

Construction of Women’s All-Around Speed Skating Event Performance Prediction Model and Competition Strategy Analysis Based on Machine Learning Algorithms

Introduction Accurately predicting the competitive performance of elite athletes is an essential prerequisite for formulating competitive strategies. Women’s all-around speed skating event consists of four individual subevents, and the competition system is complex and challenging to make accurate predictions on their performance. Objective The present study aims to explore the feasibility and effectiveness of machine learning algorithms for predicting the performance of women’s all-around speed skating event and provide effective training and competition strategies. Methods The data, consisting of 16 seasons of world-class women’s all-around speed skating competition results, used in the present study came from the International Skating Union (ISU). According to the competition rules, distinct features are filtered using lasso regression, and a 5,000 m race model and a medal model are built using a fivefold cross-validation method. Results The results showed that the support vector machine model was the most stable among the 5,000 m race and the medal models, with the highest AUC (0.86, 0.81, respectively). Furthermore, 3,000 m points are the main characteristic factors that decide whether an athlete can qualify for the final. The 11th lap of the 5,000 m, the second lap of the 500 m, and the fourth lap of the 1,500 m are the main characteristic factors that affect the athlete’s ability to win medals. Conclusion Compared with logistic regression, random forest, K-nearest neighbor, naive Bayes, neural network, support vector machine is a more viable algorithm to establish the performance prediction model of women’s all-around speed skating event; excellent performance in the 3,000 m event can facilitate athletes to advance to the final, and athletes with outstanding performance in the 500 m event are more likely competitive for medals.

Liu, Meng↗
DOE OSTI2022

Biosynthesis of polycyclopropanated high energy biofuels

Cyclopropane-functionalized hydrocarbons are excellent fuels due their high energy density. However, the organic synthesis of these molecules is challenging and harmful to the environment. In this work we produced polycyclopropanated fatty acids in bacteria. These molecules can be easily converted into renewable fuels for high energy applications such as shipping, long-haul transport, aviation, and rocketry. We explored the chemical diversity encoded in the genome of thousands of bacteria to identify and repurpose naturally occurring cyclopropanated molecules. We identified a set of candidate iterative polyketide synthases (iPKSs) predicted to produce polycyclopropanated fatty acids (POP-FAs), expressed these PKSs in Streptomyces coelicolor and produced the POP-FAs. We determined the structure of the molecules and increased their production 22-fold. Polycyclopropanated fatty acid methyl esters (POP-FAMEs) were obtained by methyl esterifying the POP-FAs. Finally, we calculated that our POP fuel candidates can have energy densities of more than 50 MJ/L. Our research shows that POP-FAMEs and other polyketide derived POPs have the energetic properties for energy-demanding applications for which sustainable alternatives are scarce.

09 BIOMASS FUELS↗
DOE OSTI2022

Elastic behavior of binary and ternary refractory multi-principal-element alloys

Elastic properties are essential to the mechanical performance of materials, and therefore, can be tuned to design high-performance materials. In this study, the elastic constants of the equiatomic ternary refractory multi-principal-element alloys, NbTiV, and MoNbV, were investigated, using in-situ neutron diffraction and first-principles calculations. The experimentally measured and theoretically predicted elastic constants show a good agreement. The alloying effect of adding Ti and Mo into NbV base alloy on the elastic constants is studied. Particularly, adding Ti elements into the NbV alloy results in the increase of the Zener anisotropy ratio from 0.59 to 0.99, leading to the formation of the elastically isotropic NbTiV alloy, while the addition of Mo decreases the anisotropy ratio to 0.52. Pugh’s ratio (B/G), Cauchy pressure (C 12 -C 44 ), and Poisson’s ratio (ν) are used to predict the brittle/ductile nature of the studied alloys, which is consistent with the mechanical results. The present work provides valuable insights into the design of ductile and strong refractory high-entropy alloys by tuning the elastic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

In-situ neutron diffraction investigation of two-stage martensitic transformation in a 13%Mn steel with serrated deformation

Two stage austenite →ε-martensite →α-martensite phase transformation, phase-specific lattice strain evolution and load sharing during tensile deformation of a 13%Mn hot-rolled austenitic steel are revealed by in-situ neutron diffraction. In conclusion, direct evidence is provided that serrated deformation behavior is attributed to discontinuous martensitic transformation.

Austenitic steel↗
DOE OSTI2022

Modular automated bottom-up proteomic sample preparation for high-throughput applications

Manual proteomic sample preparation methods limit sample throughput and often lead to poor data quality when thousands of samples must be analyzed. Automated liquid handler systems are increasingly used to overcome these issues for many of the sample preparation steps. Here, we detail a step-by-step protocol to prepare samples for bottom-up proteomic analysis for Gram-negative bacterial and fungal cells. The full modular protocol consists of three optimized protocols to: (A) lyse Gram-negative bacteria and fungal cells; (B) quantify the amount of protein extracted; and (C) normalize the amount of protein and set up tryptic digestion. These protocols have been developed to facilitate rapid, low variance sample preparation of hundreds of samples, be easily implemented on widely-available Beckman-Coulter Biomek automated liquid handlers, and allow flexibility for future protocol development. By using this workflow 50 micrograms of protein from 96 samples can be prepared for tryptic digestion in under an hour. We validate these protocols by analyzing 47 Pseudomonas putida and Rhodosporidium toruloides samples and show that this modular workflow provides robust, reproducible proteomic samples for high-throughput applications. The expected results from these protocols are 94 peptide samples from Gram-negative bacterial and fungal cells prepared for bottom-up quantitative proteomic analysis without the need for desalting column cleanup and with protein relative quantity variance (CV%) below 15%.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Review of the Use of Wearables in Indoor Environmental Quality Studies and an Evaluation of Data Accessibility from a Wearable Device

An understanding of indoor environmental quality (IEQ) and its effects on occupant well-being can inform building system design and operation. The use of wearables in field studies to collect subjective and objective health performance indicators (HPIs) from a large number of occupants could deliver important improvements in IEQ. To facilitate the use of wearables in IEQ studies, there is a need to identify which HPIs should be collected and to evaluate data accessibility from these devices. To address this issue, a literature review of previous IEQ studies was conducted to identify relationships between different IEQ factors and HPIs, with a focus on HPIs that were collected using wearables. A preliminary assessment of data accessibility from a selected wearable device (Fitbit Versa 2) was performed and documented. The review suggested the need to further investigate and collect sleep quality parameters, heart rate, stress response, as well as subjective ratings of comfort using wearables. The data accessibility assessment revealed issues related to missing data points and data resolution from the examined device. A set of recommendations is outlined to inform future studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Adaptive evolution of Methylotuvimicrobium alcaliphilum to grow in the presence of rhamnolipids improves fatty acid and rhamnolipid production from CH4

Abstract Rhamnolipids (RLs) are well-studied biosurfactants naturally produced by pathogenic strains of Pseudomonas aeruginosa. Current methods to produce RLs in native and heterologous hosts have focused on carbohydrates as production substrate; however, methane (CH4) provides an intriguing alternative as a substrate for RL production because it is low cost and may mitigate greenhouse gas emissions. Here, we demonstrate RL production from CH4 by Methylotuvimicrobium alcaliphilum DSM19304. RLs are inhibitory to M. alcaliphilum growth (<0.05 g/l). Adaptive laboratory evolution was performed by growing M. alcaliphilum in increasing concentrations of RLs, producing a strain that grew in the presence of 5 g/l of RLs. Metabolomics and proteomics of the adapted strain grown on CH4 in the absence of RLs revealed metabolic changes, increase in fatty acid production and secretion, alterations in gluconeogenesis, and increased secretion of lactate and osmolyte products compared with the parent strain. Expression of plasmid-borne RL production genes in the parent M. alcaliphilum strain resulted in cessation of growth and cell death. In contrast, the adapted strain transformed with the RL production genes showed no growth inhibition and produced up to 1 μM of RLs, a 600-fold increase compared with the parent strain, solely from CH4. This work has promise for developing technologies to produce fatty acid-derived bioproducts, including biosurfactants, from CH4.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Knowledge-based Framework for Building Energy Model Performance Verification

Building energy modeling (BEM) has been widely used by researchers, regulators, and engineers to quantify building energy performance. Quality assurance (QA) and quality control (QC) of the model's performance are essential parts of such analysis. Currently, QA/QC is done in a manual and ad-hoc manner, which is tedious, error-prone, and time-consuming when QA/QC a large number of models. To solve these challenges, we propose a a dAta-driveN buIlding perforMance verificATion framEwork (ANIMATE), which conducts automated output-based verification of building operations requirements (especially for time-series output-based verification of control requirements). While this framework was developed for verifying energy model performance, it can be extended for other applications such as BEM software testing and performance verification of real buildings in the field.

Chen, Yan↗
DOE OSTI2021

Unraveling transition-metal-mediated stability of spinel oxide via in situ neutron scattering

The energy materials performance is intrinsically determined by structures from the average lattice structure to the atom arrangement, valence, and distribution of the containing transition metal (TM) elements. Understanding the mechanism of the structure transition and atom rearrangement via synthesis or processing is key to expediting the exploration of excellent energy materials. In this work, in situ neutron scattering is employed to reveal the real-time structure evolution, including the TM-O bonds, lattice, TM valence and the migration of the high-voltage spinel cathode LiNi 0.5 Mn 1.5 O 4 . The transition-metal-mediated spinel destabilization under the annealing at the oxygen-deficient atmosphere is pinpointed. Additionally, the formation of Mn 3+ is correlated to the TM migration activation, TM disordered rearrangement in the spinel, and the transition to a layered-rocksalt phase. The further TM interdiffusion and Mn 2+ reduction are also revealed with multi-stage thermodynamics and kinetics. The mechanisms of phase transition and atom migrations as functions of temperature, time and atmosphere present important guidance on the synthesis in various-valence element containing oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Visualization of Solid-State Synthesis for Chalcogenide Na Superionic Conductors by in-situ Neutron Diffraction

Chalcogenide superionic sodium (Na) conductors are great potential as solid electrolytes (SEs) in all-solid-state Na batteries with advantages of high energy density and safety, and cost effectiveness. For solid Na-ion conductors, their crystal structures and ionically conductive properties are strongly influenced by the synthetic approaches and processing parameters. Thus, understanding the synthesis process is essential to control the structures and phases and thereby yields to Na-ion conductors with desirable properties. Thanks to the high-flux and deep-penetrating time-of-flight neutron diffraction (ND), we employed in situ experiments to track real-time structural changes of two chalcogenide SEs (Na 3 SbS 4 and Na 3 SbS 3.5 Se 0.5 ) during the solid-state synthesis. For these two conductors, the ND results reveal a fast one-step reaction for the synthesis and the molten process when heating up, and the recrystallization as well as the cubic-to-tetragonal phase transition up on cooling. Moreover, Se-doping is found to influence the reaction temperatures, lattice parameter and structure stability based on neutron experimental observations and theoretical simulation. This work presents a detailed structural study using in situ neutron diffraction technology for the solid synthesis process of chalcogenide Na-ion conductors, beneficial for the design and synthesis of new solid-state conductors.

25 ENERGY STORAGE↗