Electrochemical conversion of biomass-derived furanics for production of renewable chemicals and fuels

Replacing fossil-based fuels and chemicals with biobased alternatives can help alleviate our heavy dependence on petroleum sources, reduce the global carbon footprint, and strengthen our energy security. Electrocatalytic conversion of biomass-derived platform molecules is an emerging route for sustainable fuel and chemical production, with the advantages of eliminating harmful reagents, being tunable, and potentially being driven by renewable electricity. However, the widespread application of organic electrocatalysis is hindered by limitations such as low catalytic activity, product selectivity and energy efficiency. The goals of this work were to explore the electrochemical conversion of biobased furanics and develop more efficient electrocatalysts and processes for fuel and chemical production. The electrochemical reduction of furfural was investigated on metal electrodes in acidic aqueous electrolytes. Two mechanisms, namely electrocatalytic hydrogenation and direct electroreduction, were distinguished through a combination of voltammetry, bulk electrolysis, thiol-electrode modifications, and kinetic isotope effect studies. Better understanding of the underlying mechanisms and pathways enabled the manipulation of product selectivity. By rationally tuning applied potential, electrolyte pH, and bulk furfural concentration, the selective and efficient formation of a biofuel additive (i.e. 2-methylfuran) or a precursor for polymer and resin synthesis (i.e. furfuryl alcohol) was achieved. Pairing 5-(hydroxymethyl)furfural (HMF) reduction and oxidation half-reactions in a single electrochemical cell enabled efficient HMF conversion to biobased monomers. Electrocatalytic hydrogenation of HMF to 2,5-bis(hydroxymethyl)furan (BHMF) was achieved under mild conditions using Ag/C as the cathode catalyst. The competition between Ag-catalyzed HMF hydrogenation to BHMF and undesired HMF hydrodimerization and hydrogen evolution reactions was sensitive to cathode potential. Accordingly, precise control of the cathode potential was critical for achieving high BHMF selectivity and efficiency. In contrast, the selectivity of HMF oxidation facilitated by a homogeneous electrocatalyst, 4-acetamido-TEMPO (ACT, TEMPO = 2,2,6,6‐tetramethylpiperidine‐1‐oxyl), together with an inexpensive carbon felt electrode was not dependent on anode potential. Thus, it was feasible to conduct HMF hydrogenation to BHMF and oxidation to 2,5-furandicarboxylic acid (FDCA) in a single cathode-potential-controlled cell, achieving remarkable overall electron efficiency

An Operational Perspective to Fairness Interventions: Where and How to Intervene

As AI-based decision systems proliferate, their successful operationalization requires balancing multiple desiderata: predictive performance, disparity across groups, safeguarding sensitive group attributes (e.g., race), and engineering cost. We present a holistic framework for evaluating and contextualizing fairness interventions with respect to the above desiderata. The two key points of practical consideration are \emph{where} (pre-, in-, post-processing) and \emph{how} (in what way the sensitive group data is used) the intervention is introduced. We demonstrate our framework with a case study on predictive parity. In it, we first propose a novel method for achieving predictive parity fairness without using group data at inference time via distibutionally robust optimization. Then, we showcase the effectiveness of these methods in a benchmarking study of close to 400 variations across two major model types (XGBoost vs. Neural Net), ten datasets, and over twenty unique methodologies. Methodological insights derived from our empirical study inform the practical design of ML workflow with fairness as a central concern. We find predictive parity is difficult to achieve without using group data, and despite requiring group data during model training (but not inference), distributionally robust methods we develop provide significant Pareto improvement. Moreover, a plain XGBoost model often Pareto-dominates neural networks with fairness interventions, highlighting the importance of model inductive bias

Longitudinal Health Outcomes and Treatment Utilization Among Emerging, Early-Mid, and Older Rural Adults Using Stimulants

There is limited knowledge about age-related differences in health outcomes and treatment utilization among rural stimulant users. The current study examined physical health, mental health, and treatment utilization (hospital, mental health, and substance use care) among 710 stimulant users living in rural areas of the United States. Generalized estimating equations (GEE) were used to examine associations between age and physical health, mental health, and treatment utilization over a 3-year period. Analyses controlled for participants’ gender, race, and education. To capture age-related differences, participants were grouped into emerging adults (18–25 years old, n = 223), early-mid adults (26–44 years old; n = 384), and older adults (45–61 years old; n = 103). At baseline, older stimulant users were in significantly poorer health even though they had significantly fewer substance use problems than emerging adult users. GEE models indicated that substance use outcomes improved for all participants over the course of the study but other outcomes remained stable. Older stimulant users continued to have worse physical health and mental health, even though they had fewer substance use problems, than the other age groups. Older adults also used more hospital and mental health services than the other age groups. White participants tended to be at higher risk for negative outcomes than nonwhite participants. We conclude that rural older adults who use stimulants have poor health despite having milder substance use problems and using more health care resources, and need targeted intervention to improve health outcomes

Numerical Simulation of Temperature Field in Ultra-Narrow Arc Welding of Thick-Walled Steam Turbine Valve Body Material

The welding problems of large and thick plates are becoming more prominent as the application of large-scale and thick-plate metal structures grows. Due to the issue of excessive welding deformation between the 60mm thick steam turbine valve body and the pipe joint, a new process method is employed to connect. In this paper, the welding technology of flux strip confined arc ultra-narrow gap is proposed to carry out welding test on the ZG13Cr9Mo2Co1NiVNbNB cast steel test block of steam turbine valve body material with a thickness of 60 mm. The welding temperature field is measured by means of a K-type thermocouple and numerical simulation. The results show that the thermal cycle curve obtained by the homogeneous body heat source simulation is basically consistent with the thermal cycle curve measured during the experiment, and the simulation results of the molten pool morphology are also consistent with the actual macroscopic morphology of the weld

Numerical Simulation of Temperature Field in Ultra-Narrow Arc Welding of Thick-Walled Steam Turbine Valve Body Material

The welding problems of large and thick plates are becoming more prominent as the application of large-scale and thick-plate metal structures grows. Due to the issue of excessive welding deformation between the 60mm thick steam turbine valve body and the pipe joint, a new process method is employed to connect. In this paper, the welding technology of flux strip confined arc ultra-narrow gap is proposed to carry out welding test on the ZG13Cr9Mo2Co1NiVNbNB cast steel test block of steam turbine valve body material with a thickness of 60 mm. The welding temperature field is measured by means of a K-type thermocouple and numerical simulation. The results show that the thermal cycle curve obtained by the homogeneous body heat source simulation is basically consistent with the thermal cycle curve measured during the experiment, and the simulation results of the molten pool morphology are also consistent with the actual macroscopic morphology of the weld

Design and Application of Exclusive Service App for Rural Elderly

With the further advancement of rural development and the rapid development of mobile Internet, rural service apps have gradually become an important means of promoting rural economic development and improving farmers’ production and living standards. At present, a number of service-type apps with wide applications in the field of rural services have emerged, such as “Planting Master”, “Farming Network”, “Rural Taobao”, etc. However, these apps do not pay special attention to special groups, but only target the majority of young people and office workers. However, these apps do not pay special attention to special groups, but only target the majority of young people and office workers. In order to fill this gap, we have designed a software called Nong’e Tong, which is specially designed for the elderly and other special groups. The software has a simple and beautiful interface, and is easy to use. It not only provides a lot of special functions, but also can link the elderly’s cell phone with their children’s cell phones to check the health and safety of the elderly at any time. Compared to other software, the application has special features for seniors to ensure that they can use the application easily and quickly