Accounts of Chemical Research最新文献

Health professionals working in an interprofessional work environment are entrusted to speak up on behalf of patients. However, that environment is comprised of dynamic intra- and interprofessional hierarchies, characterized by power differentials that affect speaking up behaviors. Drawing on the social bases of power and on power/interaction theory, we analyzed focus group and interview transcripts of 62 health professionals' accounts of speaking up. We focused on their primary sources of power, and described factors associated with health professionals' embracing power to speak up for patient safety, as well as those associated with relinquishing power and remaining silent. Nurses primarily employed direct patient information as a source of power to advocate for patients. Senior nurses and attending physicians exercised their legitimate power through titles or expertise, and when embracing that power, often influenced the healthcare team's speaking up behaviors and the team environment. Physician trainees perceived to have limited sources of power. Participants reported using hospital policies, relationships, and humor for engaging in speaking up behavior. Relinquishing power and remaining silent were associated with fear, anxiety, and lack of confidence. Given the complex, hierarchical environment in healthcare, leaders' inclusive behaviors for setting a culture for speaking up, including modeling speaking up, are critical.

Organic electrosynthesis hasemerged as a powerfulplatform forsustainable molecular synthesis, while continuous-flow electrochemistryis often viewed primarily as a technology for process intensificationand scaleup. In our studies, however, we have found that the significanceof continuous-flow electrochemistry extends far beyond improved productivity.The unique reaction environments created by single-pass flow electrolysis─includingshort residence times, spatially evolving electrochemical conditions,efficient mass transfer, and distinctive electrode interfacial microenvironments─canfundamentally alter reaction outcomes and facilitate transformationsthat are difficult to achieve in conventional batch reactors.

In this Account, we summarize our efforts in developing continuous-flowelectrosynthesis as a synthetic platform for challenging oxidativemolecular transformations. We first show how single-pass flow electrolysissuppresses undesired secondary electrode reactions, enabling selectiveoxidative cyclizations, C–H oxygenation, and C–H aminationreactions. We then discuss how continuous-flow electrolysis expandsthe accessible reactivity space of electro-oxidation by promotingproductive utilization of highly reactive intermediates, exemplifiedby sulfur-centered radical chemistry and phosphorus radical cationchemistry. Particular emphasis is placed on electrochemical microenvironmentengineering, where local ion distributions and acid–base propertieswithin the electric double layer can be exploited to control reactivity.We further demonstrate how these concepts culminate in electro-oxidativeasymmetric catalysis, where continuous-flow electrolysis providesan expanded operational window for simultaneously optimizing electrochemicaland stereochemical parameters.

Finally, we describe the translationof these transformations fromlaboratory-scale reactions to continuous production through reactornumber-up and process integration. We anticipate that the next phaseof development in flow electrosynthesis will be driven as much byadvances in reactor engineering as by advances in synthetic methodology,ultimately enabling increasingly sophisticated continuous and electrifiedmanufacturing platforms.

Oxidative electrochemistry providesdirect access to highly reactiveintermediates under mild and sustainable conditions, yet controllingreactivity remains a central challenge in synthesis. In batch electrochemicalsystems, short-lived radicals, electrophilic oxidants, and cationicintermediates often undergo overoxidation, decomposition, or competingside reactions because of inefficient mass transfer and poor thermalcontrol. Continuous-flow electrochemistry addresses many of theselimitations by enabling rapid intermediate generation, efficient masstransport, precise residence-time control, and intensified reactionenvironments. In this Account, we describe how oxidative flow electrochemistrycan serve as a platform for controlling reactive intermediates throughselective generation and interception under continuous-flow conditions.Emphasis is placed on oxygen-centered radicals and reactive oxygenspecies, selenium electrophiles and radicals, electrophilic halogenand hypervalent iodine intermediates, heteroatom-centered oxidativecoupling processes, and stereoselective electrochemical transformationsthrough memory of chirality. Across these studies, a common principleemerges in which reaction selectivity is governed not only by thenature of the intermediate itself, but also by how fast and preciselyit is generated, transported, and trapped within the flow reactor.Mechanistic investigations, automation strategies, online analysis,and scalable electrochemical platforms further demonstrate how flowelectrochemistry enables a transition from empirical oxidative synthesistoward controllable and predictable reactive intermediate chemistry.Collectively, these studies establish oxidative flow electrochemistryas a versatile platform for reaction control and highlight its futurepotential in sustainable synthesis, asymmetric electrosynthesis, andautomated reaction development.

Scanning probe microscopy offers a powerful suite of techniquesfor investigating meso-, micro- and nanoscale phenomena ─ enablingthe exploration of advanced materials, heterostructures, quantum materials,as well as providing insight into surface energetics and reactions.Additional spectroscopic capabilities combined with multimodal imagingallow for spatially resolved characterization of functional materialproperties. Despite its central role, microscopy is still predominantlyconducted through a sequential, operator-driven workflow in whichdata acquisition, interpretation, and subsequent experimental decisionsoccur in discrete steps. This approach not only reduces experimentalthroughput but also limits the effective utilization of increasinglycomplex multimodal data sets, where critical information may remainunrecognized across real-time data streams.

Recent advancesin artificial intelligence (AI) and machine learning(ML) have enabled the concept of self-driving laboratories (SDL) whichpromise to accelerate scientific research by closing the loop betweendata acquisition, analysis, and experimental control. Within thisbroader paradigm, self-driving microscopy (SDM) has emerged as a powerfulapproach to overcome the limitations of traditional, operator-drivenmicroscopy workflows. In this Account, we discuss the evolution ofSDM from automated experimental platforms to fully autonomous systemscapable of adaptive, decision-driven operation. We highlight its implementationfor real-time data processing and optimization, feature identification,and strategies to efficiently explore across multidimensional parameterspaces. Advanced optimization strategies, including Bayesian optimizationand reinforcement learning, allow SDM systems to iteratively refineexperimental parameters based on prior observations, prioritizingmeasurements that maximize information gain. This adaptive approachreduces the total number of experiments required while improving theefficiency of exploration.

Collectively, we showcase how SDMaccelerates microscopy throughAI/ML integration, enables real-time analysis from high-dimensionaldata acquisition, while simultaneously guiding the experiments towarddiscovery. In addition to characterization, the autonomous workflowsallow for active material manipulation to create nanoscale artificialstructures on demand. We highlight that formalizing experimental strategiesinto algorithmic workflows enhances integration and scalability acrossinstruments and laboratories. These advances position SDM as a broadlyapplicable paradigm at the forefront of next-generation experimentalscience.