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Small-molecule receptors are increasingly employed to probe various functional groups for (bio)chemical analysis. However, differentiation of polyfunctional analogs sharing multiple functional groups remains challenging for conventional mono- and bidentate receptors because their insufficient number of binding sites limits interactions with the least reactive yet property-determining functional group. Herein, we introduce 6-thioguanine (TG) as a supramolecular receptor for unique tridentate receptor-analyte complexation, achieving ≥97 % identification accuracy among 16 polyfunctional analogs across three classes: glycerol derivatives, disubstituted propane, and vicinal diols. Crucially, we demonstrate distinct spectral changes induced by the tridentate interaction between TG's three anchoring points and all the analyte's functional groups, even the least reactive ones. Notably, hydrogen bond (H-bond) networks formed in the TG-analyte complexes demonstrate additive effects in binding strength originating from good bond linearity, cooperativity, and resonance, thus strengthening complexation events and amplifying the differences in spectral changes induced among analytes. It also enhances spectral consistency by selectively forming a sole configuration that is stronger than the respective analyte-analyte interaction. Finally, we achieve 95.4 % accuracy for multiplex identification of a mixture consisting of multiple polyfunctional analogs. We envisage that extension to other multidentate non-covalent interactions enables the development of interference-free small molecule-based sensors for various (bio)chemical analysis applications., (© 2024 Wiley-VCH GmbH.)

Competing Interests: Conflict-of-Interest Disclosures: Christopher Friese discloses receiving institutional grant funding from the National Cancer Institute, consulting fees from Vanderbilt University and the Leukemia and Lymphoma Society, and compensation from the Patient-Centered Outcomes Research Institute Board of Directors and the National Cancer Advisory Board. John Wong discloses receiving Board of Governors fees from Sidra Medicine. Sharon Inouye discloses institutional grant funding from the National Institutes of Health and the Patient-Centered Outcomes Research Institute.

Background: There is an urgency to retain nurses globally. Evidence has shown that nurse residency programs promote retention of new graduate nurses. However, there is a dearth of studies examining the impact of nurse residency programs longitudinally., Aim: To evaluate the impact of a transition-to-practice program on new graduate nurses' practice confidence and job satisfaction over 24 months., Design: A retrospective longitudinal study., Setting: A 1200-bed public tertiary academic hospital., Participants: New graduate nurses from local universities who joined the hospital and were enrolled in the Graduate Nurse Residency Program (n = 104)., Methods: The program was conducted for 24 months and consisted of modules on bedside knowledge and skills, and a mentorship program with senior nurse leaders. Practice confidence and job satisfaction were measured using the Casey-Fink graduate nurse experience survey. The survey was administered four times over the 24 months as part of the program. Data was analyzed using repeated measures ANOVA., Results: Practice confidence increased and job satisfaction decreased over the 24 months. Practice confidence total score at 6 months and an extended probation period were factors associated with attrition during the 24-month clinical practice., Conclusions: This is the first longitudinal study to demonstrate the impact of a transition-to-practice program in a multiethnic Asian setting. The Graduate Nurse Residency Program enhanced the practice confidence of new graduate nurses., Competing Interests: Declaration of competing interest None., (Copyright © 2023. Published by Elsevier Ltd.)

Speedy, point-of-need detection and monitoring of small-molecule metabolites are vital across diverse applications ranging from biomedicine to agri-food and environmental surveillance. Nanomaterial-based sensor (nanosensor) platforms are rapidly emerging as excellent candidates for versatile and ultrasensitive detection owing to their highly configurable optical, electrical and electrochemical properties, fast readout, as well as portability and ease of use. To translate nanosensor technologies for real-world applications, key challenges to overcome include ultralow analyte concentration down to ppb or nM levels, complex sample matrices with numerous interfering species, difficulty in differentiating isomers and structural analogues, as well as complex, multidimensional datasets of high sample variability. In this Perspective, we focus on contemporary and emerging strategies to address the aforementioned challenges and enhance nanosensor detection performance in terms of sensitivity, selectivity and multiplexing capability. We outline 3 main concepts: (1) customization of designer nanosensor platform configurations via chemical- and physical-based modification strategies, (2) development of hybrid techniques including multimodal and hyphenated techniques, and (3) synergistic use of machine learning such as clustering, classification and regression algorithms for data exploration and predictions. These concepts can be further integrated as multifaceted strategies to further boost nanosensor performances. Finally, we present a critical outlook that explores future opportunities toward the design of next-generation nanosensor platforms for rapid, point-of-need detection of various small-molecule metabolites., Competing Interests: The authors declare no competing interests., (This journal is © The Royal Society of Chemistry.)

Gas-phase surface-enhanced Raman scattering (SERS) remains challenging due to poor analyte affinity to SERS substrates. The reported use of capturing probes suffers from concurrent inconsistent signals and long response time due to the formation of multiple potential probe-analyte interaction orientations. Here, we demonstrate the use of multiple non-covalent interactions for ring complexation to boost the affinity of small gas molecules, SO 2 and NO 2 , to our SERS platform, achieving rapid capture and multiplex detection down to 100 ppm. Experimental and in-silico studies affirm stable ring complex formation, and kinetic investigations reveal a 4-fold faster response time compared to probes without stable ring complexation capability. By synergizing spectral concatenation and support vector machine regression, we achieve 91.7 % accuracy for multiplex quantification of SO 2 and NO 2 in excess CO 2 , mimicking real-life exhausts. Our platform shows immense potential for on-site exhaust and air quality surveillance., (© 2022 Wiley-VCH GmbH.)

Harnessing large hotspot volumes is key for enhanced gas-phase surface-enhanced Raman scattering (SERS) sensing. Herein, we introduce versatile, air-stable 3D 'Plasmonic bubbles' with bi-directional sensing capabilities. Our Plasmonic bubbles are robust, afford strong and homogenous SERS signals, and can swiftly detect both encapsulated and surrounding 4-methylbenzenethiol vapors.

Population-wide surveillance of COVID-19 requires tests to be quick and accurate to minimize community transmissions. The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. Our strategy strives to spur the development of next-generation, noninvasive human breath diagnostic toolkits tailored for mass screening purposes.

Integrating machine learning with surface-enhanced Raman scattering (SERS) accelerates the development of practical sensing devices. Such integration, in combination with direct detection or indirect analyte capturing strategies, is key to achieving high predictive accuracies even in complex matrices. However, in-depth understanding of spectral variations arising from specific chemical interactions is essential to prevent model overfit. Herein, we design a machine-learning-driven "SERS taster" to simultaneously harness useful vibrational information from multiple receptors for enhanced multiplex profiling of five wine flavor molecules at parts-per-million levels. Our receptors employ numerous noncovalent interactions to capture chemical functionalities within flavor molecules. By strategically combining all receptor-flavor SERS spectra, we construct comprehensive "SERS superprofiles" for predictive analytics using chemometrics. We elucidate crucial molecular-level interactions in flavor identification and further demonstrate the differentiation of primary, secondary, and tertiary alcohol functionalities. Our SERS taster also achieves perfect accuracies in multiplex flavor quantification in an artificial wine matrix.

Chiral differentiation is critical in diverse fields ranging from pharmaceutics to chiral synthesis. While surface-enhanced Raman scattering (SERS) offers molecule-specific vibrational information with high detection sensitivity, current strategies rely on indirect detection using additional selectors and cannot exploit SERS' key advantages for univocal and generic chiral differentiation. Here, we achieve direct, label-free SERS sensing of biologically important enantiomers by synergizing asymmetric nanoporous gold (NPG) nanoparticles with electrochemical-SERS to generate enantiospecific molecular fingerprints. Experimental and in silico studies reveal that chiral recognition is two pronged. First, the numerous surface atomic defects in NPG provide the necessary localized asymmetric environment to induce enantiospecific molecular adsorptions and interaction affinities. Concurrently, the applied potential drives and orients the enantiomers close to the NPG surface for maximal analyte-surface interactions. Notably, our strategy is versatile and can be readily extended to detect various enantiomers. Furthermore, we can achieve multiplex quantification of enantiomeric ratios with excellent predictive performance. Our combinatorial approach thus offers an important paradigm shift from current approaches to achieve label-free chiral SERS sensing of various enantiomers.

The electrochemical nitrogen reduction reaction (NRR) offers a sustainable solution towards ammonia production but suffers poor reaction performance owing to preferential catalyst-H formation and the consequential hydrogen evolution reaction (HER). Now, the Pt/Au electrocatalyst d-band structure is electronically modified using zeolitic imidazole framework (ZIF) to achieve a Faradaic efficiency (FE) of >44 % with high ammonia yield rate of >161 μg mg cat -1  h -1 under ambient conditions. The strategy lowers electrocatalyst d-band position to weaken H adsorption and concurrently creates electron-deficient sites to kinetically drive NRR by promoting catalyst-N 2 interaction. The ZIF coating on the electrocatalyst doubles as a hydrophobic layer to suppress HER, further improving FE by >44-fold compared to without ZIF (ca. 1 %). The Pt/Au-N ZIF interaction is key to enable strong N 2 adsorption over H atom., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Probing changes of noncovalent interactions is crucial to study the binding efficiencies and strengths of (bio)molecular complexes. While surface-enhanced Raman scattering (SERS) offers unique molecular fingerprints to examine such interactions in situ , current platforms are only able to recognize hydrogen bonds because of their reliance on manual spectral identification. Here, we differentiate multiple intermolecular interactions between two interacting species by synergizing plasmonic liquid marble-based SERS platforms, chemometrics, and density functional theory. We demonstrate that characteristic 3-mercaptobenzoic acid (probe) Raman signals have distinct peak shifts upon hydrogen bonding and ionic interactions with tert -butylamine, a model interacting species. Notably, we further quantify the contributions from each noncovalent interaction coexisting in different proportions. As a proof-of-concept, we detect and categorize biologically important nucleotide bases based on molecule-specific interactions. This will potentially be useful to study how subtle changes in biomolecular interactions affect their structural and binding properties.

Two-photon lithography (TPL) is an emerging approach to fabricate complex multifunctional micro/nanostructures. This is because TPL can easily develop various 2D and 3D structures on a variety of surfaces, and there has been a rapidly expanding pool of processable photoresists to create different materials. However, challenges in developing two-photon processable photoresists currently impede progress in TPL. In this review, we critically discuss the importance of photoresist formulation in TPL. We begin by evaluating the commercial photoresists to design micro/nanostructures for promising applications in anti-counterfeiting, superomniphobicity, and micromachines with movable parts. Next, we discuss emerging hydrogel/organogel photoresists, focusing on customizing photoresist formulations to fabricate reconfigurable structures that can respond to changes in local pH, solvent, and temperature. We also review the development of metal salt-based photoresists for direct metal writing, whereby various formulations have been developed to enable applications in online sensing, catalysis, and electronics. Finally, we provide a critical outlook and highlight various outstanding challenges in formulating processable photoresists for TPL.

Hybrid materials of earth abundant transition metal dichalcogenides and noble metal nanoparticles, such as molybdenum sulfide (MoS x ) and gold nanoparticles, exhibit synergistic effects that can enhance electrocatalytic reactions. However, most current hybrid MoS x -gold synthesis requires an energy intensive heat source of >500 °C or chemical plating to achieve deposition of MoS x on the gold surface. Herein, we demonstrate the direct overgrowth of MoS x over colloidal nanoporous gold (NPG), conducted feasibly under ambient conditions, to form hybrid particles with enhanced electrocatalytic performance toward hydrogen evolution reaction. Our strategy exploits the localized surface plasmon resonance-mediated photothermal heating of NPG to achieve >230 °C surface temperature, which induces the decomposition of the (NH 4 ) 2 MoS 4 precursor and direct overgrowth of MoS x over NPG. By tuning the concentration ratio between the precursor and NPG, the amount of MoS x particles deposited can be systematically controlled from 0.5% to 2% of the Mo/(Au + Mo) ratio. Importantly, we find that the hybrid particles exhibit higher bridging and an apical S to terminal S atomic ratio than pure molybdenum sulfide, which gives rise to their enhanced electrocatalytic performance for hydrogen evolution reaction. We demonstrate that hybrid MoS x -NPG exhibits >30 mV lower onset potential and a 1.7-fold lower Tafel slope as compared to pure MoS x . Our methodology provides an energy- and cost-efficient synthesis pathway, which can be extended to the synthesis of various functional hybrid structures with unique properties for catalysis and sensing applications.

Stand-off Raman spectroscopy combines the advantages of both Raman spectroscopy and remote detection to retrieve molecular vibrational fingerprints of chemicals at inaccessible sites. However, it is currently restricted to the detection of pure solids and liquids and not widely applicable for dispersed molecules in air. Herein, we realize real-time stand-off SERS spectroscopy for remote and multiplex detection of atmospheric airborne species by integrating a long-range optic system with a 3D analyte-sorbing metal-organic framework (MOF)-integrated SERS platform. Formed via the self-assembly of Ag@MOF core-shell nanoparticles, our 3D plasmonic architecture exhibits micrometer thick SERS hotspot to allow active sorption and rapid detection of aerosols, gas, and volatile organic compounds down to parts-per-billion levels, notably at a distance up to 10 m apart. The platform is highly sensitive to changes in atmospheric content, as demonstrated in the temporal monitoring of gaseous CO 2 in several cycles. Importantly, we demonstrate the remote and multiplex quantification of polycyclic aromatic hydrocarbon mixtures in real time under outdoor daylight. By overcoming core challenges in current remote Raman spectroscopy, our strategy creates an opportunity in the long-distance and sensitive monitoring of air/gaseous environment at the molecular level, which is especially important in environmental conservation, disaster prevention, and homeland defense.

Surface-enhanced Raman scattering (SERS) is a molecular-specific spectroscopic technique that provides up to 10 10 -fold enhancement of signature Raman fingerprints using nanometer-scale 0D to 2D platforms. Over the past decades, 3D SERS platforms with additional plasmonic materials in the z -axis have been fabricated at sub-micrometer to centimeter scale, achieving higher hotspot density in all x , y , and z spatial directions and higher tolerance to laser misalignment. Moreover, the flexibility to construct platforms in arbitrary sizes and 3D shapes creates attractive applications besides traditional SERS sensing. In this Account, we introduce our library of substrate-based and substrate-less 3D plasmonic platforms, with an emphasis on their non-sensing applications as microlaboratories and data storage labels. We aim to provide a scientific synopsis on these high-potential yet currently overlooked applications of SERS and ignite new scientific discoveries and technology development in 3D SERS platforms to tackle real-world issues. One highlight of our substrate-based SERS platforms is multilayered platforms built from micrometer-thick assemblies of plasmonic particles, which can achieve up to 10 11 enhancement factor. As an alternative, constructing 3D hotspots on non-plasmonic supports significantly reduces waste of plasmonic materials while allowing high flexibility in structural design. We then introduce our emerging substrate-less plasmonic capsules including liquid marbles and colloidosomes, which we further incorporate the latter within an aerosol to form centimeter-scale SERS-active plasmonic cloud, the world's largest 3D SERS platform to date. We then discuss the various emerging applications arising only from these 3D platforms, in the fields of sensing, microreactions, and data storage. An important novel sensing application is the stand-off detection of airborne analytes that are several meters away, made feasible with aerosolized plasmonic clouds. We also describe plasmonic capsules as excellent miniature lab-in-droplets that can simultaneously provide in situ monitoring at the molecular level during reaction, owing to their ultrasensitive 3D plasmonic shells. We highlight the emergence of 3D SERS-based data storage platforms with 10-100-fold higher storage density than 2D platforms, featuring a new approach in the development of level 3 security (L3S) anti-counterfeiting labels. Ultimately, we recognize that 3D SERS research can only be developed further when its sensing capabilities are concurrently strengthened. With this vision, we foresee the creation of highly applicable 3D SERS platforms that excel in both sensing and non-sensing areas, providing modern solutions in the ongoing Fourth Industrial Revolution.

Surface-enhanced Raman scattering (SERS) is a molecule-specific spectroscopic technique with diverse applications in (bio)chemistry, clinical diagnosis and toxin sensing. While hotspot engineering has expedited SERS development, it is still challenging to detect molecules with no specific affinity to plasmonic surfaces. With the aim of improving detection performances, we venture beyond hotspot engineering in this tutorial review and focus on emerging material design strategies to capture and confine analytes near SERS-active surfaces as well as various promising hybrid SERS platforms. We outline five major approaches to enhance SERS performance: (1) enlarging Raman scattering cross-sections of non-resonant molecules via chemical coupling reactions; (2) targeted chemical capturing of analytes through surface-grafted agents to localize them on plasmonic surfaces; (3) physically confining liquid analytes on non-wetting SERS-active surfaces and (4) confining gaseous analytes using porous materials over SERS hotspots; (5) synergizing conventional metal-based SERS platforms with functional materials such as graphene, semiconducting materials, and piezoelectric polymers. These approaches can be integrated with engineered hotspots as a multifaceted strategy to further boost SERS sensitivities that are unachievable using hotspot engineering alone. Finally, we highlight current challenges in this research area and suggest new research directions towards efficient SERS designs critical for real-world applications.

Gas-liquid reactions form the basis of our everyday lives, yet they still suffer poor reaction efficiency and are difficult to monitor in situ, especially at ambient conditions. Now, an inert gas-liquid reaction between aniline and CO 2 is driven at 1 atm and 298 K by selectively concentrating these immiscible reactants at the interface between metal-organic framework and solid nanoparticles (solid@MOF). Real-time reaction SERS monitoring and simulations affirm the formation of phenylcarbamic acid, which was previously undetectable because they are unstable for post-reaction treatments. The solid@MOF ensemble gives rise to a more than 28-fold improvement to reaction efficiency as compared to ZIF-only and solid-only platforms, emphasizing that the interfacial nanocavities in solid@MOF are the key to enhance the gas-liquid reaction. Our strategy can be integrated with other functional materials, thus opening up new opportunities for ambient-operated gas-liquid applications., (© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Nanoporous gold (NPG) promises efficient light-to-heat transformation, yet suffers limited photothermal conversion efficiency owing to the difficulty in controlling its morphology for the direct modulation of thermo-plasmonic properties. Herein, we showcase a series of shape-controlled NPG nanoparticles with distinct bowl- (NPG-B), tube- (NPG-T) and plate-like (NPG-P) structures for quantitative temperature regulation up to 140 °C in <1 s using laser irradiation. Notably, NPG-B exhibits the highest photothermal efficiency of 68%, which is >12 and 39 percentage points better than those of other NPG shapes (NPG-T, 56%; NPG-P, 49%) and Au nanoparticles (29%), respectively. We attribute NPG-B's superior photothermal performance to its >13% enhanced light absorption cross-section compared to other Au nanostructures. We further realize an ultrasensitive heat-mediated light-to-mechanical "kill switch" by integrating NPG-B with a heat-responsive shape-memory polymer (SMP/NPG-B). This SMP/NPG-B hybrid is analogous to a photo-triggered mechanical arm, and can be activated swiftly in <4 s simply by remote laser irradiation. Achieving remotely-activated "kill switch" is critical in case of emergencies such as gas leaks, where physical access is usually prohibited or dangerous. Our work offers valuable insights into the structural design of NPG for optimal light-to-heat conversion, and creates opportunities to formulate next-generation smart materials for on-demand and multi-directional responsiveness.

Molecular-level airborne sensing is critical for early prevention of disasters, diseases, and terrorism. Currently, most 2D surface-enhanced Raman spectroscopy (SERS) substrates used for air sensing have only one functional surface and exhibit poor SERS-active depth. "Aerosolized plasmonic colloidosomes" (APCs) are introduced as airborne plasmonic hotspots for direct in-air SERS measurements. APCs function as a macroscale 3D and omnidirectional plasmonic cloud that receives laser irradiation and emits signals in all directions. Importantly, it brings about an effective plasmonic hotspot in a length scale of approximately 2.3 cm, which affords 100-fold higher tolerance to laser misalignment along the z-axis compared with 2D SERS substrates. APCs exhibit an extraordinary omnidirectional property and demonstrate consistent SERS performance that is independent of the laser and analyte introductory pathway. Furthermore, the first in-air SERS detection is demonstrated in stand-off conditions at a distance of 200 cm, highlighting the applicability of 3D omnidirectional plasmonic clouds for remote airborne sensing in threatening or inaccessible areas., (© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Electrochemical nitrogen-to-ammonia fixation is emerging as a sustainable strategy to tackle the hydrogen- and energy-intensive operations by Haber-Bosch process for ammonia production. However, current electrochemical nitrogen reduction reaction (NRR) progress is impeded by overwhelming competition from the hydrogen evolution reaction (HER) across all traditional NRR catalysts and the requirement for elevated temperature/pressure. We achieve both excellent NRR selectivity (~90%) and a significant boost to Faradic efficiency by 10 percentage points even at ambient operations by coating a superhydrophobic metal-organic framework (MOF) layer over the NRR electrocatalyst. Our reticular chemistry approach exploits MOF's water-repelling and molecular-concentrating effects to overcome HER-imposed bottlenecks, uncovering the unprecedented electrochemical features of NRR critical for future theoretical studies. By favoring the originally unfavored NRR, we envisage our electrocatalytic design as a starting point for high-performance nitrogen-to-ammonia electroconversion directly from water vapor-abundant air to address increasing global demand of ammonia in (bio)chemical and energy industries.

Timely detection of toxic vapor is vital for safeguarding people's lives. Herein, we design a plasmonic nose based on a zeolitic imidazolate framework (ZIF)-encapsulated Ag nanocube array for ultratrace recognition of VOC vapor. The plasmonic nose enables in situ adsorption kinetics and recognition of various VOCs at ppm levels, eliminating false positives. Our approach provides a paradigm shift to next-generation, effective and specific gas sensors.

The application of aluminum (Al)-based nanostructures for visible-range plasmonics, especially for surface-enhanced Raman scattering (SERS), currently suffers from inconsistent local electromagnetic field distributions and/or inhomogeneous distribution of probe molecules. Herein, we lithographically fabricate structurally uniform Al nanostructures which enable homogeneous adsorption of various probe molecules. Individual Al nanostructures exhibit strong local electromagnetic field enhancements, in turn leading to intense SERS activity. The average SERS enhancement factor (EF) for individual nanostructures exceeds 10 4 for non-resonant probe molecules in the visible spectrum. These Al nanostructures also retain more than 70% of their original SERS intensities after one-month storage, displaying superb stability under ambient conditions. We further achieve tunable polarization-dependent SERS responses using anisotropic Al nanostructures, facilitating the design of sophisticated SERS-based security labels. Our micron-sized security label comprises two-tier security features, including a machine-readable hybrid quick-response (QR) code overlaid with a set of ciphertexts. Our work demonstrates the versatility of Al-based structures in low-cost modern chemical nano-analytics and forgery protection.

Miniaturizing the continuous multistep operations of a factory into a microchemical plant offers a safe and cost-effective approach to promote high-throughput screening in drug development and enforcement of industrial/environmental safety. While particle-assembled microdroplets in the form of liquid marble are ideal as microchemical plant, these platforms are mainly restricted to single-step reactions and limited to ex situ reaction monitoring. Herein, we utilize plasmonic liquid marble (PLM), formed by encapsulating liquid droplet with Ag nanocubes, to address these issues and demonstrate it as an ideal microchemical plant to conduct reaction-and-detection sequences on-demand in a nondisruptive manner. Utilizing a two-step azo-dye formation as our model reaction, our microchemical plant allows rapid and efficient diazotization of nitroaniline to form diazonium nitrobenzene, followed by the azo coupling of this intermediate with target aromatic compound to yield azo-dye. These molecular events are tracked in situ via SERS measurement through the plasmonic shell and further verified with in silico investigation. Furthermore, we apply our microchemical plant for ultrasensitive SERS detection and quantification of bisphenol A (BPA) with detection limit down to 10 amol, which is 50 000-fold lower than the BPA safety limit. Together with the protections offered by plasmonic shell against external environments, these collective advantages empower PLM as a multifunctional microchemical plant to facilitate small-volume testing and optimization of processes relevant in industrial and research contexts.

We demonstrate a one-step precise direct metal writing of well-defined and densely packed gold nanoparticle (AuNP) patterns with tunable physical and optical properties. We achieve this by using two-photon lithography on a Au precursor comprising poly(vinylpyrrolidone) (PVP) and ethylene glycol (EG), where EG promotes higher reduction rates of Au(III) salt via polyol reduction. Hence, clusters of monodisperse AuNP are generated along raster scanning of the laser, forming high-particle-density, well-defined structures. By varying the PVP concentration, we tune the AuNP size from 27.3 to 65.0 nm and the density from 172 to 965 particles/μm 2 , corresponding to a surface roughness of 12.9 to 67.1 nm, which is important for surface-based applications such as surface-enhanced Raman scattering (SERS). We find that the microstructures exhibit an SERS enhancement factor of >10 5 and demonstrate remote writing of well-defined Au microstructures within a microfluidic channel for the SERS detection of gaseous molecules. We showcase in situ SERS monitoring of gaseous 4-methylbenzenethiol and real-time detection of multiple small gaseous species with no specific affinity to Au. This one-step, laser-induced fabrication of AuNP microstructures ignites a plethora of possibilities to position desired patterns directly onto or within most surfaces for the future creation of multifunctional lab-on-a-chip devices.

We demonstrate a molecular-level observation of driving CO 2 molecules into a quasi-condensed phase on the solid surface of metal nanoparticles (NP) under ambient conditions of 1 bar and 298 K. This is achieved via a CO 2 accumulation in the interface between a metal-organic framework (MOF) and a metal NP surface formed by coating NPs with a MOF. Using real-time surface-enhanced Raman scattering spectroscopy, a >18-fold enhancement of surface coverage of CO 2 is observed at the interface. The high surface concentration leads CO 2 molecules to be in close proximity with the probe molecules on the metal surface (4-methylbenzenethiol), and transforms CO 2 molecules into a bent conformation without the formation of chemical bonds. Such linear-to-bent transition of CO 2 is unprecedented at ambient conditions in the absence of chemical bond formation, and is commonly observed only in pressurized systems (>10 5 bar). The molecular-level observation of a quasi-condensed phase induced by MOF coating could impact the future design of hybrid materials in diverse applications, including catalytic CO 2 conversion and ambient solid-gas operation.

Liquid marbles are emergent microreactors owing to their isolated environment and the flexibility of materials used. Plasmonic liquid marbles (PLMs) are demonstrated as the smallest spectroelectrochemical microliter-scale reactor for concurrent spectro- and electrochemical analyses. The three-dimensional Ag shell of PLMs are exploited as a bifunctional surface-enhanced Raman scattering (SERS) platform and working electrode for redox process modulation. The combination of SERS and electrochemistry (EC) capabilities enables in situ molecular read-out of transient electrochemical species, and elucidate the potential-dependent and multi-step reaction dynamics. The 3D configuration of our PLM-based EC-SERS system exhibits 2-fold and 10-fold superior electrochemical and SERS performance than conventional 2D platforms. The rich molecular-level electrochemical insights and excellent EC-SERS capabilities offered by our 3D spectroelectrochemical system are pertinent in charge transfer processes., (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Aim: Develop and test an instrument to measure graduate-nurses' perceptions of a structured mentorship program., Background: New graduate nurses may experience difficulties in the transition from student to practitioner. Mentoring is commonly used to support graduates. However, there is a lack of published tools measuring graduate nurses' perceptions of mentorship. As mentoring is resource intensive, development and testing of a validated tool are important to assist in determining program effectiveness., Methods: A pretest-posttest interventional design was used. Following a critical review of literature and content experts' input, the 10-item National University Hospital Mentorship Evaluation (NUH ME) instrument was tested with a convenience sample of 83 graduate nurses. Psychometric tests included internal reliability, stability, content validity, and factor analysis. Changed scores were evaluated using paired samples t-test., Results: Seventy-three graduates (88%) out of a possible 83 completed the pre-and post-program survey. Internal reliability was excellent with a Cronbach's alpha of 0.92. Test-retest reliability was stable over time (ICC=0.81). Exploratory factor analysis supported a 1-factor solution explaining 58.2% of variance. Paired samples t-test showed statistical significance between the pre- and post-program scores (p<0.001)., Conclusions: The NUH-ME measure was found to be valid and reliable. Confirmatory Factor Analysis of the tool with different groups of nursing graduates is required. Mentorship programs can be an effective recruitment and retention strategy, but are also resource intensive. Measuring new graduates' perceptions of mentoring contributes to program relevance in addressing their personal, professional and clinical skill development needs. As mentoring engages a diverse range of mentors, feedback through measurement may also positively alter organizational learning culture., (Copyright © 2017. Published by Elsevier Ltd.)