In Situ X-ray Scattering Reveals Coarsening Rates of Superlattices Self-Assembled from Electrostatically Stabilized Metal Nanocrystals Depend Nonmonotonically on Driving Force.

Self-assembly of colloidal nanocrystals (NCs) into superlattices (SLs) is an appealing strategy to design hierarchically organized materials with promising functionalities. Mechanistic studies are still needed to uncover the design principles for SL self-assembly, but such studies have been difficult to perform due to the fast time and short length scales of NC systems. To address this challenge, we developed an apparatus to directly measure the evolving phases in situ and in real time of an electrostatically stabilized Au NC solution before, during, and after it is quenched to form SLs using small-angle X-ray scattering. By developing a quantitative model, we fit the time-dependent scattering patterns to obtain the phase diagram of the system and the kinetics of the colloidal and SL phases as a function of varying quench conditions. The extracted phase diagram is consistent with particles whose interactions are short in range relative to their diameter. We find the degree of SL order is primarily determined by fast (subsecond) initial nucleation and growth kinetics, while coarsening at later times depends nonmonotonically on the driving force for self-assembly. We validate these results by direct comparison with simulations and use them to suggest dynamic design principles to optimize the crystallinity within a finite time window. The combination of this measurement methodology, quantitative analysis, and simulation should be generalizable to elucidate and better control the microscopic self-assembly pathways of a wide range of bottom-up assembled systems and architectures.

Nonequilibrium design strategies for functional colloidal assemblies.

We use a nonequilibrium variational principle to optimize the steady-state, shear-induced interconversion of self-assembled nanoclusters of DNA-coated colloids. Employing this principle within a stochastic optimization algorithm allows us to identify design strategies for functional materials. We find that far-from-equilibrium shear flow can significantly enhance the flux between specific colloidal states by decoupling trade-offs between stability and reactivity required by systems in equilibrium. For isolated nanoclusters, we find nonequilibrium strategies for amplifying transition rates by coupling a given reaction coordinate to the background shear flow. We also find that shear flow can be made to selectively break detailed balance and maximize probability currents by coupling orientational degrees of freedom to conformational transitions. For a microphase consisting of many nanoclusters, we study the flux of colloids hopping between clusters. We find that a shear flow can amplify the flux without a proportional compromise on the microphase structure. This approach provides a general means of uncovering design principles for nanoscale, autonomous, functional materials driven far from equilibrium.

Development of a Week-Long Mathematics Intervention for Incoming Chemistry Graduate Students.

A student-led mathematics bootcamp has been designed and implemented to help foster community building, improve confidence in mathematical skills, and provide mathematical resources for incoming physical chemistry doctoral students. The bootcamp is held immediately before the start of the first semester of graduate school and uses an active learning approach to review and practice undergraduate-level mathematics problems over 5 days in small student groups. This work includes the development and presentation of a new, publicly available mathematics curriculum for the bootcamp on select mathematics topics, including calculus, linear algebra, functions, differential equations, statistics, and coding in Python, aiming at improving students' confidence and learning experiences in graduate quantum mechanics and statistical physics courses. Surveys before and after the bootcamp showed an increase in students' confidence in problem-solving in key mathematical areas and social aspects of peer-led group learning. Qualitative and quantitative analyses demonstrate that the bootcamp reduced prior inequities in students' confidence metrics based on gender and mathematical background.

Comparison of the Strengths and Weaknesses of Machine Learning Algorithms and Feature Selection on KEGG Database Microbial Gene Pathway Annotation and Its Effects on Reconstructed Network Topology.

The development of tools for the annotation of genes from newly sequenced species has not evolved much from homologous alignment to prior annotated species. While the quality of gene annotations continues to decline as we sequence and assemble more evolutionary distant gut microbiome species, machine learning presents a high quality alternative to traditional techniques. In this study, we investigate the relative performance of common classical and nonclassical machine learning algorithms in the problem of gene annotation using human microbiome-associated species genes from the KEGG database. The majority of the ensemble, clustering, and deep learning algorithms that we investigated showed higher prediction accuracy than CD-Hit in predicting partial KEGG function. Motif-based, machine-learning methods of annotation in new species were faster and had higher precision-recall than methods of homologous alignment or orthologous gene clustering. Gradient boosted ensemble methods and neural networks also predicted higher connectivity in reconstructed KEGG pathways, finding twice as many new pathway interactions than blast alignment. The use of motif-based, machine-learning algorithms in annotation software will allow researchers to develop powerful tools to interact with bacterial microbiomes in ways previously unachievable through homologous sequence alignment alone.

Self-assembly of nanocrystals into strongly electronically coupled all-inorganic supercrystals.

Colloidal nanocrystals of metals, semiconductors, and other functional materials can self-assemble into long-range ordered crystalline and quasicrystalline phases, but insulating organic surface ligands prevent the development of collective electronic states in ordered nanocrystal assemblies. We reversibly self-assembled colloidal nanocrystals of gold, platinum, nickel, lead sulfide, and lead selenide with conductive inorganic ligands into supercrystals exhibiting optical and electronic properties consistent with strong electronic coupling between the constituent nanocrystals. The phase behavior of charge-stabilized nanocrystals can be rationalized and navigated with phase diagrams computed for particles interacting through short-range attractive potentials. By finely tuning interparticle interactions, the assembly was directed either through one-step nucleation or nonclassical two-step nucleation pathways. In the latter case, the nucleation was preceded by the formation of two metastable colloidal fluids.

Exploiting Nanomaterials for Optical Coherence Tomography and Photoacoustic Imaging in Nanodentistry.

There is already a societal awareness of the growing impact of nanoscience and nanotechnology, with nanomaterials (with at least one dimension less than 100 nm) now incorporated in items as diverse as mobile phones, clothes or dentifrices. In the healthcare area, nanoparticles of biocompatible materials have already been used for cancer treatment or bioimaging enhancement. Nanotechnology in dentistry, or nanodentistry, has already found some developments in dental nanomaterials for caries management, restorative dentistry and orthodontic adhesives. In this review, we present state-of-the-art scientific development in nanodentistry with an emphasis on two imaging techniques exploiting nanomaterials: optical coherence tomography (OCT) and photoacoustic imaging (PAI). Examples will be given using OCT with nanomaterials to enhance the acquired imaging, acting as optical clearing agents for OCT. A novel application of gold nanoparticles and nanorods for imaging enhancement of incipient occlusal caries using OCT will be described. Additionally, we will highlight how the OCT technique can be properly managed to provide imaging with spatial resolution down to 10's-100's nm resolution. For PAI, we will describe how new nanoparticles, namely TiN, prepared by femtosecond laser ablation, can be used in nanodentistry and will show photoacoustic microscopy and tomography images for such exogenous agents.

Direct Evaluation of Rare Events in Active Matter from Variational Path Sampling.

Active matter represents a broad class of systems that evolve far from equilibrium due to the local injection of energy. Like their passive analogs, transformations between distinct metastable states in active matter proceed through rare fluctuations; however, their detailed balance violating dynamics renders these events difficult to study. Here, we present a simulation method for evaluating the rate and mechanism of rare events in generic nonequilibrium systems and apply it to study the conformational changes of a passive solute in an active fluid. The method employs a variational optimization of a control force that renders the rare event a typical one, supplying an exact estimate of its rate as a ratio of path partition functions. Using this method we find that increasing activity in the active bath can enhance the rate of conformational switching of the passive solute in a manner consistent with recent bounds from stochastic thermodynamics.

Enantioselective C-H Functionalization Reactions under Gold Catalysis.

Transition metal-catalyzed enantioselective functionalization of ubiquitous C-H bonds has proven to be promising field as it offers the construction of chiral molecular complexity in a step- and atom-economical manner. In recent years, gold has emerged as an attractive contender for catalyzing such reactions. The unique reactivities and selectivities offered by gold catalysts have been exploited to access numerous asymmetric transformations based on gold-catalyzed C-H functionalization processes. Herein, this review critically highlights the major advances and discoveries made in the enantioselective C-H functionalization under gold catalysis which is accompanied by mechanistic insights at appropriate places.

BEmoC: A Corpus for Identifying Emotion in Bengali Texts.

Emotion classification in text has growing interest among NLP experts due to the enormous availability of people's emotions and its emergence on various Web 2.0 applications/services. Emotion classification in the Bengali texts is also gradually being considered as an important task for sports, e-commerce, entertainments, and security applications. However, It is a very critical task to develop an automatic emotion classification system for low-resource languages such as, Bengali. Scarcity of resources and deficiency of benchmark corpora make the task more complicated. Thus, the development of a benchmark corpus is the prerequisite to develop an emotion classifier for Bengali texts. This paper describes the development of an emotional corpus (hereafter called 'BEmoC') for classifying six emotions in Bengali texts. The corpus development process consists of four key steps: data crawling, pre-processing, labelling, and verification. A total of 7000 texts are labelled into six basic emotion categories such as anger, fear, surprise, sadness, joy, and disgust, respectively. Dataset evaluation with 0.969 Cohen's κ score indicates the close agreement between the corpus annotators and the expert. The analysis of evaluation also represents that the distribution of emotion words obeys Zipf's law. Moreover, the results of BEmoC analysis shown in terms of coding reliability, emotion density, and most frequent emotion words, respectively.

Decision-making process for esthetic treatment of gummy smile: A surgical perspective.

Gummy smile is a quite frequently found esthetic alteration characterized by excessive display of gingiva during smiling. Several causes have been implicated in the literature, but a dearth of clinical decision-making process has been found in the surgical treatment of excessive gingival display. An external bevel gingivectomy with osseous correction was performed in anterior maxillary region in accordance with the proposed decision-making process. The clinical observation at 1 month postoperatively revealed restoration of natural smile with 1-2 mm of facial gingival display. The outcome seems to suggest that this proposed decision-making process can provide valid treatment options for gummy smile cases.

Reinforcement learning of rare diffusive dynamics.

We present a method to probe rare molecular dynamics trajectories directly using reinforcement learning. We consider trajectories that are conditioned to transition between regions of configuration space in finite time, such as those relevant in the study of reactive events, and trajectories exhibiting rare fluctuations of time-integrated quantities in the long time limit, such as those relevant in the calculation of large deviation functions. In both cases, reinforcement learning techniques are used to optimize an added force that minimizes the Kullback-Leibler divergence between the conditioned trajectory ensemble and a driven one. Under the optimized added force, the system evolves the rare fluctuation as a typical one, affording a variational estimate of its likelihood in the original trajectory ensemble. Low variance gradients employing value functions are proposed to increase the convergence of the optimal force. The method we develop employing these gradients leads to efficient and accurate estimates of both the optimal force and the likelihood of the rare event for a variety of model systems.

Evaluation of Pearson correlation coefficient and Parisi parameter of replica symmetry breaking in a hybrid electronically addressable random fiber laser.

The hybrid electronically addressable random (HEAR) laser is a novel type of random fiber laser that presents the remarkable property of selection of the fiber section with lasing emission. Here we present a joint analysis of the correlations between intensity fluctuations at distinct wavelengths and replica symmetry breaking (RSB) behavior of the HEAR laser. We introduce a modified Pearson coefficient that simultaneously comprises both the Parisi overlap parameter and standard Pearson correlation coefficient. Our results highlight the contrast between the correlations and presence or not of RSB phenomenon in the spontaneous emission behavior well below threshold, replica-symmetric ASE regime slightly below threshold, and RSB phase with random lasing emission above threshold. In particular, in the latter we find that the onset of RSB behavior is accompanied by a stochastic dynamics of the lasing modes, leading to competition for gain intertwined with correlation and anti-correlation between modes in this complex photonic phase.

Photoacoustic imaging of occlusal incipient caries in the visible and near-infrared range.

PURPOSE: This study aimed to demonstrate the presence of dental caries through a photoacoustic imaging system with visible and near-infrared wavelengths, highlighting the differences between the 2 spectral regions. The depth at which carious tissue could be detected was also verified. MATERIALS AND METHODS: Fifteen permanent molars were selected and classified as being sound or having incipient or advanced caries by visual inspection, radiography, and optical coherence tomography analysis prior to photoacoustic scanning. A photoacoustic imaging system operating with a nanosecond pulsed laser as the light excitation source at either 532 nm or 1064 nm and an acoustic transducer at 5 MHz was developed, characterized, and used. En-face and lateral (depth) photoacoustic signals were detected. RESULTS: The results confirmed the potential of the photoacoustic method to detect caries. At both wavelengths, photoacoustic imaging effectively detected incipient and advanced caries. The reconstructed photoacoustic images confirmed that a higher intensity of the photoacoustic signal could be observed in regions with lesions, while sound surfaces showed much less photoacoustic signal. Photoacoustic signals at depths up to 4 mm at both 532 nm and 1064 nm were measured. CONCLUSION: The results presented here are promising and corroborate that photoacoustic imaging can be applied as a diagnostic tool in caries research. New studies should focus on developing a clinical model of photoacoustic imaging applications in dentistry, including soft tissues. The use of inexpensive light-emitting diodes together with a miniaturized detector will make photoacoustic imaging systems more flexible, user-friendly, and technologically viable.

The interplay of carbophilic activation and Au(I)/Au(III) catalysis: an emerging technique for 1,2-difunctionalization of C-C multiple bonds.

Gold complexes have emerged as the catalysts of choice for various functionalization reactions of C-C multiple bonds due to their inherent carbophilic nature. In a parallel space, efforts to realize less accessible cross-coupling reactivity have led to the development of various strategies that facilitate the arduous Au(I)/Au(III) redox cycle. The interplay of the two important reactivity modes encountered in gold catalysis, namely carbophilic activation and Au(I)/Au(III) catalysis, has allowed the development of a novel mechanistic paradigm that sponsors 1,2-difunctionalization reactions of various C-C multiple bonds. Interestingly, the reactivity as well as selectivity obtained through this interplay could be complementary to that obtained by the use of various other transition metals that mainly involved the classical oxidative addition/migratory insertion pathways. The present review shall comprehensively cover all the 1,2-difunctionalization reactions of C-C multiple bonds that have been realized by the interplay of the two important reactivity modes and categorized on the basis of the method that has been employed to foster the Au(I)/Au(III) redox cycle.

Variational design principles for nonequilibrium colloidal assembly.

Using large deviation theory and principles of stochastic optimal control, we show that rare molecular dynamics trajectories conditioned on assembling a specific target structure encode a set of interactions and external forces that lead to enhanced stability of that structure. Such a relationship can be formulated into a variational principle, for which we have developed an associated optimization algorithm and have used it to determine optimal forces for targeted self-assembly within nonequilibrium steady-states. We illustrate this perspective on inverse design in a model of colloidal cluster assembly within linear shear flow. We find that colloidal clusters can be assembled with high yield using specific short-range interactions of tunable complexity. Shear decreases the yields of rigid clusters, while small values of shear increase the yields of nonrigid clusters. The enhancement or suppression of the yield due to shear is rationalized with a generalized linear response theory. By studying 21 unique clusters made of six, seven, or eight particles, we uncover basic design principles for targeted assembly out of equilibrium.

Nonlinear photoacoustic response of suspensions of laser-synthesized plasmonic titanium nitride nanoparticles.

A nonlinear photoacoustic (PA) response from solutions of 40 nm plasmonic titanium nitride nanoparticles (NPs) synthesized by laser ablation in a liquid environment (acetone) is reported. Using a photoacoustic Z-scan with 5 ns pumping pulses, values of effective nonlinear absorption (NLA) coefficients ßPA,eff were measured and found to be 3.27±0.17 × 10-8, 6.41±0.32 × 10-8, and 3.22±0.16 × 10-8 for 600, 700, and 800 nm pumping wavelengths, respectively. To take into account the influence of nonlinear scattering, absorption-dependent PA measurements were carried out together with the optical Z-scan, and the obtained data were compared. The origin of the effective absorptive nonlinearity is discussed based on combined NLA in NPs, nonlinear scattering, and bubble generation triggered by NP-mediated light absorption. Potential applications include biomedical diagnostics and therapy.

Hybrid electronically addressable random fiber laser.

We report here a novel architecture for a random fiber laser exploiting the combination of a semiconductor optical amplifier (SOA) and an erbium doped fiber (EDF). The EDF was optically biased by a continuous wave pump laser, whereas the SOA was arranged in a fiber loop-mirror and driven by nanosecond duration current pulses. Laser pulses were obtained by synchronizing the SOA driver to the returning amplified Rayleigh back-scattered light from a selected short section of the EDF. By tuning the SOA pulse rate, random lasing was achieved by addressing selected meter-long sections of the 81-m long EDF, which was open-ended. Laser oscillation can be potentially obtained with SOA modulation frequencies from several kHz to the MHz regime. We discuss the mechanism leading to the hybrid random laser emission, connecting with phase sensitive optical time domain reflectometry and envision potential applications of this electronically addressable random laser.

Ligand-Enabled Gold-Catalyzed C(sp2)-N Cross-Coupling Reactions of Aryl Iodides with Amines.

The first example of ancillary (P,N)-ligand-enabled gold-catalyzed C-N cross-coupling reactions of aryl iodides with amines is reported. The high generality of the reaction in de novo synthesis, late-stage modifications, and cascade processes to access functionalized indolinones and carbazoles underscores the synthetic potential of the presented strategy. Monitoring the reaction with ESI-HRMS and NMR provided strong evidence for the in situ formation of putative high valent Au(III) intermediates.

Variational control forces for enhanced sampling of nonequilibrium molecular dynamics simulations.

We introduce a variational algorithm to estimate the likelihood of a rare event within a nonequilibrium molecular dynamics simulation through the evaluation of an optimal control force. Optimization of a control force within a chosen basis is made possible by explicit forms for the gradients of a cost function in terms of the susceptibility of driven trajectories to changes in variational parameters. We consider probabilities of time-integrated dynamical observables as characterized by their large deviation functions and find that in many cases, the variational estimate is quantitatively accurate. Additionally, we provide expressions to exactly correct the variational estimate that can be evaluated directly. We benchmark this algorithm against the numerically exact solution of a model of a driven particle in a periodic potential, where the control force can be represented with a complete basis. We then demonstrate the utility of the algorithm in a model of repulsive particles on a line, which undergo a dynamical phase transition, resulting in singular changes to the form of the optimal control force. In both systems, we find fast convergence and are able to evaluate large deviation functions with significant increases in statistical efficiency over alternative Monte Carlo approaches.