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Abstract Although first principles based anharmonic lattice dynamics is one of the most common methods to obtain phonon properties, such method is impractical for high-throughput search of target thermal materials. We develop an elemental spatial density neural network force field as a bottom-up approach to accurately predict atomic forces of ~80,000 cubic crystals spanning 63 elements. The primary advantage of our indirect machine learning model is the accessibility of phonon transport physics at the same level as first principles, allowing simultaneous prediction of comprehensive phonon properties from a single model. Training on 3182 first principles data and screening 77,091 unexplored structures, we identify 13,461 dynamically stable cubic structures with ultralow lattice thermal conductivity below 1 Wm −1 K −1 , among which 36 structures are validated by first principles calculations. We propose mean square displacement and bonding-antibonding as two low-cost descriptors to ease the demand of expensive first principles calculations for fast screening ultralow thermal conductivity. Our model also quantitatively reveals the correlation between off-diagonal coherence and diagonal populations and identifies the distinct crossover from particle-like to wave-like heat conduction. Our algorithm is promising for accelerating discovery of novel phononic crystals for emerging applications, such as thermoelectrics, superconductivity, and topological phonons for quantum information technology. 

Abstract Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-material basis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneck with the developed Elemental Spatial Density Neural Network Force Field, namely Elemental-SDNNFF. The effectiveness and precision of our Elemental-SDNNFF approach are demonstrated on 11,866 full, half, and quaternary Heusler structures spanning 55 elements in the periodic table by prediction of complete phonon properties. Self-improvement schemes including active learning and data augmentation techniques provide an abundant 9.4 million atomic data for training. Deep insight into predicted ultralow lattice thermal conductivity (<1 Wm −1  K −1 ) of 774 Heusler structures is gained by p–d orbital hybridization analysis. Additionally, a class of two-band charge-2 Weyl points, referred to as “double Weyl points”, are found in 68% and 87% of 1662 half and 1550 quaternary Heuslers, respectively. 

α-Branched amines are fundamental building blocks in a variety of natural products and pharmaceuticals. Herein is reported a unique cascade reaction that enables the preparation of α-branched amines bearing aryl or alkyl groups at the β- or γ-positions. The cascade is initiated by reduction of redox active esters to alkyl radicals. The resulting alkyl radicals are trapped by styrene derivatives, leading to benzylic radicals. The persistent 2-azaallyl radicals and benzylic radicals are proposed to undergo a radical–radical coupling leading to functionalized amine products. Evidence is provided that the role of the nickel catalyst is to promote formation of the alkyl radical from the redox active ester and not promote the C–C bond formation. The synthetic method introduced herein tolerates a variety of imines and redox active esters, allowing for efficient construction of amine building blocks. 

Abstract Allylation of nucleophiles with highly reactive electrophiles like allyl halides can be conducted without metal catalysts. Less reactive electrophiles, such as allyl esters and carbonates, usually require a transition metal catalyst to facilitate the allylation. Herein, we report a unique transition-metal-free allylation strategy with allyl ether electrophiles. Reaction of a host of allyl ethers with 2-azaallyl anions delivers valuable homoallylic amine derivatives (up to 92%), which are significant in the pharmaceutical industry. Interestingly, no deprotonative isomerization or cyclization of the products were observed. The potential synthetic utility and ease of operation is demonstrated by a gram scale telescoped preparation of a homoallylic amine. In addition, mechanistic studies provide insight into these C(sp 3 )–C(sp 3 ) bond-forming reactions. 

Synopsis The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research. 

A unique enantioselective nickel-catalyzed vinylation of 2-azaallyl anions is advanced for the first time. This method affords diverse vinyl aryl methyl amines with high enantioselectivities, which are frequently occurring scaffolds in natural products and medications. This C–H functionalization method can also be extended to the synthesis of enantioenriched 1,3-diamine derivatives by employing suitably elaborated vinyl bromides. Key to the success of this process is the identification of a Ni/chiraphos catalyst system and a less reducing 2-azaallyl anion, all of which favor an anionic vinylation route over a background radical reaction. A telescoped gram scale synthesis and a product derivatization study confirmed the scalability and synthetic potential of this method. 

A unique C(sp 3 )–H/C(sp 3 )–H dehydrocoupling of N -benzylimines with saturated heterocycles is described. Using super electron donor (SED) 2-azaallyl anions and aryl iodides as electron acceptors, single-electron-transfer (SET) generates an aryl radical. Hydrogen atom transfer (HAT) from saturated heterocycles or toluenes to the aryl radical generates alkyl radicals or benzylic radicals, respectively. The newly formed alkyl radicals and benzylic radicals couple with the 2-azaallyl radicals with formation of new C–C bonds. Experimental evidence supports the key hydrogen-abstraction by the aryl radical, which determines the chemoselectivity of the radical–radical coupling reaction. It is noteworthy that this procedure avoids the use of traditional strong oxidants and transition metals. 

In survival regression analysis, when the time-dependent covariates are censored and measured with errors, a joint model is often considered for the longitudinal covariate data and the survival data. Typically, an empirical linear (mixed) model is assumed for the time-dependent covariates. However, such an empirical linear covariate model may be inappropriate for the (unobserved) censored covariate values that may behave quite differently from the observed covariate process. In applications such as human immunodeficiency virus–acquired immune deficiency syndrome studies, a mechanistic non-linear model can be derived for the covariate process on the basis of the underlying data generation mechanisms and such a non-linear covariate model may provide better ‘predictions’ for the censored and mismeasured covariate values. We propose a joint Cox and non-linear mixed effect model to model survival data with censored and mismeasured time varying covariates. We use likelihood methods for inference, implemented by the Monte Carlo EM algorithm. The models and methods are evaluated by simulations. An acquired immune deficiency syndrome data set is analysed in detail, where the time-dependent covariate is a viral load which may be censored because of a lower detection limit and may also be measured with errors. The results based on linear and non-linear covariate models are compared and new insights are gained.

 

α‐Amino nitriles are versatile structural motifs in a variety of biologically active compounds and pharmaceuticals and they serve as valuable building blocks in synthesis. The preparation of α‐ and β‐functionalized α‐amino nitriles from readily available scaffolds, however, remains challenging. Herein is reported a novel dual catalytic photoredox/copper‐catalyzed chemo‐ and regioselective radical carbocyanation of 2‐azadienes to access functionalized α‐amino nitriles by using redox‐active esters (RAEs) and trimethylsilyl cyanide. This cascade process employs a broad scope of RAEs and provides the corresponding α‐amino nitrile building blocks in 50–95 % yields (51 examples, regioselectivity >95 : 5). The products were transformed into prized α‐amino nitriles and α‐amino acids. Mechanistic studies suggest a radical cascade coupling process.