Solar-driven hydrogen production from water using particulate photocatalysts is considered the most economical and effective approach to produce hydrogen fuel with little environmental concern. ...However, the efficiency of hydrogen production from water in particulate photocatalysis systems is still low. Here, we propose an efficient biphase photocatalytic system composed of integrated photothermal-photocatalytic materials that use charred wood substrates to convert liquid water to water steam, simultaneously splitting hydrogen under light illumination without additional energy. The photothermal-photocatalytic system exhibits biphase interfaces of photothermally-generated steam/photocatalyst/hydrogen, which significantly reduce the interface barrier and drastically lower the transport resistance of the hydrogen gas by nearly two orders of magnitude. In this work, an impressive hydrogen production rate up to 220.74 μmol h
cm
in the particulate photocatalytic systems has been achieved based on the wood/CoO system, demonstrating that the photothermal-photocatalytic biphase system is cost-effective and greatly advantageous for practical applications.
Lithium (Li) metal is a promising anode material for high‐energy density batteries. However, the unstable and static solid electrolyte interphase (SEI) can be destroyed by the dynamic Li ...plating/stripping behavior on the Li anode surface, leading to side reactions and Li dendrites growth. Herein, we design a smart Li polyacrylic acid (LiPAA) SEI layer high elasticity to address the dynamic Li plating/stripping processes by self‐adapting interface regulation, which is demonstrated by in situ AFM. With the high binding ability and excellent stability of the LiPAA polymer, the smart SEI can significantly reduce the side reactions and improve battery safety markedly. Stable cycling of 700 h is achieved in the LiPAA‐Li/LiPAA‐Li symmetrical cell. The innovative strategy of self‐adapting SEI design is broadly applicable, providing opportunities for use in Li metal anodes
Stretching exercises: A flexible lithium polyacrylic acid (LiPAA) solid electrolyte interphase (SEI) layer which is highly stretchable is designed to address the dynamic volume changes during Li plating/stripping on the Li anode surface in Li ion batteries. The LiPAA polymer SEI can significantly reduce the side reactions and improve the safety performance.
Monolayers of transition metal dichalcogenides can exist in several structural polymorphs, including 2H, 1T and 1T'. The low-symmetry 1T' phase has three orientation variants, resulting from the ...three equivalent directions of Peierls distortion in the parental 1T phase. Using first-principles calculations, we predict that mechanical strain can switch the relative thermodynamic stability between the orientation variants of the 1T' phase. We find that such strain-induced variant switching only requires a few percent elastic strain, which is eminently achievable experimentally with transition metal dichalcogenide monolayers. Calculations indicate that the transformation barrier associated with such variant switching is small (<0.2 eV per chemical formula unit), suggesting that strain-induced variant switching can happen under laboratory conditions. Monolayers of transition metal dichalcogenides with 1T' structure therefore have the potential to be ferroelastic and shape memory materials with interesting domain physics.
Li anodes have been rapidly developed in recent years owing to the rising demand for higher‐energy‐density batteries. However, the safety issues induced by dendrites hinder the practical applications ...of Li anodes. Here, Li metal anodes stabilized by regulating lithium plating/stripping in vertically aligned microchannels are reported. The current density distribution and morphology evolution of the Li deposits on porous Cu current collectors are systematically analyzed. Based on simulations in COMSOL Multiphysics, the tip effect leads to preferential deposition on the microchannel walls, thus taking full advantage of the lightening rod theory of classical electromagnetism for restraining growth of Li dendrites. The Li anode with a porous Cu current collector achieves an enhanced cycle stability and a higher average Coulombic efficiency of 98.5% within 200 cycles. In addition, the resultant LiFePO4/Li full battery demonstrates excellent rate capability and stable cycling performance, thus demonstrating promise as a current collector for high‐energy‐density, safe rechargeable Li batteries.
A new strategy to restrain lithium dendrite growth is proposed and demonstrated using vertically aligned microchannel Cu current collectors for Li metal anodes. Most of the lithium is preferentially deposited into the microchannels. The current‐density distribution, deposition behavior, and electrochemical performance are simulated and investigated experimentally to understand the effectiveness of the microchannel structure.
Quantum spin Hall (QSH) effect materials feature edge states that are topologically protected from backscattering. However, the small band gap in materials that have been identified as QSH insulators ...limits applications. We use first-principles calculations to predict a class of large-gap QSH insulators in two-dimensional transition metal dichalcogenides with IT' structure, namely, 1T'-MX2 with M = (tungsten or molybdenum) and X = (tellurium, selenium, or sulfur). A structural distortion causes an intrinsic band inversion between chalcogenide-p and metal-d bands. Additionally, spin-orbit coupling opens a gap that is tunable by vertical electric field and strain. We propose a topological field effect transistor made of van der Waals heterostructures of 1T'-MX2 and two-dimensional dielectric layers that can be rapidly switched off by electric field through a topological phase transition instead of carrier depletion.
Lithium metal anodes are potentially key for next‐generation energy‐dense batteries because of the extremely high capacity and the ultralow redox potential. However, notorious safety concerns of Li ...metal in liquid electrolytes have significantly retarded its commercialization: on one hand, lithium metal morphological instabilities (LMI) can cause cell shorting and even explosion; on the other hand, breaking of the grown Li arms induces the so‐called “dead Li”; furthermore, the continuous consumption of the liquid electrolyte and cycleable lithium also shortens cell life. The research community has been seeking new strategies to protect Li metal anodes and significant progress has been made in the last decade. Here, an overview of the fundamental understandings of solid electrolyte interphase (SEI) formation, conceptual models, and advanced real‐time characterizations of LMI are presented. Instructed by the conceptual models, strategies including increasing the donatable fluorine concentration (DFC) in liquid to enrich LiF component in SEI, increasing salt concentration (ionic strength) and sacrificial electrolyte additives, building artificial SEI to boost self‐healing of natural SEI, and 3D electrode frameworks to reduce current density and delay Sand's extinction are summarized. Practical challenges in competing with graphite and silicon anodes are outlined.
Conceptual models of lithium metal morphological instabilities (LMIs) are presented. Mitigation strategies including increasing the donatable fluorine concentration (DFC), salt concentrations (ionic strength), and sacrificial electrolyte additives, building an artificial solid electrolyte interphase (SEI) to aid self‐healing of the natural SEI, and 3D electrodes to reduce the current density and delay Sand's extinction are addressed. Practical challenges in competing with graphite and silicon anodes are delineated.
The study of high-throughput genomic profiles from a pharmacogenomics viewpoint has provided unprecedented insights into the oncogenic features modulating drug response. A recent study screened for ...the response of a thousand human cancer cell lines to a wide collection of anti-cancer drugs and illuminated the link between cellular genotypes and vulnerability. However, due to essential differences between cell lines and tumors, to date the translation into predicting drug response in tumors remains challenging. Recently, advances in deep learning have revolutionized bioinformatics and introduced new techniques to the integration of genomic data. Its application on pharmacogenomics may fill the gap between genomics and drug response and improve the prediction of drug response in tumors.
We proposed a deep learning model to predict drug response (DeepDR) based on mutation and expression profiles of a cancer cell or a tumor. The model contains three deep neural networks (DNNs), i) a mutation encoder pre-trained using a large pan-cancer dataset (The Cancer Genome Atlas; TCGA) to abstract core representations of high-dimension mutation data, ii) a pre-trained expression encoder, and iii) a drug response predictor network integrating the first two subnetworks. Given a pair of mutation and expression profiles, the model predicts IC
values of 265 drugs. We trained and tested the model on a dataset of 622 cancer cell lines and achieved an overall prediction performance of mean squared error at 1.96 (log-scale IC
values). The performance was superior in prediction error or stability than two classical methods (linear regression and support vector machine) and four analog DNN models of DeepDR, including DNNs built without TCGA pre-training, partly replaced by principal components, and built on individual types of input data. We then applied the model to predict drug response of 9059 tumors of 33 cancer types. Using per-cancer and pan-cancer settings, the model predicted both known, including EGFR inhibitors in non-small cell lung cancer and tamoxifen in ER+ breast cancer, and novel drug targets, such as vinorelbine for TTN-mutated tumors. The comprehensive analysis further revealed the molecular mechanisms underlying the resistance to a chemotherapeutic drug docetaxel in a pan-cancer setting and the anti-cancer potential of a novel agent, CX-5461, in treating gliomas and hematopoietic malignancies.
Here we present, as far as we know, the first DNN model to translate pharmacogenomics features identified from in vitro drug screening to predict the response of tumors. The results covered both well-studied and novel mechanisms of drug resistance and drug targets. Our model and findings improve the prediction of drug response and the identification of novel therapeutic options.
A
bstract
The transverse momentum distribution of the
t
t
¯
system is of both experimental and theoretical interest. In the presence of azimuthally asymmetric divergences, pursuing resummation at ...high logarithmic precision is rather demanding in general. In this paper, we propose the projected transverse momentum spectrum
d
σ
t
t
¯
/
d
q
τ
, which is derived from the classical
q
→
T
spectrum by integrating out the rejection component
q
τ
⊥
with respect to a reference unit vector
τ
→
, to serve as an alternative solution to remove these asymmetric divergences, in addition to the azimuthally averaged case
d
σ
t
t
¯
/
d
∣
q
→
T
∣
. In the context of the effective field theories, SCET
II
and HQET, we will demonstrate that in spite of the
q
τ
⊥
integrations, the leading asymptotic terms of
d
σ
t
t
¯
/
d
q
τ
still observe the factorisation pattern in terms of the hard, beam, and soft functions in the vicinity of
q
τ
= 0 GeV. Then, with the help of the renormalisation group equation techniques, we carry out the resummation at NLL+NLO, N
2
LL+N
2
LO, and approximate N
2
LL′+N
2
LO accuracy on three observables of interest,
d
σ
t
t
¯
/
d
q
T
,
in
,
d
σ
t
t
¯
/
d
q
T
,
out
, and
d
σ
t
t
¯
/
d
Δ
ϕ
t
t
¯
, within the domain
M
t
t
¯
≥ 400 GeV. The first two cases are obtained by choosing
τ
→
parallel and perpendicular to the top quark transverse momentum, respectively. The azimuthal de-correlation
Δ
ϕ
t
t
¯
of the
t
t
¯
pair is evaluated through its kinematical connection to
q
T
,
out
. This is the first time the azimuthal spectrum
Δ
ϕ
t
t
¯
is appraised at or beyond the N
2
LL level including a consistent treatment of both beam collinear and soft radiation.
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