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Comment Article text (Score -1) 41

Rechargeable lithium-ion batteries, the most popular energy source for mobile electronic devices, are rapidly expanding their range of applications into fields such as electrical vehicles, grid energies, and flexible electronic devices.1 This strong market demand stimulates the need for development of advanced lithium ion battery technologies capable of improving energy storage densities, cycle life, charge/discharge rates, and design flexibility.2, 3

One strategy to address certain of these goals involves advanced structural design in the electrodes, along with associated new material development. For example, three dimensional (3D) electrodes can yield improvements in rate capability and capacity retention.4–6 These advantages are further enhanced in high-capacity anode materials, such as silicon and tin, which undergo large changes in volume during charge/discharge cycling.7, 8 One challenge for 3D electrodes, particularly in integration of active components, arises from difficulties in securing conformal electrolytes that can also prevent electrical shorts between electrodes.6 Although liquid electrolytes ensure excellent electrochemical performance and good physical contact with 3D electrodes, they suffer from potential leakage, leading to safety concerns. More importantly, liquid electrolytes limit choices in cell design due to their fluidic characteristics and the need for separator membranes in cell assembly. This situation motivates the development of self-supporting solid-state electrolytes that can conform to 3D electrodes and, at the same time, provide sufficient mechanical deformability for reliable use, especially for applications in flexible electronics and other demanding areas of envisioned use.

Among various solid-state electrolytes, gel polymer electrolytes (GPEs), which are generally composed of polymer matrix and liquid electrolyte, are widely used in lithium-ion batteries owing to their excellent ionic conductivity, low rates of safety failure, and mechanical flexibility.9–11 In general, conventional GPEs are prepared using a predesigned frame via solution casting of liquid state mixtures (i.e., liquid electrolytes and polymers dissolved in organic solvents or liquid electrolytes/polymerizable monomers), followed by solvent evaporation or chemical cross-linking for solidification. The initial, liquid-state, mixtures for GPEs have limited dimensional stability before solidification due to their intrinsically fluidic characteristics, thereby restricting their facile application to complex-structured systems such as 3D batteries.

To the best of our knowledge, there are no polymer electrolytes that are both shape-conformable to 3D electrodes and mechanically flexible without impairing their electrochemical performance. Moreover, it is still challenging to secure dimensional stability (as a solid form) of polymer electrolytes during electrolyte preparation and cell assembly process.6, 12

In the following, we demonstrate a facile and scalable approach to the fabrication of highly ion-conductive and bendable polymer electrolytes that can be also conformable to 3D micropatterned architectures of electrodes over large areas. These polymer electrolytes can also be directly writable or printable onto substrates of interest (including electrodes with complex geometries) due to well-tuned rheological characteristics. The materials are a kind of composite gel polymer electrolyte (hereinafter, referred to as “c-GPE”), composed of a UV (ultraviolet)-cured ethoxylated trimethylolpropane triacrylate (ETPTA) polymer matrix, high-boiling point liquid electrolyte (1M LiPF6 in ethylene carbonate (EC)/propylene carbonate (PC) = 1/1 (v/v)), and alumina (Al2O3) nanoparticles (Figure 1a). The ETPTA monomer, which contains trivalent vinyl groups that participate in UV-crosslinking,13, 14 serves as a mechanical framework (after UV-curing). The chemical structure of the ETPTA, along with 2-hydroxy-2-methyl-1-phenyl-1-propanon (HMPP, a photo-initiator), appears in Figure S1 in ESI. The Al2O3 nanoparticles are incorporated as a functional filler to control the rheological properties of the electrolyte mixture and enable direct printing on a substrate such as an electrode.

Figure 1. a) Conceptual illustration of an imprintable, flexible, shape-conformable c-GPE. b) Dripping characteristic of a liquid electrolyte that does not incorporate Al2O3 nanoparticles (designated as F-solution). c) Non-dripping behavior of UV-curable electrolyte mixture before UV-crosslinking reaction (designated as V-solution). d) Comparison of viscosity (as a function of shear rate) between the F- and V-solution.

As a control sample, an electrolyte mixture (hereinafter, referred as “F-solution”) comprised of the ETPTA monomer and liquid electrolyte without Al2O3 nanoparticles, was also cast onto an LiCoO2 cathode. Due to its fluidic character, the F-solution flows easily when it is vertically tilted (Figure 1b). By contrast, an otherwise similar solution with Al2O3 nanoparticles (hereinafter, referred as “V-solution”) is highly viscous and undergoes limited flow even before UV crosslinking (Figure 1c). Viscosity measurements reveal that the F-solution exhibits traditional Newtonian behavior, yielding a viscosity of 11 cP. The V-solution, on the other hand, shows a non-Newtonian response, (i.e., typical shear-thinning behavior), wherein the viscosity increases by 4 orders of magnitude as compared to the F-solution (Figure 1d). This unique rheological feature of the V-solution can facilitate its application in writable or printable electrolyte systems.

It should be noted that the rheological behavior of the V-solution depends strongly on composition ratio and dispersion state of the Al2O3 nanoparticles. Here, the Al2O3 content was varied between 33% and 80%, as determined by the amount of Al2O3 in total weight (= Al2O3 + ETPTA + liquid electrolyte) (See Figure S2 in ESI). Among the various compositions, an Al2O3 content of 66% was found to exhibit optimal rheological properties, for printing and comforming to complex-structured substrates.

Direct UV-assisted nanoimprint lithography (UV-NIL)15–18 was exploited to construct 3D shape-comformable polymer electrolytes from the rheologically tuned V-solution. The UV-IL technique is a well known, versatile patterning technology for production of diverse micro- and nanostructures for microelectronics, optoelectronic devices, and high-density magnetic data storage. Here, we used PDMS stamps for UV-NIL, featuring a maze-like structure with a repeating surface grating (wall thickness and height were 10 m, respectively) in 1.5 cm × 1.5 cm dimensions. We also explored silicon anode pillars on a rigid silicon wafer as columnar structure6, 19, of a type that is prefered for 3D electrodes designed to accomodate severe volume change during charge-discharge cycle. These two structures were used to investigate not only the applicability of polymer electrolyte on flexible and rigid substrates but also replication of round and angular patterns. PDMS stamps were formed using the casting and curing procedures of soft lithography with a master fabricated by exposure (365 nm UV mask-aligner; Karl-Suss) of photoresist SU-8 (Micro Chem) on a silicon wafer. Pressing such stamps against cast layers of V-solutions followed by UV exposure through the stamps yielded solid replicas while in contact (Figure 2a). A SEM image of a molded c-GPE with maze patterns demonstrates the high fidelity that can be achieved in this process, where the structures show well-defined vertical edge profiles and high mechanical stability (Figure 2b). A high-magnification, cross sectional SEM image shows that the Al2O3 nanoparticles are uniformly dispersed through the c-GPE (see Figure S3 in ESI).

Figure 2. a) Steps for fabricating an imprintable, bendable, and shape-conformable polymer electrolyte (c-GPE) via direct UV-assisted nanoimprint lithography (UV-NIL) b) A SEM photograph (surface) of a c-GPE with a maze-pattern (an inset is a cross-sectional image). c) Photographs demonstrating highly-bendable and twistable features of c-GPE. d) FT-IR spectra depicting acrylic C = C double bonds of V-solution (before UV-irradiation) and c-GPE (after UV-irradiation).

The mechanical bendability of the c-GPE as a self-standing film (thickness 150 m) was quantitatively measured using a bending test (under longituidinal strain ranged from 10 to 30 mm, strain rate = 10 mmmin1). The c-GPE offers strong resistance to mechanical breakage upon appreciable bending (bending radius 0.5 cm), even at a low concentration of polymer matrix (i.e., ETPTA/liquid electrolyte = 15/85 w/w). Also, the c-GPE retains dimensional stability until the 29th bending cycle. (Fracture occurs upon additional cycles, as in Figure S4 in ESI). The c-GPE was also mechanically stable under the twisting (bending radius 0.35 cm) (Figure 2c) deformations. Moreover, the maze patterns do not distort even after being subjected to five cycles of bending stress (bending radius 0.5 cm) (see Figure S5 in ESI), which reflects the excellent structural stability of the c-GPE.

The FT-IR measurements before and after UV-irradiation show that the characteristic peaks assgined to acrylic C = C bonds (1610 1625 cm1)13, 14 disappear (Figure 2d), which verifies that the crosslinking reaction is successfully completed in the c-GPE. This process was further confirmed by estimating the gel content of c-GPE, after solvent (dimethyl carbonate followed by acetone) extraction to remove the incorporated liquid electrolytes and any unreacted monomers.20 Over 99% by weight remained relative to the initial weight of UV curable monomer. This result verifies that the UV-curing reaction of ETPTA monomer in the c-GPE was nearly complete. The solid electrolyte characteristics (electrochemical stability, ionic conductivity, and cell performance) of the c-GPE are examined. Linear sweep voltammograms indicate that no significant decomposition of any components in the c-GPE takes place below 4.5 V vs. Li/Li+. This high anodic stability suggests potential for application to high-voltage lithium-ion batteries (Figure 3a). Figure 3a shows that the ionic conductivity of the c-GPE is more than 103 S cm1 at room temperature, with values that increase with temperature. Another advantageous feature of the c-GPE is that no weight loss is observed below temperature of 100 C, as observed from the TGA result due to the presence of high-boiling point liquid electrolyte (i.e., 1M LiPF6 in EC/PC) (Figure 3b).

Figure 3. a) Electrochemical stability window for a c-GPE (an inset shows temperature-dependent ionic conductivity of c-GPE). b) TGA profiles showing difference in thermal stability compared to a conventional carbonate-based liquid electrolyte (1M LiPF6 in EC/DEC = 1/1 v/v) and c-GPE. c) Charge/discharge profiles of a cell (lithium metal/flat-shaped c-GPE/LiCoO2 cathode) as a function of cycle number (at a constant charge/discharge current density = 0.5 C/0.5 C under a voltage range of 3.0–4.2 V). d) Cycling performance (= capacity retention with cycling and coulombic efficiency of a cell, lithium metal/flat-shaped c-GPE/LiCoO2 cathode).

Cycling performance of the cell (LiCoO2 cathode/c-GPE/lithium metal anode) was examined using a flat c-GPE film, where the cell was cycled between 3.0 and 4.2 V at a constant charge/discharge current density (= 0.5 C/0.5 C). The cell exhibits highly stable charge/discharge profiles up to the 50th cycle (Figure 3c). In addition, the couloumb efficiency is 97%, thereby contributing to the negligible capacity loss during cycling (Figure 3d).

To explore the feasibility of applying the c-GPE to 3D- electrodes, cells were prepared using silicon anodes that are patterned into arrays of columns supported by similarly structured copper on a silicon wafer. The fabrication involved sputter deposition of silicon to a thickness of 40 nm onto the copper in pillars with heights of 18 m,21 where the electrode area is 0.9 cm × 0.9 cm. The electrode was incorporated into a cell that employs lithium metal as the counter electrode and c-GPE as the solid electrolyte (see Figure S6 in ESI). As shown in Figure 4, an inverse replica of the 3D silicon structure is successfully formed in the c-GPE, allowing good contact with the anode. Analysis of the SEM images (Figure 4c) shows that the imprinted c-GPE has a height (18 m) and radius (153 m), well matched with the dimension of the 3D silicon anode.

Figure 4. a) Charge/discharge profiles of a cell comprising a 3D Si anode/c-GPE/lithium metal as a function of cycle number (at a constant charge/discharge current density = 0.5 C/0.5 C under a voltage range of 0.01–1.5 V). b) A SEM photograph of a 3D pillar (height = 18 m, radius = 153 m) structured current collector. c) A SEM photograph (surface) of inversely-replicated c-GPE (i.e., after being detached from the 3D pillar structured Si anode), where the inset is a cross-sectional image. d) A SEM photograph (surface) of an inversely-replicated c-GPE disassembled from a cell after the 10th cycle of operation (the inset is a cross-sectional image).

Figure 4a shows the cycling performance of the cell (Si anode/c-GPE/Li metal) using inversely-replicated c-GPE as an electrolyte, where the cell was cycled between 0.01 and 1.5 V at a constant charge/discharge current density (= 0.5 C/0.5 C). The cell shows capacity loss due to SEI (solid electrolyte interphase) layer formation at the first cycle and gradual capacity decay afterwards. This charge/discharge behavior of the cell is similar to the previously reported results for 3D Si anodes.22 From a calculation based on the 40 nm thickness silicon, the initial charge (i.e., lithiation of silicon anode) capacity is found to be 2680 mAh g1. Although the capacity retention with cycling is not ideal, because the 3D-structured cells are not optimized, the overall cycling performance is promising compared to that of c-GPE with non-optimized Al2O3 content. Moreover, Figure 4d shows that the inversely-replicated structure of the c-GPE is almost unchanged, even after the 10th cycle, compared to the initial shape (Figure 4c). This result demonstrates dimensional stability in the imprinted c-GPE and verifies the successful application of the shape-conformable c-GPE to the 3D-structured cells. It also suggests that the good cycling performance in the optimized c-GPE formulation results from its outstanding imprintability, shape conformability, flexibility, and electrochemical performance. These attributes can facilitate the development of 3D-structured battery systems.

Figure 5 shows that Al2O3 content of 33% (or 80%) leads to unsuccessful integration on 3D Si anodes due to non-optimized rheological properties, consistent with the previous result (Figure S2). It should be noted that the structure of the imprinted c-GPEs has a significant influence on the cell performance. For instance, c-GPE with Al2O3 content of 33%, where the c-GPE exhibits highly fluidic characteristic, most of the 3D Si anode remains uncoated. As a result, no meaningful charge/discharge reaction is obtained, likely due to internal short-circuit between the anode and cathode. For c-GPE with Al2O3 content of 80%, the Al2O3 nanoparticles agglomerate, and the c-GPE does not completely cover the 3D Si anode. The mechanical compliance diminishes, and large-sized pinholes and cracks appear. Due to this non-uniform morphology of the imprinted c-GPE, the cell assembled with the c-GPE does not provide normal charge/discharge behavior. More specifically, excessively large charge capacity and very low coulombic efficiency ( 9%) at the 1st cycle are observed. The cell in this case might be partially internally short-circuited due to the poorly-imprinted c-GPE on the 3D Si anode.

Figure 5. Charge/discharge profiles of a cell comprising 3D Si anode/non-optimized c-GPE/lithium metal as a function of cycle number (at a constant charge/discharge current density = 0.5 C/0.5 C): (a) Al2O3 content = 33%; (b) Al2O3 content = 80%.

In summary, we successfully fabricated highly ion-conductive, bendable polymer electrolytes that are also conformable to 3D micropatterned architectures of electrodes over large areas. More notably, the polymer electrolytes can be directly writable or printable onto complex, contoured substrates, owing to the structural uniqueness and well-tuned rheological characteristics. A persistent challenge in the development of 3D-structured or flexible batteries is in the maintenance of good contact between polymer electrolytes and electrodes, to facilitate electrochemical reaction at the interface. In this respect, the polymer electrolytes introduced here can be important.

Comment HTFA (Score -1, Flamebait) 233

Efforts over the past decade to characterize the genetic alterations in human cancers have led to a better understanding of molecular drivers of this complex set of diseases. Although we in the cancer field hoped that this would lead to more effective drugs, historically, our ability to translate cancer research to clinical success has been remarkably low1. Sadly, clinical trials in oncology have the highest failure rate compared with other therapeutic areas. Given the high unmet need in oncology, it is understandable that barriers to clinical development may be lower than for other disease areas, and a larger number of drugs with suboptimal preclinical validation will enter oncology trials. However, this low success rate is not sustainable or acceptable, and investigators must reassess their approach to translating discovery research into greater clinical success and impact.

Many factors are responsible for the high failure rate, notwithstanding the inherently difficult nature of this disease. Certainly, the limitations of preclinical tools such as inadequate cancer-cell-line and mouse models2 make it difficult for even the best scientists working in optimal conditions to make a discovery that will ultimately have an impact in the clinic. Issues related to clinical-trial design — such as uncontrolled phase II studies, a reliance on standard criteria for evaluating tumour response and the challenges of selecting patients prospectively — also play a significant part in the dismal success rate3.

S. GSCHMEISSNER/SPL

Many landmark findings in preclinical oncology research are not reproducible, in part because of inadequate cell lines and animal models.

Unquestionably, a significant contributor to failure in oncology trials is the quality of published preclinical data. Drug development relies heavily on the literature, especially with regards to new targets and biology. Moreover, clinical endpoints in cancer are defined mainly in terms of patient survival, rather than by the intermediate endpoints seen in other disciplines (for example, cholesterol levels for statins). Thus, it takes many years before the clinical applicability of initial preclinical observations is known. The results of preclinical studies must therefore be very robust to withstand the rigours and challenges of clinical trials, stemming from the heterogeneity of both tumours and patients.

Confirming research findings
The scientific community assumes that the claims in a preclinical study can be taken at face value — that although there might be some errors in detail, the main message of the paper can be relied on and the data will, for the most part, stand the test of time. Unfortunately, this is not always the case. Although the issue of irreproducible data has been discussed between scientists for decades, it has recently received greater attention (see go.nature.com/q7i2up) as the costs of drug development have increased along with the number of late-stage clinical-trial failures and the demand for more effective therapies.

Over the past decade, before pursuing a particular line of research, scientists (including C.G.B.) in the haematology and oncology department at the biotechnology firm Amgen in Thousand Oaks, California, tried to confirm published findings related to that work. Fifty-three papers were deemed 'landmark' studies (see 'Reproducibility of research findings'). It was acknowledged from the outset that some of the data might not hold up, because papers were deliberately selected that described something completely new, such as fresh approaches to targeting cancers or alternative clinical uses for existing therapeutics. Nevertheless, scientific findings were confirmed in only 6 (11%) cases. Even knowing the limitations of preclinical research, this was a shocking result.

Table 1: Reproducibility of research findings
Preclinical research generates many secondary publications, even when results cannot be reproduced.
Full table
Of course, the validation attempts may have failed because of technical differences or difficulties, despite efforts to ensure that this was not the case. Additional models were also used in the validation, because to drive a drug-development programme it is essential that findings are sufficiently robust and applicable beyond the one narrow experimental model that may have been enough for publication. To address these concerns, when findings could not be reproduced, an attempt was made to contact the original authors, discuss the discrepant findings, exchange reagents and repeat experiments under the authors' direction, occasionally even in the laboratory of the original investigator. These investigators were all competent, well-meaning scientists who truly wanted to make advances in cancer research.

In studies for which findings could be reproduced, authors had paid close attention to controls, reagents, investigator bias and describing the complete data set. For results that could not be reproduced, however, data were not routinely analysed by investigators blinded to the experimental versus control groups. Investigators frequently presented the results of one experiment, such as a single Western-blot analysis. They sometimes said they presented specific experiments that supported their underlying hypothesis, but that were not reflective of the entire data set. There are no guidelines that require all data sets to be reported in a paper; often, original data are removed during the peer review and publication process.

Unfortunately, Amgen's findings are consistent with those of others in industry. A team at Bayer HealthCare in Germany last year reported4 that only about 25% of published preclinical studies could be validated to the point at which projects could continue. Notably, published cancer research represented 70% of the studies analysed in that report, some of which might overlap with the 53 papers examined at Amgen.

Some non-reproducible preclinical papers had spawned an entire field, with hundreds of secondary publications that expanded on elements of the original observation, but did not actually seek to confirm or falsify its fundamental basis. More troubling, some of the research has triggered a series of clinical studies — suggesting that many patients had subjected themselves to a trial of a regimen or agent that probably wouldn't work.

These results, although disturbing, do not mean that the entire system is flawed. There are many examples of outstanding research that has been rapidly and reliably translated into clinical benefit. In 2011, several new cancer drugs were approved, built on robust preclinical data. However, the inability of industry and clinical trials to validate results from the majority of publications on potential therapeutic targets suggests a general, systemic problem. On speaking with many investigators in academia and industry, we found widespread recognition of this issue.

Improving the preclinical environment
How can the robustness of published preclinical cancer research be increased? Clearly there are fundamental problems in both academia and industry in the way such research is conducted and reported. Addressing these systemic issues will require tremendous commitment and a desire to change the prevalent culture. Perhaps the most crucial element for change is to acknowledge that the bar for reproducibility in performing and presenting preclinical studies must be raised.

An enduring challenge in cancer-drug development lies in the erroneous use and misinterpretation of preclinical data from cell lines and animal models. The limitations of preclinical cancer models have been widely reviewed and are largely acknowledged by the field. They include the use of small numbers of poorly characterized tumour cell lines that inadequately recapitulate human disease, an inability to capture the human tumour environment, a poor appreciation of pharmacokinetics and pharmacodynamics, and the use of problematic endpoints and testing strategies. In addition, preclinical testing rarely includes predictive biomarkers that, when advanced to clinical trials, will help to distinguish those patients who are likely to benefit from a drug.

Wide recognition of the limitations in preclinical cancer studies means that business as usual is no longer an option. Cancer researchers must be more rigorous in their approach to preclinical studies. Given the inherent difficulties of mimicking the human micro-environment in preclinical research, reviewers and editors should demand greater thoroughness.

As with clinical studies, preclinical investigators should be blinded to the control and treatment arms, and use only rigorously validated reagents. All experiments should include and show appropriate positive and negative controls. Critical experiments should be repeated, preferably by different investigators in the same lab, and the entire data set must be represented in the final publication. For example, showing data from tumour models in which a drug is inactive, and may not completely fit an original hypothesis, is just as important as showing models in which the hypothesis was confirmed.

Studies should not be published using a single cell line or model, but should include a number of well-characterized cancer cell lines that are representative of the intended patient population. Cancer researchers must commit to making the difficult, time-consuming and costly transition towards new research tools, as well as adopting more robust, predictive tumour models and improved validation strategies. Similarly, efforts to identify patient-selection biomarkers should be mandatory at the outset of drug development.

“The scientific process demands the highest standards of quality, ethics and rigour.”
Ultimately, however, the responsibility for design, analysis and presentation of data rests with investigators, the laboratory and the host institution. All are accountable for poor experimental design, a lack of robust supportive data or selective data presentation. The scientific process demands the highest standards of quality, ethics and rigour.

Building a stronger system
What reasons underlie the publication of erroneous, selective or irreproducible data? The academic system and peer-review process tolerates and perhaps even inadvertently encourages such conduct5. To obtain funding, a job, promotion or tenure, researchers need a strong publication record, often including a first-authored high-impact publication. Journal editors, reviewers and grant-review committees often look for a scientific finding that is simple, clear and complete — a 'perfect' story. It is therefore tempting for investigators to submit selected data sets for publication, or even to massage data to fit the underlying hypothesis.

But there are no perfect stories in biology. In fact, gaps in stories can provide opportunities for further research — for example, a treatment that may work in only some cell lines may allow elucidation of markers of sensitivity or resistance. Journals and grant reviewers must allow for the presentation of imperfect stories, and recognize and reward reproducible results, so that scientists feel less pressure to tell an impossibly perfect story to advance their careers.

Although reviewers, editors and grant-committee members share some responsibility for flaws in the system, investigators must be accountable for the data they generate, analyse and submit. We in the field must remain focused on the purpose of cancer research: to improve the lives of patients. Success in our own careers should be a consequence of outstanding research that has an impact on patients.

The lack of rigour that currently exists around generation and analysis of preclinical data is reminiscent of the situation in clinical research about 50 years ago. The changes that have taken place in clinical-trials processes over that time indicate that changes in prevailing attitudes and philosophies can occur (see 'Improving the reliability of preclinical cancer studies').

Box 1: Recommendations: Improving the reliability of preclinical cancer studies
Full box
Improving preclinical cancer research to the point at which it is reproducible and translatable to clinical-trial success will be an extraordinarily difficult challenge. However, it is important to remember that patients are at the centre of all these efforts. If we in the field forget this, it is easy to lose our sense of focus, transparency and urgency. Cancer researchers are funded by community taxes and by the hard work and philanthropic donations of advocates. More importantly, patients rely on us to embrace innovation, make advances and deliver new therapies that will improve their lives. Although hundreds of thousands of research papers are published annually, too few clinical successes have been produced given the public investment of significant financial resources. We need a system that will facilitate a transparent discovery process that frequently and consistently leads to significant patient benefit.

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