SummerEyes vs Typeset

In the battle of SummerEyes vs Typeset, which AI Summarizer tool comes out on top? We compare reviews, pricing, alternatives, upvotes, features, and more.

Which one is better? SummerEyes or Typeset?

Upon comparing SummerEyes with Typeset, which are both AI-powered summarizer tools, Typeset is the clear winner in terms of upvotes. Typeset has garnered 24 upvotes, and SummerEyes has garnered 6 upvotes.

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SummerEyes

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Bliro

ChatGPT for your Meetings

What is SummerEyes?

Accelerate Your Online Reading Experience with SummerEyes! This innovative Chrome extension promises to revolutionize the way you interact with text on the internet. Designed to enhance productivity, SummerEyes allows you to summarize any web text with just one click, helping you distill information down to its key points and save precious time. Users benefit from an impressive average reading speed increase of 70%, translating to about 30 minutes saved each day. SummerEyes is not only lightning-fast but also incredibly convenient, living right within your browser. It leverages the most current advancements in Natural Language Processing to deliver quick, on-the-spot summaries. Whether it's long articles, dense emails, or extensive newsletters, SummerEyes helps you cut through the clutter and focus on what truly matters. Installation is a breeze, and once set up on a supported device, this powerful AI-driven tool is ready to streamline your online reading. Get ahead with SummerEyes—the essential browser extension for the fast-paced digital world.

Typeset

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Premium

Bliro

ChatGPT for your Meetings

What is Typeset?

Your platform to explore and explain papers. Search for 270M+ papers, understand them in simple language, and find connected papers, authors, topics.

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Bliro

ChatGPT for your Meetings

SummerEyes Upvotes

Typeset Upvotes

24🏆

SummerEyes Top Features

Blazingly Fast: Instantly condense long articles into concise summaries.
Convenient: Summarize directly within your browser without switching apps.
Powerful AI: Utilizes 400 million parameters for advanced text understanding.
Versatile: Read newsletters articles and company-wide emails effectively.
Easily Installable: Available as a Chrome extension for quick access.

Typeset Top Features

No top features listed

SummerEyes Category

Summarizer

Typeset Category

Summarizer

SummerEyes Pricing Type

Freemium

Typeset Pricing Type

Free

SummerEyes Technologies Used

Typeset Technologies Used

Amazon Web Services

jQuery

Bootstrap

SummerEyes Tags

Text Generation

Summarizer

SEO Optimized

Typeset Tags

Content Summary

AI Whitepapers

AI Emails

SummerEyes Average Rating

No rating available

Typeset Average Rating

4.00

SummerEyes Reviews

No reviews available

Typeset Reviews

Sara Sara

The simulation model validated experimental J-V and external quantum efficiency (EQE) to demonstrate an improvement in perovskite (PSK) solar cell (PSC) efficiency. The effect of interface properties at the electron transport layer (ETL)/PSK and PSK/hole transport layer (HTL) was investigated using the Solar Cell Capacitance Simulator (SCAPS). The interfaces between ETL, PSK, and HTL were identified as critical factors in determining high open-circuit voltage (Voc) and FF. In this study, the impact of two types of interfaces, ETL/PSK and PSK/HTL, were investigated. Lowering the defect density at both interfaces to 102 cm−2 reduced interface recombination and increased Voc and FF.The absorber layer defect density and n/i interface of perovskite solar cells were investigated using the Solar Cell Capacitance Simulator-1D (SCAPS-1D) at various cell thicknesses. The planar p-i-n structure was defined as PEDOT:PSS/Perovskite/CdS, and its performance was calculated. With a defect density of <1014 cm−3 and an absorber layer thickness of >400 nm, power conversion efficiency can exceed 25%. The study assumed a 0.6 eV Gaussian defect energy level beneath the perovskite's conduction band, which has a characteristic energy of 0.1 eV. These conditions produced the same result on the n/i interface. These findings place constraints on numerical simulations of the correlation between defect mechanism and performance

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